Subjects -> TRANSPORTATION (Total: 216 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (26 journals)
    - RAILROADS (10 journals)
    - ROADS AND TRAFFIC (9 journals)
    - SHIPS AND SHIPPING (39 journals)
    - TRANSPORTATION (123 journals)

TRANSPORTATION (123 journals)                     

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Hybrid Journal   (Followers: 122)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 9)
Applied Mobilities     Hybrid Journal   (Followers: 3)
Archives of Transport     Open Access   (Followers: 18)
Asian Transport Studies     Open Access   (Followers: 1)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 16)
Cities in the 21st Century     Open Access   (Followers: 16)
Danish Journal of Transportation Research / Dansk Tidsskrift for Transportforskning     Open Access   (Followers: 3)
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 2)
Economics of Transportation     Partially Free   (Followers: 14)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
eTransportation     Open Access   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 15)
European Transport Research Review     Open Access   (Followers: 24)
Geosystem Engineering     Hybrid Journal   (Followers: 2)
IATSS Research     Open Access  
IEEE Open Journal of Intelligent Transportation Systems     Open Access   (Followers: 7)
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
IET Electrical Systems in Transportation     Open Access   (Followers: 11)
IET Intelligent Transport Systems     Open Access   (Followers: 12)
IET Smart Cities     Open Access   (Followers: 1)
IFAC-PapersOnLine     Open Access   (Followers: 1)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 11)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 12)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 6)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 11)
International Journal of Electronic Transport     Hybrid Journal   (Followers: 9)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 7)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 16)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 9)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 12)
International Journal of Services Technology and Management     Hybrid Journal   (Followers: 1)
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 19)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 19)
International Journal of Transportation Engineering     Open Access   (Followers: 2)
International Journal of Transportation Science and Technology     Open Access   (Followers: 12)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 16)
Journal of Big Data Analytics in Transportation     Hybrid Journal   (Followers: 2)
Journal of Intelligent and Connected Vehicles     Open Access   (Followers: 2)
Journal of KONES     Open Access  
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 9)
Journal of Navigation     Hybrid Journal   (Followers: 281)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 12)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 3)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 5)
Journal of Transport & Health     Hybrid Journal   (Followers: 12)
Journal of Transport and Land Use     Open Access   (Followers: 26)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 16)
Journal of Transport Geography     Hybrid Journal   (Followers: 28)
Journal of Transport History     Hybrid Journal   (Followers: 13)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 10)
Journal of Transportation Security     Hybrid Journal   (Followers: 2)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 12)
Journal of Transportation Technologies     Open Access   (Followers: 15)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 8)
Journal on Vehicle Routing Algorithms     Hybrid Journal  
Les Dossiers du Grihl     Open Access   (Followers: 1)
LOGI ? Scientific Journal on Transport and Logistics     Open Access   (Followers: 1)
Logistics     Open Access   (Followers: 3)
Logistics & Sustainable Transport     Open Access   (Followers: 6)
Logistique & Management     Hybrid Journal  
Mobility in History     Full-text available via subscription   (Followers: 5)
Modern Transportation     Open Access   (Followers: 12)
Nonlinear Dynamics     Hybrid Journal   (Followers: 20)
Open Journal of Safety Science and Technology     Open Access   (Followers: 17)
Open Transportation Journal     Open Access   (Followers: 1)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 4)
Periodica Polytechnica Transportation Engineering     Open Access  
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 8)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 15)
Promet : Traffic &Transportation     Open Access  
Public Transport     Hybrid Journal   (Followers: 20)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 8)
Revista Transporte y Territorio     Open Access   (Followers: 1)
Revue Marocaine de Management, Logistique et Transport     Open Access  
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 13)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 3)
Streetnotes     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 1)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 7)
Transport     Open Access   (Followers: 17)
Transport and Telecommunication     Open Access   (Followers: 5)
Transport in Porous Media     Hybrid Journal   (Followers: 2)
Transport Problems     Open Access   (Followers: 5)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 10)
Transport technic and technology     Open Access   (Followers: 1)
Transportation     Hybrid Journal   (Followers: 34)
Transportation Engineering     Open Access   (Followers: 1)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation in Developing Economies     Hybrid Journal  
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 17)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 6)
Transportation Research Interdisciplinary Perspectives     Open Access   (Followers: 3)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 41)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 39)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 31)
Transportation Research Procedia     Open Access   (Followers: 7)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 37)
Transportation Safety and Environment     Open Access   (Followers: 2)
Transportation Science     Full-text available via subscription   (Followers: 26)
Transportation Systems and Technology     Open Access  
TRANSPORTES     Open Access   (Followers: 6)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 9)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Transportrecht     Hybrid Journal   (Followers: 1)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 12)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 4)
Urban Development Issues     Open Access   (Followers: 3)
Urban, Planning and Transport Research     Open Access   (Followers: 33)
Vehicles     Open Access  
Vehicular Communications     Full-text available via subscription   (Followers: 4)
World Electric Vehicle Journal     Open Access  
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 6)
Транспортні системи та технології перевезень     Open Access  

           

Similar Journals
Journal Cover
Transportation Research Record : Journal of the Transportation Research Board
Journal Prestige (SJR): 0.589
Citation Impact (citeScore): 1
Number of Followers: 37  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 0361-1981 - ISSN (Online) 2169-4052
Published by TRB Homepage  [1 journal]
  • Florida Department of Transportation’s Enhanced Hydroplaning
           Prediction Tool
    • Authors: Hyung Suk Lee, Mateo Carvajal, Charles Holzschuher, Bouzid Choubane
      Abstract: Transportation Research Record, Ahead of Print.
      Florida Department of Transportation (FDOT) recently developed and implemented a new hydroplaning prediction (HP) program for predicting the traveling speed at which a vehicle would start hydroplaning. The tool was developed as part of the effort to reduce hydroplaning accidents and is being used during the roadway design phase to evaluate the hydroplaning potential of Florida’s roadways. This paper presents an overview of FDOT’s HP program and demonstrates how it may be used. The tool incorporates a total of four water film thickness models and three hydroplaning speed models developed in the past, allowing for a total of 12 model combinations for the hydroplaning analysis. The tool also offers different analysis options that may be used to meet a variety of FDOT’s needs. As demonstrated in this paper, the primary use of the new HP tool is for checking the final geometric roadway design parameters for hydroplaning potential. In addition, the HP program can also be used as a forensic investigation tool for identifying specific locations that exhibit higher potential for hydroplaning.
      Citation: Transportation Research Record
      PubDate: 2021-05-10T01:46:06Z
      DOI: 10.1177/03611981211011479
       
  • Impact of Geometry and Operations on Left-Turn Gap Acceptance at
           Signalized Intersections with Permissive Indication
    • Authors: Boris Claros, Madhav Chitturi, Andrea Bill, David A. Noyce
      Abstract: Transportation Research Record, Ahead of Print.
      Critical and follow-up headways are the foundation for estimating the saturation flow of permissive left-turns at signalized intersections. Current critical and follow-up headways recommended in the 2016 Highway Capacity Manual (HCM) are based on limited data collected from five intersections in Texas in the 1970s. This study analyzed over 2,500 left-turning vehicles at 45 intersection approaches, provides insights into gap acceptance parameters, and evaluates the effect of different site-specific factors. Video data were collected and processed from different geographical regions in the United States—Arizona, Florida, North Carolina, Virginia, and Wisconsin. Using the maximum likelihood method to estimate gap acceptance parameters, the mean critical headway was 4.87 s and the mean follow-up headway was 2.73 s. To account for site-specific characteristics, the effect of several geometric and operational variables on critical and follow-up headway were explored. Through a meta-regression analysis, the posted speed limit and width of opposing travel lanes were found to have a significant effect on gap acceptance parameters. Results showed that with decreasing posted speed limit and width of opposing lanes, critical and follow-up headways also decreased, resulting in greater saturation flows. When site-specific saturation flow estimates were compared with HCM saturation flow estimates, the differences ranged from −30% to +23%. This paper quantifies and illustrates the impact of site-specific characteristics on gap acceptance parameters and saturation flow.
      Citation: Transportation Research Record
      PubDate: 2021-05-10T01:40:14Z
      DOI: 10.1177/03611981211011476
       
  • Long-Distance Airport Substitution and Air Market Leakage: Empirical
           Investigations in the U.S. Midwest
    • Authors: Kaleab Woldeyohannes Yirgu, Amy M. Kim, Megan S. Ryerson
      Abstract: Transportation Research Record, Ahead of Print.
      Following airline mergers and network reorganizations aimed at reducing operational costs, consolidated air services at large hub airports have encouraged air travelers to forego use of their smaller local airports to access large hub airports offering superior air services farther away. This study investigates airport leakage in areas of Wisconsin and Michigan served by small airports, where air travelers may leak to neighboring large hubs. Using a proximity-based service area definition, three airports experiencing leakage are identified, and a hierarchical logit airport choice model is applied that accounts for air service characteristics and access distance for travelers coming from these airports’ service areas. Results show that a similar mean number of flight legs at both the local and substitute (large hub) airports will encourage leakage at Dane County Regional and Gerald R. Ford International airports, indicating that adding direct flights alone will not be sufficient to combat leakage. Comparable access distances to local and substitute airports have opposite effects on the local markets of Gerald R. Ford International and Milwaukee Mitchell International airports—promoting leakage at the former but discouraging it at the latter. Furthermore, proportional increases in airfares at local airports lead to uneven losses of markets in investigated service areas. Overall, the study provides empirical evidence of long-distance airport leakage in parts of the U.S. Midwest, and how its implications can be used by small airports seeking to further understand and respond to travelers’ airport choices within their local markets.
      Citation: Transportation Research Record
      PubDate: 2021-05-08T10:19:22Z
      DOI: 10.1177/03611981211010797
       
  • Speeds of Right-Turning Vehicles at Signalized Intersections during Green
           or Yellow Phase
    • Authors: Kay Fitzpatrick, Michael P. Pratt, Raul Avelar
      Abstract: Transportation Research Record, Ahead of Print.
      The operation and design of signalized intersections involves tradeoffs between operational efficiency and safety for a variety of users, including motorists, pedestrians, and bicyclists. Additionally, the mix of vehicle types in the fleet sometimes requires special considerations. These concerns especially apply to the selection of curb radius at the corners, where right-turning vehicles operate close to pedestrians. Larger curb radii accommodate the swept paths of trucks and allow right turns to occur at higher speeds but may compromise safety and security for pedestrians by increasing the crossing distance and increasing the frequency of higher-speed turns. The authors collected right-turn vehicle speeds at 31 urban signalized intersection approaches in Texas with radii ranging from 15 to 70 ft. The authors calibrated a model to predict right-turn speeds as a function of site characteristics including curb radius, leading headway, vehicle type (car versus truck), maneuver of the preceding vehicle (through versus right turn), and signal indication (yellow or green). The analysis results indicate that right-turn speeds increase slightly with increasing radius, if the preceding vehicle proceeds through (rather than turning right) at the intersection, or if the signal indication is yellow rather than green. The calculated 85th percentile turning speed is generally higher than the assumed speed calculated using the radius of curvature equation. These trends should be considered if the intersection is expected to have notable volumes of pedestrians or trucks, as lower speeds are desirable for pedestrian safety, but larger radii may be necessary to accommodate turning trucks.
      Citation: Transportation Research Record
      PubDate: 2021-05-07T06:29:13Z
      DOI: 10.1177/03611981211011642
       
  • Precision Scheduled Railroading and the Need for Improved Estimates of
           Yard Capacity and Performance Considering Traffic Complexity
    • Authors: C. Tyler Dick
      Abstract: Transportation Research Record, Ahead of Print.
      Multiple North American freight railroads have adopted concepts of Precision Scheduled Railroading (PSR) that attempt to reduce costs by maximizing train length and minimizing railcar transit time. To achieve these objectives, PSR emphasizes pre-blocking traffic and operating general-purpose trains. These changes have altered the nature of operations at many classification yards, leading to yard closures and conversions to different yard types. Difficulty in implementing PSR-inspired operating practices at yards suggests the industry requires improved estimates of classification yard performance and capacity. While volume-based approaches may be adequate when yard operations are consistent with historical experience, it is hypothesized that approaches considering overall traffic complexity will offer improved predictions when changes are also made to the number of blocks and trains assembled in the yard. An original simulation model of a classification yard pull-down process is used to investigate this hypothesis. The simulation results suggest that a combination of factors describing yard traffic complexity can be a better predictor of yard performance than volume alone. The results are also transformed into a capacity constraint that describes the interaction between the maximum allowable daily number of railcars, blocks, and trains processed by a classification yard. Better understanding of these relationships can aid practitioners and researchers in improving network blocking models and developing train plans that properly use available yard capacity under PSR and other operating plans, reducing the likelihood of future network disturbances and congestion events.
      Citation: Transportation Research Record
      PubDate: 2021-05-07T06:27:33Z
      DOI: 10.1177/03611981211011486
       
  • Balancing the Service Benefits and Mainline Delay Disbenefits of Operating
           Shorter Freight Trains
    • Authors: Adrian Diaz de Rivera, C. Tyler Dick, Matthew M. Parkes
      Abstract: Transportation Research Record, Ahead of Print.
      Advanced train control systems enabling single-person crews or driverless trains promise to significantly reduce the fixed costs of operating a train, removing a strong incentive for longer trains. For carload freight traffic, operating a given number of railcars in shorter trains enables railroads to improve service quality and revenue through increased train frequencies or more direct trains bypassing intermediate classification yards. However, operating shorter trains increases the total number of trains on existing rail corridors, exacerbating congestion and decreasing network fluidity. Rail Traffic Controller simulation software is used to quantify the potential mainline delay impacts and relative capacity consumption of shorter trains. Different combinations of train length and train type heterogeneity are tested on representative single-track freight corridors. Results indicate that train control systems with moving blocks can mitigate some of the mainline delay impacts of shorter trains, particularly at a high traffic volume, with a mix of train types and a greater proportion of railcars traveling on short trains. Mid-siding crossovers can further boost the effectiveness of moving blocks in managing complex train conflicts caused by train type heterogeneity. Simulation results are used to perform an example railcar transit time estimation illustrating the trade-off between yard connection time benefits and mainline delay disbenefits, and the thresholds at which different operating strategies produce a net transit time benefit. Understanding the mainline delay impacts of shorter trains can assist railroad practitioners formulating long-term capital investment plans, developing future operating strategies, and improving service quality and market share through a short train philosophy.
      Citation: Transportation Research Record
      PubDate: 2021-05-07T06:24:11Z
      DOI: 10.1177/03611981211011484
       
  • Multi-Objective Evaluation Model of Single-Lane Roundabouts
    • Authors: Hend Ahmed, Said M. Easa
      Abstract: Transportation Research Record, Ahead of Print.
      Mobility, safety, and environmental sustainability are priorities in the geometric design of roundabouts. This paper presents a multi-objective optimization model that determines the geometric design elements of single-lane roundabouts using all three objectives. The user can specify weights for the objectives, or the model can determine the optimal weights. Mobility is defined in terms of roundabout delay and modeled using the United Kingdom empirical model. Safety is modeled in terms of collision frequency based on the methodology of the Highway Safety Manual. Environmental sustainability is represented by vehicle emissions (nitrogen oxides, hydrocarbons, carbon dioxide, and carbon monoxide) and is modeled using the vehicle-specific power methodology. The proposed model directly identifies the optimal geometric dimensions (decision variables) of the roundabout, including entry width, exit width, approach half-width, circulatory width, effective flare length, entry radius, entry angle, and inscribed circle diameter. The input data to the model include traffic data, site conditions, and limitations based on design guidelines. Application of the proposed model is illustrated using two actual roundabouts. The comparison results show that the proposed model provides substantial improvements in safety, mobility, and environmental sustainability compared with existing conditions. In addition, the model requires much less effort to apply compared with the traditional iterative method, and as such should be of interest to highway designers.
      Citation: Transportation Research Record
      PubDate: 2021-05-07T06:22:52Z
      DOI: 10.1177/03611981211011478
       
  • Dynamically Collected Local Density using Low-Cost Lidar and its
           Application to Traffic Models
    • Authors: Azhagan Avr, Shams Tanvir, Nagui M. Rouphail, Ishtiak Ahmed
      Abstract: Transportation Research Record, Ahead of Print.
      This article demonstrates the use of traffic density observations collected dynamically in the vicinity of probe vehicles. Fixed position sensors cannot capture the longitudinal evolution of local traffic density in the corridor. In this research, dynamic traffic density observations were collected in a naturalistic driving setting that was free of any controlled experiment biases. Speed from global positioning system and space headway from a light detection and ranging module was collected on one arterial and one freeway segment, 2 and 4 mi long, respectively. The combined data frequency was approximately 3 Hz. Space headway was used to estimate the local density and consequently to identify the density of a specific location in a corridor. Besides, driver behavior was characterized using the relationship between instantaneous speed and local density under different regimes of the Wiedemann car-following model. Macroscopic traffic stream models were used to investigate the relationship between dynamically collected instantaneous speed and local density. Using the longitudinal evolution of density, precise local density across the corridor can be obtained along with the leader and follower trajectories. A method to identify driver behavior across density ranges was developed for different facility types using a microscopic relationship between instantaneous speed and local density. Overall driving behavior on the freeway segment can be represented by translating the instantaneous speed and local density relationship to macroscopic stream models.
      Citation: Transportation Research Record
      PubDate: 2021-05-07T06:20:51Z
      DOI: 10.1177/03611981211010184
       
  • Driver Expectations toward Strategic Routing
    • Authors: Alexander Kröller, Falk Hüffner, Łukasz Kosma, Katja Kröller, Mattia Zeni
      Abstract: Transportation Research Record, Ahead of Print.
      Strategic Routing is a traffic intervention mechanism. To reduce traffic in a certain area, drivers are asked to take a pre-defined route diverting them from the area, even though this increases their travel time. This can be implemented with navigation apps or in-dash navigation from navigation service providers such as TomTom or Google. Triggered by a traffic authority, the driver receives information through the service provider’s infrastructure and user interface about a new route and potentially a reward. In this work, we investigate the dynamics between traffic authority, service provider, and end user by analyzing user expectations. Ultimately, service providers are competing for customers. They can, therefore, only implement strategic routing if it appeals to drivers rather than scares them away. We report on the insights of a two-stage study with 457 participants, exploring what kind of strategic routing interventions are appreciated by drivers. We find that drivers report a high interest in seeing diversion suggestions, even when they are not inclined to take them. However, they are unwilling to have their route adapted automatically. Important factors affecting drivers’ willingness to divert are the reason for the detour and the additional driving time. Incentives do increase the efficacy, but only marginally increase user appreciation, indicating that users may mistrust strategic routing that relies too strongly on incentives.
      Citation: Transportation Research Record
      PubDate: 2021-05-07T06:18:49Z
      DOI: 10.1177/03611981211006426
       
  • Hidden Markov Model of Lane-Changing-Based Car-Following Behavior on
           Freeways using Naturalistic Driving Data
    • Authors: Li Zhao, Laurence Rilett, Mm Shakiul Haque
      Abstract: Transportation Research Record, Ahead of Print.
      This paper develops a methodology for simultaneously modeling lane-changing and car-following behavior of automated vehicles on freeways. Naturalistic driving data from the Safety Pilot Model Deployment (SPMD) program are used. First, a framework to process the SPMD data is proposed using various data analytics techniques including data fusion, data mining, and machine learning. Second, pairs of automated host vehicle and their corresponding front vehicle are identified along with their lane-change and car-following relationship data. Using these data, a lane-changing-based car-following (LCCF) model, which explicitly considers lane-change and car-following behavior simultaneously, is developed. The LCCF model is based on Gaussian-mixture-based hidden Markov model theory and is disaggregated into two processes: LCCF association and LCCF dissociation. These categories are based on the result of the lane change. The overall goal is to predict a driver’s lane-change intention using the LCCF model. Results show that the model can predict the lane-change event in the order of 0.6 to 1.3 s before the moment of the vehicle body across the lane boundary. In addition, the execution times of lane-change maneuvers average between 0.55 and 0.86 s. The LCCF model allows the intention time and execution time of driver’s lane-change behavior to be forecast, which will help to develop better advanced driver assistance systems for vehicle controls with respect to lane-change and car-following warning functions.
      Citation: Transportation Research Record
      PubDate: 2021-05-07T06:17:06Z
      DOI: 10.1177/0361198121999382
       
  • Prioritizing Pedestrian and Bicyclist Count Locations for Volume
           Estimation
    • Authors: Jessica Schoner, Frank Proulx, Katherine Knapp de Orvañanos, Brian Almdale
      Abstract: Transportation Research Record, Ahead of Print.
      As data collection programs grow, cities need a way to systematically deploy counting equipment in a way that ensures robust pedestrian and bicyclist volume data are collected across a spectrum of use patterns and infrastructure contexts. This paper presents the findings from a deep dive into pedestrian and bicyclist volumes and exposure, including statistical modeling, as well as translating the outputs into an algorithm for systematically growing Seattle Department of Transportation’s nonmotorized count data collection program. The data collection location prioritization algorithm described in this paper provides a roadmap for cities and other agencies as they build their nonmotorized data collection programs.
      Citation: Transportation Research Record
      PubDate: 2021-05-06T12:47:47Z
      DOI: 10.1177/03611981211011164
       
  • Vehicle Dimensions Based Passenger Car Classification using Fuzzy and
           Non-Fuzzy Clustering Methods
    • Authors: Naghmeh Niroomand, Christian Bach, Miriam Elser
      Abstract: Transportation Research Record, Ahead of Print.
      There has been globally continuous growth in passenger car sizes and types over the past few decades. To assess the development of vehicular specifications in this context and to evaluate changes in powertrain technologies depending on surrounding frame conditions, such as charging stations and vehicle taxation policy, we need a detailed understanding of the vehicle fleet composition. This paper aims therefore to introduce a novel mathematical approach to segment passenger vehicles based on dimensions features using a means fuzzy clustering algorithm, Fuzzy C-means (FCM), and a non-fuzzy clustering algorithm, K-means (KM). We analyze the performance of the proposed algorithms and compare them with Swiss expert segmentation. Experiments on the real data sets demonstrate that the FCM classifier has better correlation with the expert segmentation than KM. Furthermore, the outputs from FCM with five clusters show that the proposed algorithm has a superior performance for accurate vehicle categorization because of its capacity to recognize and consolidate dimension attributes from the unsupervised data set. Its performance in categorizing vehicles was promising with an average accuracy rate of 79% and an average positive predictive value of 75%.
      Citation: Transportation Research Record
      PubDate: 2021-05-06T12:43:26Z
      DOI: 10.1177/03611981211010795
       
  • Investigation of Surrogate Performance Related Tests for Fatigue Cracking
           of Asphalt Pavements
    • Authors: Liya Jiao, John T. Harvey, Mohamed Elkashef, Yanlong Liang, David Jones
      Abstract: Transportation Research Record, Ahead of Print.
      This paper studies the relationship between laboratory measurements of fatigue performance and fracture performance of conventional asphalt mixtures, asphalt mixtures with reclaimed asphalt pavement (RAP), and rubberized asphalt mixtures. The existing four-point bending (4PB) test was developed to evaluate the fatigue performance of asphalt pavements; however, it is not necessarily appropriate for use in routine job mix formula approval and is too slow and expensive for quality control/quality assurance (QC/QA). In this paper, the semi-circular bending test and indirect tensile asphalt cracking test (IDEAL-CT) were evaluated for their potential to serve as a simple and fast surrogate fatigue performance related test for QC/QA on routine projects and routine mix design. Multiple representative fracture parameters were obtained from the Illinois flexibility index test and the IDEAL-CT. The coefficient of variation revealed that the lowest variability from both tests was in fracture strength. In addition, the linear regression analysis between fracture parameters and fatigue performance indicated that slopes, fracture toughness, and strength from fracture tests have good correlations with the initial flexural stiffness from 4PB tests, while 4PB initial stiffness is well correlated with fatigue life. The direct correlation between fracture properties and fatigue life was not as good. The fracture parameter “strength” also showed the capability of discriminating among asphalt materials with low RAP content.
      Citation: Transportation Research Record
      PubDate: 2021-05-06T12:42:04Z
      DOI: 10.1177/03611981211010182
       
  • Virus Transmission Risk in Urban Rail Systems: Microscopic
           Simulation-Based Analysis of Spatio-Temporal Characteristics
    • Authors: Jiali Zhou, Haris N. Koutsopoulos
      Abstract: Transportation Research Record, Ahead of Print.
      The transmission risk of airborne diseases in public transportation systems is a concern. This paper proposes a modified Wells-Riley model for risk analysis in public transportation systems to capture the passenger flow characteristics, including spatial and temporal patterns, in the number of boarding and alighting passengers, and in number of infectors. The model is used to assess overall risk as a function of origin–destination flows, actual operations, and factors such as mask-wearing and ventilation. The model is integrated with a microscopic simulation model of subway operations (SimMETRO). Using actual data from a subway system, a case study explores the impact of different factors on transmission risk, including mask-wearing, ventilation rates, infectiousness levels of disease, and carrier rates. In general, mask-wearing and ventilation are effective under various demand levels, infectiousness levels, and carrier rates. Mask-wearing is more effective in mitigating risks. Impacts from operations and service frequency are also evaluated, emphasizing the importance of maintaining reliable, frequent operations in lowering transmission risks. Risk spatial patterns are also explored, highlighting locations of higher risk.
      Citation: Transportation Research Record
      PubDate: 2021-05-06T12:41:02Z
      DOI: 10.1177/03611981211010181
       
  • Connected Vehicle-Cooperative Adaptive Cruise Control Algorithm to Divide
           and Reform Connected Vehicle Platoons at Signalized Intersections to
           Improve Traffic Throughput and Safety
    • Authors: Yuwei Bie, Tony Z. Qiu
      Abstract: Transportation Research Record, Ahead of Print.
      The cooperative adaptive cruise control (CACC) algorithm is a simple and effective way to form small-headway platoons so that road capacity and traffic throughput can be improved. The CACC algorithm has been broadly discussed in relation to the highway driving environment where frequent stopping and merging are uncommon. This paper proposes that CACC can also benefit urban arterials, using the appropriate algorithm to predict platoon behavior with optimized trajectories to divide and reform platoons before and after signalized intersections, thus maintaining small, safe headways. Connected vehicle (CV) technology is the key to adapting and improving the CACC algorithm, as it enables the signal phasing plan to be sent to a target CACC platoon and allows vehicles to acquire real-time information from other vehicles in the platoon. In this research, a CV-CACC algorithm is proposed consisting of two functions: platoon division and platoon reforming. The new algorithm is also equipped with acceleration as a new control variable instead of speed, so that the platoon is able to accommodate sharp speed changes around intersections, something the baseline CACC is unable to accommodate. In this study, computer simulations have been conducted to test the reliability of the CV-CACC algorithm and compare its performance against the baseline CACC algorithm.
      Citation: Transportation Research Record
      PubDate: 2021-05-06T12:38:43Z
      DOI: 10.1177/03611981211005456
       
  • Level Crossing Safety Impact Assessments for Vehicle and Pedestrian
           Crossings
    • Authors: Shane Turner, Eddie Cook, Shaun Bosher
      Abstract: Transportation Research Record, Ahead of Print.
      Although the number of deaths and injuries at level crossings in New Zealand is relatively low compared with the national road toll and injury burden, the high severity of crashes involving trains makes it a key “safe system” focus. It is also alarming that the proportion of crashes involving pedestrians and cyclists at level crossings has been increasing over recent years. This in part is owing to the construction of several cycleways and shared paths that travel alongside railway lines. In the past, KiwiRail has relied primarily on the Australian Level Crossing Assessment Model (ALCAM), a crash estimation model, to assess the increased risk of crashes at crossings resulting from a change in use. Although ALCAM is one of the better developed level crossing models internationally, it does have its limitations when used in isolation. ALCAM documentation specifies that other information such as incident data and the opinions of locomotive engineers should be considered in assessing risk. In practice, these factors and ALCAM risk ratings are rarely afforded equal importance. ALCAM does not pick up in sufficient detail the safety impacts created by the surrounding transport network. To better inform decision making, KiwiRail has developed a wider assessment process that includes these factors: the Level Crossing Safety Impact Assessment (LCSIA). This paper outlines the LCSIA process, provides an example of how it has been used, and also discusses the important learnings that have occurred since it was first introduced in 2016.
      Citation: Transportation Research Record
      PubDate: 2021-05-05T12:41:18Z
      DOI: 10.1177/03611981211007857
       
  • Vision for Mechanistic-Empirical Railway Track System and Component
           Analysis and Design
    • Authors: J. Riley Edwards, Ricardo J. Quirós-Orozco, Josué César Bastos, Marcus S. Dersch, Erol Tutumluer
      Abstract: Transportation Research Record, Ahead of Print.
      Many analytical methods and other processes have been developed for the evaluation of railway track and its components, but these have largely been used for analysis. Design is often driven by development projects that do not engage research, resulting in designs that may not be optimized in the context of the broader track structure. This paper proposes a mechanistic-empirical (M-E) analysis and design framework that encourages an understanding of mechanical load-response behavior and comparison of loading demands, and the capacity of the track infrastructure component under study. The approach builds on similar advancements in the field of highway pavement research, including the development and use of the Mechanistic-Empirical Pavement Design Guide (MEPDG). Rail applications present unique economies to a focused M-E design approach, given that loads are concentrated in localized regions and beneath the rails. This paper first reviews prior design and analysis approaches, then presents the essential features of an M-E railway track system and component analysis and design, and, in the end, notes gaps that will require future research before proper implementation of M-E design within rail engineering. The authors also discuss the role of probabilistic design and structural reliability analysis in future design practices. Finally, governing mechanistic failure modes for the track system as well as components and associated life cycle data to achieve full implementation of such an M-E design process are identified and a path forward for implementation is proposed.
      Citation: Transportation Research Record
      PubDate: 2021-05-05T12:39:01Z
      DOI: 10.1177/03611981211009881
       
  • Lane-Change Gaming Decision Control Based on Multiple Targets Evaluation
           for Autonomous Vehicle
    • Authors: Yangyang Wang, Hangyun Deng, Guangda Chen
      Abstract: Transportation Research Record, Ahead of Print.
      Automatic lane change is one of the most important highway operations. It seriously affects traffic efficiency and safety. It is also an important driving technology for automatic driving. To achieve the best automatic lane-change control, it is necessary to achieve the control from the perspective of multi-objective evaluation. In this paper, to make it applicable for a hybrid condition of car following and lane change, the traditional car-following model is modified by regarding the longitudinal motion during the lane-changing process as a transition of the car-following behavior in the two lanes before and after a certain lane-change behavior. A hyperbolic tangent transition function is introduced to connect the model to achieve a smooth transition of the model output. Then, the discretionary lane-change decision process of highway autonomous vehicles is modeled into a two-vehicle game model, and a comprehensive loss function concerning safety, efficiency, and ride comfort is proposed for the evaluation of the strategies. The optimal strategy is obtained by minimizing the expectation of losses. Finally, to verify the performance of the proposed new model, simulations of different car-following and lane-changing models are carried out, which is for multi-target simulation conditions. The results of the simulation show that the new model exhibits higher traffic efficiency, better homogeneity, and stability.
      Citation: Transportation Research Record
      PubDate: 2021-05-03T12:06:35Z
      DOI: 10.1177/03611981211011167
       
  • Assessment of Arterial Signal Timings Based on Various Operational
           Policies and Optimization Tools
    • Authors: Suhaib Al Shayeb, Nemanja Dobrota, Aleksandar Stevanovic, Nikola Mitrovic
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic simulation and optimization tools are classified, according to their practical applicability, into two main categories: theoretical and practical. The performance of the optimized signal timing derived by any tool is influenced by how calculations are executed in the particular tool. Highway Capacity Software (HCS) and Vistro implement the procedures defined in the Highway Capacity Manual, thus they are essentially utilized by traffic operations and design engineers. Considering its capability of timing diagram drafting and travel time collection studies, Tru-Traffic is more commonly used by practitioners. All these programs have different built-in objective function(s) to develop optimized signal plans for intersections. In this study, the performance of the optimal signal timing plans developed by HCS, Tru-Traffic, and Vistro are evaluated and compared by using the microsimulation software Vissim. A real-world urban arterial with 20 intersections and heavy traffic in Fort Lauderdale, Florida served as the testbed. To eliminate any bias in the comparisons, all experiments were performed under identical geometric and traffic conditions, coded in each tool. The evaluation of the optimized plans was conducted based on average delay, number of stops, performance index, travel time, and percentage of arrivals on green. Results indicated that although timings developed in HCS reduced delay, they drastically increased number of stops. Tru-Traffic signal timings, when only offsets are optimized, performed better than timings developed by all of the other tools. Finally, Vistro increased arrivals on green, but it also increased delay. Optimized signal plans were transferred manually from optimization tools to Vissim. Therefore, future research should find methods for automatically transferring optimized plans to Vissim.
      Citation: Transportation Research Record
      PubDate: 2021-05-03T12:04:09Z
      DOI: 10.1177/03611981211011165
       
  • Performance-Based and Evidence-Based Approach to Research Implementation
           at the Georgia Department of Transportation
    • Authors: Binh Bui, Adjo Amekudzi-Kennedy, Russell Clark, Janille Smith-Colin, Stephanie Amoaning-Yankson
      Abstract: Transportation Research Record, Ahead of Print.
      This paper discusses the Georgia Department of Transportation’s (GDOT’s) performance-based and evidence-based approach to research implementation. Transportation agencies in the United States spend hundreds of millions of dollars on research, development, and technology transfer annually. From a performance-based standpoint, agencies will realize higher returns on investment and higher impacts of their research programs as research is implemented more effectively and efficiently. From an evidence-based standpoint, requesting evidence of research implementation as implementation deliverables from the outset of the project requires the project research team and other staff to think through and incorporate in the project plan explicit ways in which the research will be implemented. GDOT’s performance-based approach to research program management treats research implementation as part of an overall asset management business process. This process integrates technical, human, organizational, and external resources to encourage, track, and monitor research implementation activities toward achieving agency strategic objectives, using an evidence-based approach. The paper discusses the adoption of a performance-based and evidence-based process, and a research implementation management tool, and their application in the development of the fiscal year 2018 Annual Research Implementation Report as well as its impact within and beyond the agency. This paper is potentially useful to transportation practitioners and agencies that want to adopt a performance-based and evidence-based approach to augment return on research investment.
      Citation: Transportation Research Record
      PubDate: 2021-05-03T12:02:35Z
      DOI: 10.1177/03611981211005466
       
  • Some New Developments in Two-Way-Stop-Controlled Intersections Procedures
           and Recommendations for a Future Version of the Highway Capacity Manual
    • Authors: Ning Wu, Werner Brilon
      Abstract: Transportation Research Record, Ahead of Print.
      The estimation of capacities and traffic performance at two-way-stop-controlled (TWSC) intersections has been the subject of investigations conducted by many researchers. The results of these investigations are incorporated in highway capacity manuals like the U.S. Highway Capacity Manual (HCM) or the German Handbuch für die Bemessung von Strassen (HBS). Although the underlying methodologies are similar, there are two major differences between the current HBS 2015 and HCM6: (a) the procedure for the impedance factor for movements of rank 4 and (b) the procedure for estimating the capacity of shared short lanes for both minor and major movements. In HBS 2015, new developments are accounted for and the accuracy of capacity and traffic quality estimations significantly improved. In HCM6, these two procedures have not been updated. Therefore, the replacement of the two procedures in HCM6 is recommended. In both HCM6 and HBS 2015, the procedures for calculating delays at shared lanes or shared short lanes are inaccurate and they also should be updated. In most cases, the delays are significantly underestimated. Recently, the authors have developed a new methodology dealing with this problem which can be easily incorporated into future versions of HBS and HCM. In this paper, the theoretical backgrounds of the three new methods are presented and major results are summarized. Compared with HCM6, the advantages of the new developments are highlighted. As a recommendation, three corresponding procedures for estimation of capacity and delay are given for potential use in a future version of HCM.
      Citation: Transportation Research Record
      PubDate: 2021-04-30T07:22:05Z
      DOI: 10.1177/03611981211007844
       
  • Deriving Operational Traffic Signal Performance Measures from Vehicle
           Trajectory Data
    • Authors: Enrique Saldivar-Carranza, Howell Li, Jijo Mathew, Margaret Hunter, James Sturdevant, Darcy M. Bullock
      Abstract: Transportation Research Record, Ahead of Print.
      Operations-oriented traffic signal performance measures are important for identifying the need for retiming to improve traffic signal operations. Currently, most traffic signal performance measures are obtained from high-resolution traffic signal controller event data, which provides information on an intersection-by-intersection basis and requires significant initial capital investment. Over 400 billion vehicle trajectory points are generated each month in the United States. This paper proposes using high-fidelity vehicle trajectory data to produce traffic signal performance measures such as: split failure, downstream blockage, and quality of progression, as well as traditional Highway Capacity Manual level of service. Geo-fences are created at specific signalized intersections to filter vehicle waypoints that lie within the generated boundaries. These waypoints are then converted into trajectories that are relative to the intersection. A case study is presented that summarizes the performance of an eight-intersection corridor with four different timing plans using over 160,000 trajectories and 1.4 million GPS samples collected during weekdays in July 2019 between 5:00 a.m. and 10:00 p.m. The paper concludes by commenting on current probe data penetration rates, indicating that these techniques can be applied to corridors with annual average daily traffic of ~15,000 vehicles per day for the mainline approaches, and discussing cloud-based implementation opportunities.
      Citation: Transportation Research Record
      PubDate: 2021-04-30T07:21:21Z
      DOI: 10.1177/03611981211006725
       
  • Evaluating the Durability of Lime-Stabilized Soil Mixtures using Soil
           Mineralogy and Computational Geochemistry
    • Authors: Pavan Akula, Saureen Rajesh Naik, Dallas N. Little
      Abstract: Transportation Research Record, Ahead of Print.
      Lime stabilization is a common technique used to improve the engineering properties of clayey soils. The process of lime stabilization can be split into two parts. First, the mobilization and crowding of [math] ions or [math]molecules from hydrated lime at net negative surface charge sites on expansive clay colloids. Second, the formation of pozzolanic products including calcium-silicate-hydrate (C-S-H) because of reactions within lime-soil mixtures. The pozzolanic reaction is generally considered to be more durable, while the [math] adsorption has been associated with more easily reversible consistency changes. This study offers a protocol to assess whether the stabilization process is dominated by durable C-S-H (pozzolanic) reactions or a combination of cation exchange and pozzolanic reactions. Expansive clays with plasticity indices>45% from a major highway project in Texas are the focus of lime treatment in this study. The protocol consists of subjecting lime-soil mixtures to a reasonable curing period followed by a rigorous but realistic durability test and investigating the quality and quantity of the pozzolanic reaction product. Mineralogical analyses using quantitative X-ray diffraction (XRD) and thermogravimetric analysis (TGA) indicates the formation of different forms of C-S-H. In addition, geochemical modeling is used to simulate the lime-soil reactions and evaluate the effect of pH on the stability of C-S-H. The results indicate C-S-H with Ca/Si ratio of 0.66 as most the stable form of C-S-H among other forms with Ca/Si ratio ranging from 0.66 to 2.25. The effect of reducing equilibrium pH on C-S-H is also evaluated. A reduction in pH favored dissolution of all forms of C-S-H indicating the need to maintain a pH ≥ 10.
      Citation: Transportation Research Record
      PubDate: 2021-04-30T07:20:44Z
      DOI: 10.1177/03611981211007848
       
  • Reliability-Based Assessment of Potential Risk for Lane-Changing Maneuvers
    • Authors: Yang-Jun Joo, Ho-Chul Park, Seung-Young Kho, Dong-Kyu Kim
      Abstract: Transportation Research Record, Ahead of Print.
      Despite the urgent need for continuous risk assessments during autonomous driving, achieving reliable assessment results is still challenging because of the unpredictable behaviors of adjacent human drivers and the resulting complexity. Such complexity increases particularly during lane changes because several vehicles need to interact with other vehicles. Therefore, this paper proposes a new framework to analyze lane-changing risk on freeways considering the forecastability in adjacent vehicles. Virtual lane-change scenarios are constructed based on historical maneuvers in adjacent vehicles, and the risk of potential lane change is evaluated through the safety evaluation result of the scenario. Adjacent vehicles’ future maneuvers are predicted using a multivariate Bayesian structural time series model, and the forecastability is estimated as the standard error of the predicted values. The failure probability of those lane-changing scenarios is obtained through the first-order reliability method, assuming that failure occurred when any time-to-collision value for adjacent vehicles was less than a threshold at the end of the lane change. This study tested two scenarios with three levels of uncertainty to show the effect of uncertainty on the level of risk. The results showed that the reduced uncertainty allowed a clearer distinction between risky situations. The proposed framework differentiates itself from existing methods by estimating higher risk in an adjacent vehicle’s more significant uncertainties. It is expected that the outcome of this study will be valuable in developing reliable lane-change strategies in autonomous driving.
      Citation: Transportation Research Record
      PubDate: 2021-04-30T07:20:27Z
      DOI: 10.1177/03611981211010800
       
  • Slip Coefficient Testing of ASTM A709 Grade 50CR and Dissimilar Metal
           Bolted Connections
    • Authors: Jason T. Provines, Haddis Abebe
      Abstract: Transportation Research Record, Ahead of Print.
      The purpose of this study was to conduct slip coefficient testing of bolted connections made from ASTM A709 Grade 50CR steel to determine how they fit into the current AASHTO LRFD Bridge Design Specifications surface condition classifications. At this time, Grade 50CR steel is not included in these classifications because it was not being used for bridges when the existing surface condition classifications were developed. The slip coefficient tests in this study were conducted according to the Research Council of Structural Connections. Some test specimens were made up entirely of Grade 50CR steel, while others were dissimilar metal connections, consisting of Grade 50CR steel and either weathering or galvanized steel. Dissimilar metal connections were included in the testing because their use is anticipated in which a bridge girder would be constructed using both Grade 50CR steel and other ASTM A709 bridge steels. Results showed that unblasted Grade 50CR steel has a slip coefficient value of at least 0.30, meeting the current AASHTO Class A surface condition for unblasted steel. Blast-cleaned Grade 50CR steel from either steel shot or garnet media has a slip coefficient value of 0.50, meeting the current AASHTO Class B surface condition for blast-cleaned steel. When dissimilar metal connections are made with Grade 50CR steel, the design slip coefficient value of the connection can be taken as equal to the smaller of the two slip coefficient values being joined.
      Citation: Transportation Research Record
      PubDate: 2021-04-29T10:53:28Z
      DOI: 10.1177/03611981211008890
       
  • Forecasting U.S. Maritime Incidents using the Grey-Markov Model
    • Authors: Fatima Zouhair, Jerome Kerby
      Abstract: Transportation Research Record, Ahead of Print.
      Vessel incidents periodically occur in the waterways of the United States, but some types of commercial vessels have shown a downward trend in the number of incidents in recent years. One of the missions of the United States Coast Guard (USCG) is to develop regulations to mitigate and potentially prevent maritime incidents. In this paper, the USCG gathered data on more than 117,000 incidents that involved U.S.-flag vessels in U.S. waterways for the period 2001 through 2018. We applied the Grey System theory or model and Grey-Markov forecasting model to predict the future number of vessel incidents for four different vessel types from 2019 through 2030. Incident data can vary considerably from year to year and often can be incomplete. The Grey-Markov model, which is a combination of the Grey model and the Markov chain process, is suitable for this purpose because of its predictive ability. From our results, we found that the Grey-Markov model performed exceptionally well and showed the predicted values of the number of incidents to be remarkably similar to the actual values with acceptable mean relative errors ranging from 5.2% to 8.2%. We expect that these results will benefit decision makers in formulating sound policies thereby improving the maritime safety of vessels operating in waterways of the United States.
      Citation: Transportation Research Record
      PubDate: 2021-04-29T10:53:26Z
      DOI: 10.1177/03611981211009219
       
  • Performance of Waterproofing Membranes to Protect Concrete Bridge Decks
    • Authors: Matthew A. Haynes, Erdem Coleri, Ihsan Obaid
      Abstract: Transportation Research Record, Ahead of Print.
      The installation of waterproofing membranes on concrete bridge decks is a commonly used strategy to prevent water on the roadway surface from penetrating into the deck and to reduce the load and freeze–thaw related damage to the bridge deck. Typically, an asphalt layer is paved over the waterproofing membrane to prevent damage from heavy vehicles. The early failure of asphalt pavement overlays on concrete bridge decks with waterproofing membranes has been recognized as a significant issue by several transportation agencies. Potential reasons for the failure of the asphalt overlay were thought to be poor adhesion between the waterproofing membrane and the asphalt wearing course, and the material properties of the asphalt layer. By determining the most effective waterproofing methods and strategies, this research will serve to decrease repair and replacement costs, and increase the service life of asphalt overlays on concrete bridge decks. The main goals of this study are to provide the industry and transportation agencies with better insight into the failure mechanisms of asphalt overlays on concrete bridge decks and to establish field and laboratory experiments to evaluate the performance of these overlays. From the results of this study, a poured waterproofing membrane was recommended as an ideal membrane for use on concrete bridge decks because of its ease of installation, complete impermeability, and high bond strengths between the concrete deck, membrane layers, and asphalt overlay.
      Citation: Transportation Research Record
      PubDate: 2021-04-29T10:52:59Z
      DOI: 10.1177/03611981211009527
       
  • Measuring Instantaneous Resilience of a Highway Bridge Subjected to
           Earthquake Events
    • Authors: S. Hooman Ghasemi, Ji Yun Lee
      Abstract: Transportation Research Record, Ahead of Print.
      Bridges in a road network play a significant role in supporting the flows of people, goods, and freight during an earthquake event and are expected to maintain their functionality following the event. Thus, measuring the capability of a bridge immediately following an earthquake event is critical for understanding the post-earthquake functionalities of transportation networks and supply chain systems involving highway bridges. To this end, this paper proposes a new metric for measuring the resistant capacity of a highway immediately following an earthquake event, which is here called instantaneous resilience. The proposed metric first compares the reliability indices of a bridge before and following an earthquake event to measure the immediate earthquake impact. Although this comparison (i.e., robustness measure in this paper) indicates the remaining strength of the bridge subjected to a given earthquake event, it does not reflect collapse failure modes appropriately. Therefore, the proposed instantaneous-resilience metric combines the robustness measure with the structural redundancy measure to consider various scenarios of load path distribution. The proposed metric is computationally efficient because, in the process, it utilizes a generalized reliability-intensity (R-I) surface of a bridge which can be used to calculate the pre- and post-earthquake reliabilities of any bridge designed based on the American Association of State Highway and Transportation Officials (AASHTO) load and resistance factor design (LRFD). Without developing bridge-specific fragility curves and performing structural analysis of a bridge, the proposed measure enables engineers to make a preliminary assessment of the immediate impact of the earthquake on bridges on a quantitative basis. The step-by-step calculation process of the proposed instantaneous-resilience of a bridge is presented, and its potential use in highway network performance assessment is illustrated with a simple hypothetical network system.
      Citation: Transportation Research Record
      PubDate: 2021-04-29T10:52:41Z
      DOI: 10.1177/03611981211009546
       
  • Investigating Head-On Crash Severity Involving Commercial Motor Vehicles
           in Kentucky
    • Authors: James Smith, Mehdi Hosseinpour, Ryan Mains, Nathanael Hummel, Kirolos Haleem
      Abstract: Transportation Research Record, Ahead of Print.
      This study examines various features affecting the severity associated with commercial motor vehicle (CMV, i.e., large truck and bus) head-on collisions on Kentucky highways. Recent five-year (2015–2019) crash data and variables rarely explored before (e.g., presence of centerline rumble strips, type of passing zone, and terrain type) were collected and prepared using Google Maps. A total of 378 CMV-related head-on collisions were analyzed. The generalized ordered probit (GOP) model was employed to identify the significant factors affecting the severity level resulting from CMV head-on collisions. The model allows the coefficients to vary across the injury severity categories for reliable parameter estimations. From the preliminary investigation, rolling terrains had the highest share of severe CMV head-on crashes (62% and 71% for multilane and two-lane roadways, respectively). The presence of centerline rumble strips could reduce severe crash outcomes along multilane and two-lane facilities. The GOP model identified various significant predictors of minor and severe injuries from CMV head-on crashes. Occupants wearing seatbelt were 39.3% less likely to sustain severe head-on crash injuries. From the roadway characteristics, presence of median cable and concrete barriers could significantly reduce the probability of severe head-on crash injuries, with median cables being more effective. With regard to the driver characteristics, drug impairment and speeding increased the risk of sustaining fatal/serious injuries by 39.5% and 26.4%, respectively. Necessary safety recommendations are proposed to reduce the severity of CMV head-on-related collisions. One example is installing median cable barriers along roadway stretches with a history of head-on CMV-related crashes.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T09:13:34Z
      DOI: 10.1177/03611981211010803
       
  • Effect of Changing a Traffic Control Device Color on Driver Behavior and
           Perception across Different Age Groups
    • Authors: Hatem Abou-Senna, Mohamed El-Agroudy, Mustapha Mouloua, Essam Radwan
      Abstract: Transportation Research Record, Ahead of Print.
      The use of express lanes (ELs) in freeway traffic management has seen increasing popularity throughout the United States, particularly in Florida. These lanes aim at making the most efficient transportation system management and operations tool to provide a more reliable trip. An important component of ELs is the channelizing devices used to delineate the separation between the ELs and the general-purpose lane. With the upcoming changes to the FHWA Manual on Uniform Traffic Control Devices, this study provided an opportunity to recommend changes affecting safety and efficiency on a nationwide level. It was important to understand the impacts on driver perception and performance in response to the color of the EL delineators. It was also valuable to understand the differences between demographics in responding to delineator colors under different driving conditions. The driving simulator was used to test the responses of several demographic groups to changes in marker color and driving conditions. Furthermore, participants were tested for several factors relevant to driving performance including visual and subjective responses to the changes in colors and driving conditions. Impacts on driver perception were observed via eye-tracking technology with changes to time of day, visibility, traffic density, roadway surface type, and, crucially, color of the delineating devices. The analyses concluded that white was the optimal and most significant color for notice of delineators across the majority of subjective and performance measures, followed by yellow, with black being the least desirable.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T09:10:41Z
      DOI: 10.1177/03611981211011168
       
  • Measuring Pedestrian Level of Stress in Urban Environments: Naturalistic
           Walking Pilot Study
    • Authors: Seth LaJeunesse, Paul Ryus, Wesley Kumfer, Sirisha Kothuri, Krista Nordback
      Abstract: Transportation Research Record, Ahead of Print.
      Walking is the most basic and sustainable mode of transportation, and many jurisdictions would like to see increased walking rates as a way of reducing congestion and emission levels and improving public health. In the United States, walking trips account for 10.5% of all trips undertaken. To increase this rate, additional research on what makes people feel more comfortable while walking is needed. Research on pedestrian quality of service (QOS) has sought to quantify the performance of the pedestrian facilities from a pedestrian’s perspective. However, the impact of pedestrian safety countermeasures on pedestrian QOS for roadway crossings is largely unknown. The objective of this study is to discern pedestrian QOS based on physiological measurements of pedestrians performing normal walking activities in different traffic contexts. The naturalistic walking study described in this paper recruited 15 pedestrians and asked each to wear an instrumented wristband and GPS recorder on all walking trips for one week. Surprisingly, the findings from the study showed no correlation between participants’ stress levels and individual crossing locations. Instead, stress was associated with roadway conditions. Higher levels of stress were generally associated with walking in proximity to collector and arterial streets and in areas with industrial and mixed (e.g., offices, retail, residential) land uses. Stress levels were tempered in lower-density residential land uses, as well as in forest, park, and university campus environments. The outcomes from this study can inform how planners design urban environments that reduce pedestrian stress levels to promote walkability.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T09:08:41Z
      DOI: 10.1177/03611981211010183
       
  • Examining Driver Injury Severity in Single-Vehicle Road Departure Crashes
           Involving Large Trucks
    • Authors: Mehdi Hosseinpour, Kirolos Haleem
      Abstract: Transportation Research Record, Ahead of Print.
      Road departure (RD) crashes are among the most severe crashes that can result in fatal or serious injuries, especially when involving large trucks. Most previous studies neglected to incorporate both roadside and median hazards into large-truck RD crash severity analysis. The objective of this study was to identify the significant factors affecting driver injury severity in single-vehicle RD crashes involving large trucks. A random-parameters ordered probit (RPOP) model was developed using extensive crash data collected on roadways in the state of Kentucky between 2015 and 2019. The RPOP model results showed that the effect of local roadways, the natural logarithm of annual average daily traffic (AADT), the presence of median concrete barriers, cable barrier-involved collisions, and dry surfaces were found to be random across the crash observations. The results also showed that older drivers, ejected drivers, and drivers trapped in their truck were more likely to sustain severe single-vehicle RD crashes. Other variables increasing the probability of driver injury severity have included rural areas, dry road surfaces, higher speed limits, single-unit truck types, principal arterials, overturning-consequences, truck fire occurrence, segments with median concrete barriers, and roadside fixed object strikes. On the other hand, wearing seatbelt, local roads and minor collectors, higher AADT, and hitting median cable barriers were associated with lower injury severities. Potential safety countermeasures from the study findings include installing median cable barriers and flattening steep roadside embankments along those roadway stretches with high history of RD large-truck-related crashes.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T09:06:41Z
      DOI: 10.1177/03611981211010178
       
  • Factors Affecting Driver Injury Severity in the Wrong-Way Crash:
           Accounting for Potential Heterogeneity in Means and Variances of Random
           Parameters
    • Authors: Miao Yu, Jinxing Shen, Changxi Ma
      Abstract: Transportation Research Record, Ahead of Print.
      Because of the high percentage of fatalities and severe injuries in wrong-way driving (WWD) crashes, numerous studies have focused on identifying contributing factors to the occurrence of WWD crashes. However, a limited number of research effort has investigated the factors associated with driver injury-severity in WWD crashes. This study intends to bridge the gap using a random parameter logit model with heterogeneity in means and variances approach that can account for the unobserved heterogeneity in the data set. Police-reported crash data collected from 2014 to 2017 in North Carolina are used. Four injury-severity levels are defined: fatal injury, severe injury, possible injury, and no injury. Explanatory variables, including driver characteristics, roadway characteristics, environmental characteristics, and crash characteristics, are used. Estimation results demonstrate that factors, including the involvement of alcohol, rural area, principal arterial, high speed limit (>60 mph), dark-lighted conditions, run-off-road collision, and head-on collision, significantly increase the severity levels in WWD crashes. Several policy implications are designed and recommended based on findings.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T09:05:01Z
      DOI: 10.1177/03611981211009882
       
  • Assessment of Commercial Truck Driver Injury Severity as a Result of
           Driving Actions
    • Authors: Muhammad Tahmidul Haq, Milan Zlatkovic, Khaled Ksaibati
      Abstract: Transportation Research Record, Ahead of Print.
      The disaggregate modeling approach is a new trend in the literature to analyze the injury severity of truck-involved crashes. The assessment of truck driver injury severity based on driver action is still missing in the literature. This paper presents an extensive exploratory analysis that highlights significant variability in the severity of truck drivers’ injuries based on various action types (i.e., aggressive driving, failure to keep proper lane, driving too fast, and no improper driving). Binary logistic regression with the Bayesian random intercept approach was developed to examine the factors contributing to fatal or any injuries of truck drivers using 10 years (2007–2016) of historical crash data in Wyoming. Log-likelihood ratio tests were performed to justify that separate models by various driving action types are warranted. The results demonstrated the effects of various vehicle, driver, crash, and roadway characteristics, combined with truck driver-specific action, on the corresponding severity of driver injury. The gross vehicle weight, age and gender of the driver, time of day, lighting condition, and the presence of junctions were found to have significantly different impacts on the severity of truck driver injury in various driving action-related crashes. With the incorporation of the random intercept in the modeling procedure, the analysis found a strong presence (27%–33%) of intra-crash correlation in driver injury severity within the same crash. Finally, based on the findings of this study, several recommendations are made.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T09:02:41Z
      DOI: 10.1177/03611981211009880
       
  • Field Density Investigation of Asphalt Mixtures in Minnesota
    • Authors: Tianhao Yan, Mihai Marasteanu, Chelsea Bennett, John Garrity
      Abstract: Transportation Research Record, Ahead of Print.
      In a current research effort, University of Minnesota and Minnesota Department of Transportation have been working on designing asphalt mixtures that can be constructed at 5% air voids, similar to the Superpave 5 mix design. High field density of asphalt mixtures is desired because it increases the durability and extends the service life of asphalt pavements. The paper investigates the current situation of field densities in Minnesota, to better understand how much improvement is needed from the current field density level to the desired level, and to identify possible changes to the current mix design to improve field compactability. Field densities and material properties of 15 recently constructed projects in Minnesota are investigated. First, a statistical analysis is performed to study the probability distribution of field densities. Then, a two-way analysis of variance is conducted to check if the nominal maximum aggregate size and traffic levels have any significant effect on field densities. A correlation analysis is then conducted to identify significant correlations between the compactability of mixtures and their material properties. The results show that the field density data approximately obey normal distribution, with an average field density of 93.4% of theoretical maximum specific gravity; there are significant differences in field density between mixtures with different traffic levels; compactability of mixtures is significantly correlated with fine aggregate angularity and fine aggregate gradation of the mixtures.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T09:00:20Z
      DOI: 10.1177/03611981211009545
       
  • Development of a Novel Intelligent Speed Adaptation System Based on
           Available Sight Distance
    • Authors: Abrar Hazoor, Alessandra Lioi, Marco Bassani
      Abstract: Transportation Research Record, Ahead of Print.
      Most existing roads were designed without considering the improved performance of modern vehicles and the new onboard technologies available for assisted driving. In addition, vehicles frequently travel at speeds that exceed the maximum considered in road design. For these reasons, the need for speed- and safety-related countermeasures (e.g., field control, mobile or fixed speed cameras, traffic calming measures) is evident. However, these countermeasures are only partially effective and the proportion of crashes that are speed-related remains significant. This investigation is aimed at the development of a new intelligent speed adaptation (ISA) system based on the available sight distance (ASD). In conditions of poor visibility, the system can (i) inform drivers when they are traveling at inappropriate speeds, or (ii) generate warning sounds to the same effect, or (iii) intervene directly and compel the vehicle to adopt the speed which is most appropriate to the particular ASD. As reported in this methodological paper, the functionality of the new ISA system was tested at the driving simulator of the Politecnico di Torino (Italy) and the resulting estimated ASD value was validated and tested successfully. Future experimental investigations will be devoted to assessing the effectiveness of the system on driver speed behavior and decision making.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T08:57:53Z
      DOI: 10.1177/03611981211008885
       
  • Cable Median Barrier Effect on Commercial Vehicle Crossover Crashes
    • Authors: Nikiforos Stamatiadis, Shraddha Sagar, Samantha Wright, Eric Green, Reginald Souleyrette
      Abstract: Transportation Research Record, Ahead of Print.
      In the United States (U.S.) the annual number of commercial motor vehicle (CMV) crashes has been on an upward trajectory since 2009. In 2016, CMV crashes accounted for 11.8% of all fatal crashes in the U.S., and in Kentucky, between 2009 and 2016, the number of CMV crashes rose 27%. Of particular concern to state departments of transportation have been crossover crashes involving CMVs. These occur when a vehicle leaves its intended path and veers into the path of oncoming traffic, typically resulting in head-on or sideswipe opposite direction collisions. While some researchers have found that installing cable median barriers can mitigate crossover crashes involving CMVs, no definitive conclusions have been reached. To move toward a resolution of this question, this study leveraged analysis by a panel of experts and the development of safety performance functions and crash modification factors to gauge how cable median barriers can influence the number and severity of crossover CMV crashes on Kentucky interstate routes. Expert panelists contended that cable median barriers will improve safety, a conclusion substantiated by statistical modeling. Despite the study’s limited scope, it appears that installing cable median barriers can prevent or mitigate CMV crashes.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T08:56:10Z
      DOI: 10.1177/03611981211007845
       
  • Driving Maneuvers Detection using Semi-Supervised Long Short-Term Memory
           and Smartphone Sensors
    • Authors: Pei Li, Mohamed Abdel-Aty, Zubayer Islam
      Abstract: Transportation Research Record, Ahead of Print.
      Driving maneuvers detection is an important component of proactive traffic safety management and connected vehicle systems. Most of the existing studies used supervised learning concepts to train their models with labeled data. These methods achieved promising results but were limited by the heavy dependence on the labeled data. With the development of mobile sensing technologies, massive traffic-related data can be efficiently collected by mobile devices (e.g., smartphones, tablets, etc.). Considering the high costs of labeling data, this paper proposed a semi-supervised deep learning method to learn from the unlabeled data. Data from a smartphone’s accelerometer and gyroscope were collected by different drivers with a variety of smartphones, vehicles, and locations. Three long short-term memory (LSTM) models were trained with the proposed semi-supervised learning algorithm. Experimental results indicated that the proposed semi-supervised LSTM could learn from the unlabeled data and achieve outstanding results with only a small portion of the labeled data. Using much fewer labeled data, semi-supervised LSTM could achieve similar results compared with the supervised method. Moreover, the proposed method outperformed other machine learning methods (e.g., convolutional neural network, XGBoost, random forest) on precision, recall, F1-score, and area under curve. More and more traffic data will be available in the future, the proposed method is expected to make use of the undiscovered potential from the massive unlabeled data.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T08:53:34Z
      DOI: 10.1177/03611981211007483
       
  • Automated Detection and Classification of Pavement Distresses using 3D
           Pavement Surface Images and Deep Learning
    • Authors: Rohit Ghosh, Omar Smadi
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement distresses lead to pavement deterioration and failure. Accurate identification and classification of distresses helps agencies evaluate the condition of their pavement infrastructure and assists in decision-making processes on pavement maintenance and rehabilitation. The state of the art is automated pavement distress detection using vision-based methods. This study implements two deep learning techniques, Faster Region-based Convolutional Neural Networks (R-CNN) and You Only Look Once (YOLO) v3, for automated distress detection and classification of high resolution (1,800 × 1,200) three-dimensional (3D) asphalt and concrete pavement images. The training and validation dataset contained 625 images that included distresses manually annotated with bounding boxes representing the location and types of distresses and 798 no-distress images. Data augmentation was performed to enable more balanced representation of class labels and prevent overfitting. YOLO and Faster R-CNN achieved 89.8% and 89.6% accuracy respectively. Precision-recall curves were used to determine the average precision (AP), which is the area under the precision-recall curve. The AP values for YOLO and Faster R-CNN were 90.2% and 89.2% respectively, indicating strong performance for both models. Receiver operating characteristic (ROC) curves were also developed to determine the area under the curve, and the resulting area under the curve values of 0.96 for YOLO and 0.95 for Faster R-CNN also indicate robust performance. Finally, the models were evaluated by developing confusion matrices comparing our proposed model with manual quality assurance and quality control (QA/QC) results performed on automated pavement data. A very high level of match to manual QA/QC, namely 97.6% for YOLO and 96.9% for Faster R-CNN, suggest the proposed methodology has potential as a replacement for manual QA/QC.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T08:50:33Z
      DOI: 10.1177/03611981211007481
       
  • Modeling CO2 Emissions from Trips using Urban Air Mobility and Emerging
           Automobile Technologies
    • Authors: Sai V. Mudumba, Hsun Chao, Apoorv Maheshwari, Daniel A. DeLaurentis, William A. Crossley
      Abstract: Transportation Research Record, Ahead of Print.
      Urban air mobility (UAM) operations provide the potential for more, or more attractive, trips in a metropolitan area relative to wholly surface-based transportation. But the emissions produced by a UAM mode must be studied in relation to these benefits. In this paper, an emissions model for the UAM context using electric vertical takeoff and landing (eVTOL) aircraft is developed that incorporates CO2 gases emitted from the electricity production required to charge the vehicle batteries. The model quantifies trip emissions using UAM for part or all of the trip and compares these with automobile-based trips. The estimations consider using gasoline and electric automobiles, with the impact of autonomy and average ground speeds in traffic. Trip case studies in the Chicago and Dallas metropolitan areas showcase the regional differences when using UAM and different automobile technology scenarios. In particular, differences stemming from how electricity generation from power grids (i.e., grid emission index) contributes to CO2 emissions of eVTOL trips and electric automobile trips in the Chicago and Dallas metropolitan areas are computed. This paper introduces trip properties called the surface-to-air distance ratio and the detour ratio to understand how they influence the CO2 emissions of a trip. Results from the simulation on identified trip cases in Chicago and Dallas illustrate the significant impact of the grid emission index of a region’s power plant on the emissions of electric vehicles.
      Citation: Transportation Research Record
      PubDate: 2021-04-28T08:47:35Z
      DOI: 10.1177/03611981211006439
       
  • Comparing Regional Sustainability and Transportation Sustainability at the
           Metropolitan Level in the U.S. using Artificial Neural Network Clustering
           Techniques
    • Authors: Haiqing Liu, Na Chen, Xinhao Wang
      Abstract: Transportation Research Record, Ahead of Print.
      Regional sustainability and transportation sustainability have been intensely discussed and analyzed in recent decades. Though the use of indicators has been adopted in those models, debates continue on what indicators should be used and how to optimize the number of indicators. This results in the lack of a comprehensive and efficient method to assess and compare the sustainability of a sub-system, such as transportation system, and overall regional sustainability. A thorough literature review is conducted to identify indicators used to assess regional sustainability and transportation sustainability. Then, based on the available data, two sets of indicators for regional sustainability and transportation sustainability are identified and calculated respectively for the 382 metropolitan statistical areas (MSAs) in the U.S. A self-organizing map, which is a type of artificial neural network, is used to cluster the MSAs and compare their regional sustainability and transportation sustainability as well as to investigate the relationships among indicators. The results show that MSAs with a higher score on regional sustainability do not necessarily have a higher score on transportation sustainability. Some MSAs that are geographically close to each other have similar scores in regional sustainability and transportation sustainability. These findings provide insights to decision makers that the assessment of sustainability should consider both correlation and heterogeneity of different indicators within a region. Therefore, it is important to develop a comprehensive and efficient method to evaluate the role of sustainability in one urban sub-system, such as transportation, in the overall regional sustainability.
      Citation: Transportation Research Record
      PubDate: 2021-04-27T07:56:42Z
      DOI: 10.1177/03611981211009519
       
  • Meso-Scale Kinematic Responses of Asphalt Mixture in Both Field and
           Laboratory Compaction
    • Authors: Xue Wang, Shihui Shen, Hai Huang
      Abstract: Transportation Research Record, Ahead of Print.
      Compaction is one of the most critical steps in asphalt pavement construction. Traditional compaction relies heavily on engineering experience and post-construction quality control and can lead to under/over compaction problems. The emerging intelligent compaction technology has improved compaction quality but is still not successful in obtaining mixture properties of a single pavement layer. Besides, very few studies have discussed the internal material responses during field and laboratory compaction to explain the meso-scale (i.e., particle scale) compaction mechanism. Knowledge in those areas may greatly promote the development of smart compaction. Therefore, this study aims to investigate the kinematic behavior of the asphalt mixture particles (translation and rotation) under six types of field and laboratory compaction methods and establish the relationship between the field and the laboratory compaction by using a real-time particle motion sensor, SmartRock. It was found that particle movement pattern was mainly affected by the compaction mode. At the meso-scale where particle behavior is the focus, the kneading effects of a pneumatic-tire roller can be simulated by laboratory gyratory and rolling wheel compaction, and the vibrating effects of a vibratory roller can be simulated by Marshall compaction. However, none of those laboratory compaction methods can completely simulate the field compaction. Under vibratory rolling, particle acceleration decreased fast in the breakdown rolling stage. Under pneumatic-tire rolling, particle angular position change was related to aggregate skeleton, and particle relative rotation showed a decreasing trend that was consistent with the laboratory gyratory compaction results. Those kinematic responses can potentially be used to monitor density change in field compaction.
      Citation: Transportation Research Record
      PubDate: 2021-04-27T07:54:10Z
      DOI: 10.1177/03611981211009222
       
  • Use of the Pavement Surface Cracking Metric to Quantify Distresses from
           Digital Images
    • Authors: Danilo Balzarini, James Erskine, Michael Nieminen
      Abstract: Transportation Research Record, Ahead of Print.
      The development of new laser technologies in recent years has changed pavement data collection, opening the door to a fully automated approach. In this paper the application of the Pavement Surface Cracking Metric (PSCM), inspired by the Universal Cracking Indicator proposed by William Paterson in 1994, and developed by the ASTM E17 group is presented. The method uses quantitative definitions to ensure consistency of the results and eliminate the subjectivity associated with human ratings of pavement distresses. Multiple runs of pavement data have been collected on three asphalt sections to assess the repeatability and reproducibility of the method. The application of the Pavement Surface Cracking Index to convert the PSCM value, which is a physical property of the pavement, into a 100-0 score of the pavement section is also presented. Finally, the use of the PSCM to classify pavement distress and the inclusion of potholes and patching in the metrics are discussed.
      Citation: Transportation Research Record
      PubDate: 2021-04-27T07:53:12Z
      DOI: 10.1177/03611981211008189
       
  • Effectiveness of Green Warning Lights with Different Flashing Patterns for
           Winter Maintenance Operations
    • Authors: Fatemeh Fakhrmoosavi, Ramin Saedi, Farish Jazlan, Ali Zockaie, Mehrnaz Ghamami, Timothy J. Gates, Peter T. Savolainen
      Abstract: Transportation Research Record, Ahead of Print.
      Snow removal activities are performed by roadway agencies to enhance winter mobility and safety. Slower travel speeds during these operations, combined with low visibility and reduced pavement friction, mean that safety and collision avoidance remain a persistent concern. Many studies have implemented signing and lighting technologies to improve the visibility of snowplows. Although a few studies have evaluated the use of different colors on snowplows, there is no rigorous study that evaluates the potential impacts of using green warning lights for winter maintenance operations. This study, therefore, investigates the impacts of various warning light configurations on the visibility of snowplows, with the focus on green lights. To this end, 37 warning light configurations are designed using various color combinations (green and amber), and flashing patterns (single and quad) on the back (LED), the top (beacon), or both, of snowplows. These configurations are evaluated to identify the most effective configurations. Three sets of experiments are designed and implemented: static, dynamic, and weather to evaluate the visibility effectiveness in different contexts: day versus night, clear versus snowy weather, and static versus dynamic scenarios. Human subjects are employed to conduct the experiments and the test results are evaluated using statistical analyses. The conspicuity during the day time and glare during the night time are statistically different among various configurations. In addition, adding green lights with a single flash pattern to amber warning lights improves the conspicuity, while keeping the glare at an acceptable level relative to configurations using only amber.
      Citation: Transportation Research Record
      PubDate: 2021-04-27T07:52:10Z
      DOI: 10.1177/03611981211008187
       
  • Stabilization of the Highway Slope using Recycled Plastic Pins
    • Authors: Mohammad Sadik Khan, MD Sahadat Hossain, Masoud Nobahar
      Abstract: Transportation Research Record, Ahead of Print.
      The recycled plastic pin (RPP) is made from recycled plastics and waste materials (i.e., polymer, sawdust, fly ash, etc.). It is a lightweight material and is less susceptible to chemical and biological degradation than the alternative reinforcing element. RPPs are driven into the slope face and provide additional resistance along the slip surface which increases the factor of safety against shallow slope failure. The current paper summarizes a case study using RPPs to repair highway slopes, investigating the use of a finite element method, and summarizes a design method. The highway slope was located over US 287 near the St. Paul overpass in Midlothian, Texas. The surficial movement had taken place over the slope, resulting in cracks over the shoulder near the bridge abutment. Three 15.2-m sections over the slope were reinforced using RPPs. After RPP installation, the slope was instrumented with inclinometers, rain gauges, moisture sensors, and water potential probes, and was monitored periodically. The performance monitoring results indicated that RPP provides resistance in the slope constructed using highly plastic clay. Further analysis of the slope using finite element analysis indicates that RPP can significantly improve the marginal slopes to a factor of safety more than 2.0. Finally, a simple design chart is presented to calculate the capacity of RPPs for slope repair design using an infinite slope approach.
      Citation: Transportation Research Record
      PubDate: 2021-04-27T07:50:54Z
      DOI: 10.1177/03611981211007143
       
  • Drivers and Barriers of Households’ Carsharing Decisions
    • Authors: Raïsa Carmen, Luc Alaerts, Kris Bachus, Donald A. Chapman, Johan Eyckmans, Karel Van Acker, Luc Van Ootegem, Sandra Rousseau
      Abstract: Transportation Research Record, Ahead of Print.
      Based on a survey of 2,106 individuals, this study aims to get a better understanding of the attitudes toward carsharing in Flanders, Belgium. Several drivers and barriers that influence household decisions to participate in a carsharing system are identified. An ordinal logit model reveals that highly educated, younger males with high ecological concerns are more likely to share cars. It is shown that living in a rural environment or owning a company car are important barriers. A parking policy aimed at discouraging private car use while stimulating sustainable mobility choices appears to be an interesting avenue for future research.
      Citation: Transportation Research Record
      PubDate: 2021-04-27T07:50:33Z
      DOI: 10.1177/03611981211006726
       
  • Assessing the Bus Bridging Effectiveness on the Operational Resilience of
           the Subway Service in Toronto
    • Authors: Alaa Itani, Amer Shalaby
      Abstract: Transportation Research Record, Ahead of Print.
      Unplanned rail disruptions result in substantial delays to passengers and severe effects on the economy of a large city like Toronto. While bus bridging has been a widely adopted method to replace the subway service in such events, its effect on the operational resilience of the subway service is less often studied. This study assesses the resilience of the subway network of Toronto employing an optimal bus bridging strategy. First, subway incidents are categorized based on their characteristics using K-mean clustering analysis. The incidents are then grouped based on the performance of optimal bus bridging plans. Classification and regression tree analysis is used for this task, employing two metrics: the total user delay and total number of shuttle buses under the optimal bridging scenario. Queueing and optimization models developed previously by the University of Toronto are used to determine and simulate the optimal bus bridging plans of a sample of incidents. The severity of unplanned disruptions is finally demonstrated using a severity scale and the effect of incident duration uncertainty is analyzed. The results show that along the congested city alignments, where the capacity of the roads and stations is limited, the bus bridging service is often insufficient to replace the train service. However, it could be a good alternative in uncongested subway segments where the available street capacity is relatively high, allowing large bus volumes to serve the corridor. This model is easily applicable to different rail systems and it could assess other systems to produce better bridging plans.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T11:08:07Z
      DOI: 10.1177/03611981211007836
       
  • Simple Index to Assess the Calibration Quality of Safety Performance
           Functions Based on Multiple Goodness-of-Fit Metrics
    • Authors: Raul E. Avelar, Karen Dixon, Boniphace Kutela, Sam Klump, Beth Wemple, Richard Storm, Mary Morgan
      Abstract: Transportation Research Record, Ahead of Print.
      The calibration of safety performance functions (SPFs) is a mechanism included in the Highway Safety Manual (HSM) to adjust SPFs in the HSM for use in intended jurisdictions. Critically, the quality of the calibration procedure must be assessed before using the calibrated SPFs. Multiple resources to aid practitioners in calibrating SPFs have been developed in the years following the publication of the HSM 1st edition. Similarly, the literature suggests multiple ways to assess the goodness-of-fit (GOF) of a calibrated SPF to a data set from a given jurisdiction. This paper uses the calibration results of multiple intersection SPFs to a large Mississippi safety database to examine the relations between multiple GOF metrics. The goal is to develop a sensible single index that leverages the joint information from multiple GOF metrics to assess overall quality of calibration. A factor analysis applied to the calibration results revealed three underlying factors explaining 76% of the variability in the data. From these results, the authors developed an index and performed a sensitivity analysis. The key metrics were found to be, in descending order: the deviation of the cumulative residual (CURE) plot from the 95% confidence area, the mean absolute deviation, the modified R-squared, and the value of the calibration factor. This paper also presents comparisons between the index and alternative scoring strategies, as well as an effort to verify the results using synthetic data. The developed index is recommended to comprehensively assess the quality of the calibrated intersection SPFs.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T11:06:24Z
      DOI: 10.1177/03611981211008896
       
  • Full Scale Evaluation of Surface Treatments for Airfield Concrete Pavement
           Repair
    • Authors: Jesse D. Doyle, Jennifer A. Jefcoat, Margarita Ordaz, Craig A. Rutland
      Abstract: Transportation Research Record, Ahead of Print.
      Surface deterioration of concrete pavements requires maintenance. Highway and airfield pavements exhibit many of the same maintenance issues, but airfields have several additional unique issues and requirements. Among these are petroleum contamination on aircraft parking areas and a high potential for failed concrete or maintenance materials to damage aircraft. To address these issues, commercially available surface-applied treatment products were assessed for use on concrete pavements with particular focus on the special requirements of airfields. Fourteen products encompassing numerous chemistries were evaluated in a full-scale field experiment. The specific objectives of this study were to investigate materials for field application issues, adhesion to concrete (for both clean and oil contaminated concrete), the ability to seal cracks, behavior under aircraft traffic loads including surface friction, and durability over time with exposure to environmental conditions. Test strips of each material were applied to deteriorated concrete slabs. Half of the concrete was intentionally contaminated with oil while the other half was left clean. Simulated aircraft traffic was applied and periodic visual observations and surface friction measurements were made. Two years after material application, a final visual assessment was made. Many of the products performed well on clean concrete; however, oil contaminated concrete detrimentally affected many of them. Of the fourteen products evaluated, two of the epoxy based materials clearly emerged as the best performing.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T11:04:24Z
      DOI: 10.1177/03611981211008882
       
  • Regional Perspective of Safety Performance Functions and Their Application
           to Florida Intersections in Suburban Residential and Urban General Context
           Classification Categories
    • Authors: Ghalia Gamaleldin, Haitham Al-Deek, Adrian Sandt, John McCombs, Alan El-Urfali
      Abstract: Transportation Research Record, Ahead of Print.
      Safety performance functions (SPFs) are essential tools to help agencies predict crashes and understand influential factors. Florida Department of Transportation (FDOT) has implemented a context classification system which classifies intersections into eight context categories rather than the three classifications used in the Highway Safety Manual (HSM). Using this system, regional SPFs could be developed for 32 intersection types (unsignalized and signalized 3-leg and 4-leg for each category) rather than the 10 HSM intersection types. In this paper, eight individual intersection group SPFs were developed for the C3R-Suburban Residential and C4-Urban General categories and compared with full SPFs for these categories. These comparisons illustrate the unique and regional insights that agencies can gain by developing these individual SPFs. Poisson, negative binomial, zero-inflated, and boosted regression tree models were developed for each studied group as appropriate, with the best model selected for each group based on model interpretability and five performance measures. Additionally, a linear regression model was built to predict minor roadway traffic volumes for intersections which were missing these volumes. The full C3R and C4 SPFs contained four and six significant variables, respectively, while the individual intersection group SPFs in these categories contained six and nine variables. Factors such as major median, intersection angle, and FDOT District 7 regional variable were absent from the full SPFs. By developing individual intersection group SPFs with regional factors, agencies can better understand the factors and regional differences which affect crashes in their jurisdictions and identify effective treatments.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T11:00:24Z
      DOI: 10.1177/03611981211008447
       
  • Field Validation of Effective Dispersion Analysis of Reflections, a New
           Method for Nondestructive Estimation of Pile Depth
    • Authors: Vivek Samu, Murthy Guddati
      Abstract: Transportation Research Record, Ahead of Print.
      Several methods have been developed for nondestructive pile depth estimation over the past few decades, with impact-based methods remaining popular because of their ease of application. Sonic-echo techniques rely on generating nondispersive longitudinal waves by impacting the pile top and subsequently picking peaks that correspond to initial and reflected wave arrivals. Unfortunately, pile tops are often inaccessible for in-service foundations and alternate impacting techniques result in signals for which time domain peak picking can be difficult. Pile sides are often easily accessible, but side impact generates highly dispersive flexural waves resulting in complicated waveforms for which analysis is not straightforward. Existing methods to process dispersive flexural waves rely on signal processing based methods and do not explicitly incorporate the physical dispersion properties of the system, resulting in large errors. To address the current limitations, a new method called effective dispersion analysis of reflections (EDAR) was recently developed for pile length estimation. EDAR provides a simple and robust technique to analyze dispersive flexural waves generated from side impact for which time domain processing is not applicable. In this paper, length estimation through EDAR is explained for longitudinal and flexural waves using synthetic bar and Timoshenko beam models. Field validation for two types of pile, concrete filled steel tubes and prestressed concrete, with varying cross sections and embedment are presented. EDAR resulted in pile length estimates within 10% error.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T10:55:44Z
      DOI: 10.1177/03611981211008186
       
  • Strategic Evacuation for Hurricanes and Regional Events with and without
           Autonomous Vehicles
    • Authors: Jooyong Lee, Kara M. Kockelman
      Abstract: Transportation Research Record, Ahead of Print.
      A scheduling algorithm is developed for optimal planning of large-scale, complex evacuations to minimize total delay plus travel time across residents. The algorithm is applied to the eight-county Houston-Galveston region and land use setting under the 2017 Hurricane Harvey scenario with multiple destinations. Autonomous vehicle (AV) use under central guidance is also tested, to demonstrate the evacuation time benefits of AVs. Higher share of AVs delivers more efficient evacuation performance, thanks to greater reliability on evacuation order compliance, lower headways, and higher road capacity. Furthermore, 100% AV use delivers lower overall evacuation costs and network clearance times and less uncertainty in travel times (via lower standard deviation in). Based on evaluations of different evacuation schedules, a 50% compressed evacuation time span resulted in longer travel times and network congestion. A 50% longer evacuation time span reduced residents' total travel time and network congestion, but increased the evacuation cost. As expected, evacuation efficiency falls when evacuees do not comply with evaucation schedules. Large shares of AVs will not be possible in the near future, so methods to enhance evacuees' compliance behavior (e.g., enforced and prioritized evacuation orders) should be considered until a meaningful level of AV technical maturity and penetration rate is available. This paper demonstrates the benefits of scheduled departure times, AV use, and evacuation order compliance, which help balance conflicting objectives during emergencies.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T10:47:07Z
      DOI: 10.1177/03611981211007482
       
  • Comparing Commercial Vehicle Fuel Consumption Models using Real-World Data
           under Calibration Constraints
    • Authors: Lih Wei Yeow, Lynette Cheah
      Abstract: Transportation Research Record, Ahead of Print.
      Assessing commercial road vehicle fuel use at a high spatiotemporal resolution helps in understanding underlying usage patterns and informs future interventions toward fuel-efficient freight planning and operations. With the use of global navigation satellite systems in fleet tracking and advancements in driver activity surveys, instantaneous fuel consumption models can calculate fuel use in high resolution using inputs like speed and acceleration derived from GPS data. Given that several models exist, there is a need to compare fuel use estimates from different models, especially under the constraint of limited data for calibration. This study evaluates the accuracy of fuel use estimates from three fuel consumption models (COPERT 4, SIDRA TRIP, and MOVES) applied to 10 diesel commercial road vehicles in Singapore over a standardized drive cycle (NEDC) and real-world activity data derived from GPS traces using the method of space-time path segments and road grade obtained from a digital elevation model. Changes in model performance are examined when supplementary on-board diagnostics (OBD) data and payload information are used. The models gave varying fuel use estimates over the NEDC, especially for heavier vehicles in the sample. When applied to real-world data, SIDRA TRIP was found to be the most accurate for the context studied. SIDRA TRIP’s performance improved consistently when supplemented with OBD and payload information. This comparison approach allows analysts to select the most suitable model for a given context, and take steps toward more sustainable freight transportation.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T10:45:00Z
      DOI: 10.1177/03611981211007478
       
  • Environmental and Economic Effects of Fuel Savings in Driving Phase
           Resulting from Substitution of Light Metals in European Passenger Car
           Production
    • Authors: Yiğit Türe, Cengiz Türe
      Abstract: Transportation Research Record, Ahead of Print.
      The European Union (EU), which realizes one-quarter of the automobile production in the world, has made legal regulations to minimize fuel consumption and CO2 emissions in the automotive sector, to prevent global warming and climate change. Life cycle analysis for passenger cars revealed that 90% of this effect is caused by the driving phase of the vehicles. One of the practices used in the automotive industry to minimize the impact of these factors is to reduce the vehicle mass as much as possible. Aluminum (Al) and magnesium (Mg) are increasingly preferred lightweight materials, since the weight is a critical design element for automobile production. This study aims to evaluate the environmental and economic impacts of fuel consumption, fuel expense, and CO2 emission resulting from the driving cycle by creating a mathematical model of the weight savings achieved with Al and Mg substitution in the passenger car fleet produced in the EU. The results show that the average weight reduction per vehicle achieved by substituting light metals in passenger car production in the EU over the past 20 years has reached approximately 11.2% and that the positive effect on fuel consumption and CO2 emissions in the driving cycle will contribute to environmentally and economically sustainable road transport.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T10:41:59Z
      DOI: 10.1177/03611981211006418
       
  • Bayesian Approach to Developing Context-Based Crash Modification Factors
           for Medians on Rural Four-Lane Roadways
    • Authors: Xiaobing Li, Jun Liu, Chenxuan Yang, Timothy Barnett
      Abstract: Transportation Research Record, Ahead of Print.
      Rural four-lane roadways provide important transportation accessibility and mobility to populations in rural areas. It is a challenge for practitioners to determine cross-section types when both benefits and costs need to be considered. Crash Modification Factors (CMFs) are developed to evaluate the safety effectiveness of alternative designs. However, safety effectiveness could vary significantly across contexts. Thus, this study aims to estimate CMFs for alternative cross sections of rural four-lane roadways under different contexts characterized by traffic volume, truck percentage, and access point density. Using Georgia state-wide crash data, this study developed Safety Performance Functions (SPFs) to predict crash frequencies for different contexts. Considering linearity and independence assumptions of traditional negative binomial SPFs, this study adopts Bayesian generalized negative binomial modeling approaches to relax those assumptions and only follows the Bayes rule to form SPFs for CMF estimation. This study focuses on four typical cross-sections including: (1) non-traversable medians; (2) two-way-left-turn lanes; (3) 4-ft flush medians; and (4) undivided roadways with double-yellow lines (the base cross-section design). The results show that CMFs vary significantly across different contexts. Compared with the base cross-section design, safety benefits of the other three designs can be either positive or negative under different traffic or road conditions. For example, 4-ft flush medians are found to have positive safety benefits (CMF  1) under greater average daily traffic volumes (e.g., ≥ 15,000). The findings suggest that, to enhance roadway safety, practitioners should vary cross-section designs for different rural contexts.
      Citation: Transportation Research Record
      PubDate: 2021-04-26T10:38:18Z
      DOI: 10.1177/03611981211007141
       
  • Are Roundabouts Safe and Economically Viable Replacing Conventional
           Diamond Interchange Ramp Terminals'
    • Authors: Boris Claros, Beau Burdett, Madhav Chitturi, Andrea Bill, David A. Noyce
      Abstract: Transportation Research Record, Ahead of Print.
      Roundabout implementations at traditional intersections have been shown to be effective at reducing severe crashes. Roundabouts have also been implemented at interchange ramp terminals; however, limited research is available. In this study, 25 roundabout ramp terminal implementations were evaluated. The methodological approach consisted of Empirical Bayes for safety effectiveness and crash cost changes, crash type weighted distribution, crash rate analysis of bypass configuration, and cost of implementation. Roundabouts were effective at reducing fatal and injury crashes when replacing existing interchange diamond ramp terminals: 65% reduction for roundabouts replacing stop-controlled ramp terminals and 41% reduction for roundabouts replacing signal-controlled ramp terminals. Observed crash type weighted distributions are provided to visualize the frequency and location of crashes within roundabout ramp terminals for design considerations. Exit ramp and outside crossroad approaches with right-turn bypass showed significantly lower crash rates than designs without bypass. The crash cost analysis showed that roundabouts replacing diamond ramp terminals yielded crash cost savings of between $95,000 and $253,000 per site per year (69% to 54% decrease in crash costs). Considering crash costs savings only, the cost of implementation should be less than $1.9 million for a roundabout replacing a stop-controlled ramp terminal and less than $5.1 million for a roundabout replacing a signal-controlled ramp terminal to accomplish benefit-cost ratios greater than one for a service life cycle of 20 years. Costs are in 2019 dollars.
      Citation: Transportation Research Record
      PubDate: 2021-04-24T11:12:40Z
      DOI: 10.1177/03611981211008883
       
  • Understanding Gap Acceptance Behavior at Unsignalized Intersections using
           Naturalistic Driving Study Data
    • Authors: Yingfeng (Eric) Li, Haiyan Hao, Ronald B. Gibbons, Alejandra Medina
      Abstract: Transportation Research Record, Ahead of Print.
      Even though drivers disregarding a stop sign is widely considered a major contributing factor for crashes at unsignalized intersections, an equally important problem that leads to severe crashes at such locations is misjudgment of gaps. This paper presents the results of an effort to fully understand gap acceptance behavior at unsignalized intersections using SHPR2 Naturalistic Driving Study data. The paper focuses on the findings of two research activities: the identification of critical gaps for common traffic/roadway scenarios at unsignalized intersections, and the investigation of significant factors affecting driver gap acceptance behaviors at such intersections. The study used multiple statistical and machine learning methods, allowing a comprehensive understanding of gap acceptance behavior while demonstrating the advantages of each method. Overall, the study showed an average critical gap of 5.25 s for right-turn and 6.19 s for left-turn movements. Although a variety of factors affected gap acceptance behaviors, gap size, wait time, major-road traffic volume, and how frequently the driver drives annually were examples of the most significant.
      Citation: Transportation Research Record
      PubDate: 2021-04-24T11:11:17Z
      DOI: 10.1177/03611981211007140
       
  • Review of Post-Fire Inspection Procedures for Concrete Tunnels
    • Authors: Nick Menz, Simos Gerasimidis, Scott Civjan, John Czach, Joe Rigney
      Abstract: Transportation Research Record, Ahead of Print.
      It is well known that concrete structures can lose strength and long-term durability after a fire. The literature on the remaining capacity of tunnel structures after fire is quite scattered, however, and few published post-fire inspection guides exist. This paper reviews the available literature on the post-fire inspection and evaluation of concrete tunnels. The effects of fire on concrete and steel are discussed, including loss of strength, thermal spalling of concrete, and loss of strength in the bond between concrete and steel. In addition, studies on the residual strength of concrete members are presented. Available post-fire inspection strategies and methods are also discussed. Finally, the results of a survey of post-fire tunnel inspection practices at state Departments of Transportation and transit organizations across the United States are presented. Several models available in both structural building codes and experimental studies allow for the estimation of residual concrete compressive and steel tensile strength after heating and cooling from a given temperature. Furthermore, a variety of post-fire assessment methods are available, which include methods to assess the general post-fire condition of concrete tunnels, as well as methods to more directly assess the residual condition of concrete. Lastly, the review of literature and the survey of United States transit organizations revealed a lack of existing post-fire inspection procedures for concrete tunnels, and a need for further research on the subject.
      Citation: Transportation Research Record
      PubDate: 2021-04-24T11:08:59Z
      DOI: 10.1177/03611981211006732
       
  • Adaptive Sampling Simulated Annealing for the Synthesis of Disaggregate
           Mobility Data from Origin–Destination Matrices
    • Authors: Haris Ballis, Loukas Dimitriou
      Abstract: Transportation Research Record, Ahead of Print.
      Agent-based modelling has been suggested as a highly suitable approach for the tackling of future mobility challenges. However, the application of disaggregate models is often hindered by the high granularity of the required input. Recent research has suggested a combinatorial optimization-based framework to enable the conversion of typical origin–destination matrices (ODs) to suitable input for agent-based modelling (e.g., trip-chains, tours, or activity-schedules). Nonetheless, the combinatorial nature of the approach requires very efficient and scalable optimization processes to handle large-scale ODs. This study suggests an advanced optimization technique, coined as the adaptive sampling simulated annealing (ASSA) algorithm, able to exploit high-level calibration information (in the form of a joint distribution) for the efficient addressing of large-scale combinatorial problems. The proposed optimization algorithm was evaluated using high-level information about the departure profile, the types of activities, and the travel time of the expected output and a set of large-scale trip-purpose- and time-period-segmented OD matrices of 253,000 trips. The obtained results showcase the ability of the methodology to accurately and efficiently convert large-scale ODs into disaggregate mobility traces since the inputted ODs were converted into thousands of travel-demand equivalent, disaggregate mobility traces with an accuracy exceeding 90%. The implications are significant since the abundance of travel-demand information in ODs can be now exploited for the preparation of disaggregate mobility traces, suitable for sophisticated agent-based transport modelling.
      Citation: Transportation Research Record
      PubDate: 2021-04-23T11:35:51Z
      DOI: 10.1177/03611981211008891
       
  • Effects of Auditory Display Types and Acoustic Variables on Subjective
           Driver Assessment in a Rail Crossing Context
    • Authors: Chihab Nadri, Seul Chan Lee, Siddhant Kekal, Yinjia Li, Xuan Li, Pasi Lautala, David Nelson, Myounghoon Jeon
      Abstract: Transportation Research Record, Ahead of Print.
      Highway-rail grade crossings (HRGCs) present multiple collision risks for motorists, suggesting the need for additional countermeasures to increase driver compliance. The use of in-vehicle auditory alerts (IVAAs) at HRGCs has been increasing, but there are limited standards or guidelines on how such alerts should be implemented. In the current study, we sought to investigate the effect of different auditory display variables, such as display type and acoustics, on subjective user assessments. We recruited 24 participants and asked them to rate 36 different IVAAs belonging to one of three display types (earcons—short synthetic tones, speech alerts, and hybrid alerts consisting of an earcon and speech) along 11 subjective ratings. Results showed that a hybrid alert led to better overall ratings for acceptance, safety, and semantic understanding when compared with earcon or speech alerts. Additional analyses revealed that semantic variables, such as speech order and gender, should be accounted for when designing IVAAs in an HRGC context. Hybrid IVAAs with spatial audio showed lower Urgency and Hazard level ratings. Findings of the current study can help inform the design of IVAAs for HRGCs.
      Citation: Transportation Research Record
      PubDate: 2021-04-23T11:34:02Z
      DOI: 10.1177/03611981211007838
       
  • (Overlooked) Association between Express Bus Station/Stop Proximity and
           Multifamily Rents with a Surprise about Transit Mode Synergism and
           Implications for Transit and Land Use Planning
    • Authors: Arthur C. Nelson, Robert Hibberd
      Abstract: Transportation Research Record, Ahead of Print.
      Despite hundreds of studies into the association between real estate value and proximity to fixed-route transit (FRT) systems, none has assessed the association with respect to express bus transit (XBT) stations/stops. Ours is the first to do so. Using a static, cross-section quasi-experimental research design, we evaluate CoStar multifamily (MF) rent per square foot to estimate the difference in rent with respect to proximity to XBT stations/stops. However, we are also interested in knowing whether there are synergistic price effects at the intersection of XBT and other FRT systems such as light rail transit (LRT). In this article, we estimate the MF rent premium with respect to XBT and LRT (XBT+LRT) station/stop proximity separately, rent premiums for combined XBT and LRT stations/stops and for those MF cases that are more than 1.0 mi beyond the nearest LRT station. In all cases, whether separately or combined with LRT stations or away from LRT stations, we find positive associations between MF rent and proximity to XBT stations/stops. However, we also find evidence of negative externalities at or near XBT, LRT, and XBT+LRT stations/stops. Express bus transit and land-use planning implications are offered.
      Citation: Transportation Research Record
      PubDate: 2021-04-22T11:53:19Z
      DOI: 10.1177/03611981211005457
       
  • Toward Just-in-Time Data Communications over Shared Networks and
           Computational Resources on Massive Client Environment
    • Authors: Hirochika Asai, Yusuke Doi, Ryokichi Onishi
      Abstract: Transportation Research Record, Ahead of Print.
      Intelligent driving has been benefiting from advances in automotive big data analysis and on-demand data communications, where efficient vehicle-to-cloud communication is a key technology able to collect a huge amount of data from vehicles. However, as the capacities of the network and computational resources of the cloud are not unlimited, simultaneous data transfer based on a best-effort manner results in a resource starvation problem. Therefore, an application is needed to prioritize data communication to alleviate the problem and complete the data transfer just in time. This paper highlights the problem of resource starvation led by best-effort data transfers. It proposes protocols for data communication and control that could enable just-in-time data communication, notably for data collection. We demonstrate through experiments that the proposed mechanism enables efficient and effective data collection over the shared network resources.
      Citation: Transportation Research Record
      PubDate: 2021-04-22T07:16:29Z
      DOI: 10.1177/03611981211006731
       
  • Deep Learning to Detect Road Distress from Unmanned Aerial System Imagery
    • Authors: Long Ngo Hoang Truong, Omar E. Mora, Wen Cheng, Hairui Tang, Mankirat Singh
      Abstract: Transportation Research Record, Ahead of Print.
      Surface distress is an indication of poor or unfavorable pavement performance or signs of impending failure that can be classified into a fracture, distortion, or disintegration. To mitigate the risk of failing roadways, effective methods to detect road distress are needed. Recent studies associated with the detection of road distress using object detection algorithms are encouraging. Although current methodologies are favorable, some of them seem to be inefficient, time-consuming, and costly. For these reasons, the present study presents a methodology based on the mask regions with convolutional neural network model, which is coupled with the new object detection framework Detectron2 to train the model that utilizes roadway imagery acquired from an unmanned aerial system (UAS). For a comprehensive understanding of the performance of the proposed model, different settings are tested in the study. First, the deep learning models are trained based on both high- and low-resolution datasets. Second, three different backbone models are explored. Finally, a set of threshold values are tested. The corresponding experimental results suggest that the proposed methodology and UAS imagery can be used as efficient tools to detect road distress with an average precision score up to 95%.
      Citation: Transportation Research Record
      PubDate: 2021-04-22T07:13:30Z
      DOI: 10.1177/03611981211004973
       
  • Measuring Congestion and Reliability Impacts of Safety Projects
    • Authors: Simona Babiceanu, Sanhita Lahiri, Mena Lockwood
      Abstract: Transportation Research Record, Ahead of Print.
      This study uses a suite of performance measures that was developed by taking into consideration various aspects of congestion and reliability, to assess impacts of safety projects on congestion. Safety projects are necessary to help move Virginia’s roadways toward safer operation, but can contribute to congestion and unreliability during execution, and can affect operations after execution. However, safety projects are assessed primarily for safety improvements, not for congestion. This study identifies an appropriate suite of measures, and quantifies and compares the congestion and reliability impacts of safety projects on roadways for the periods before, during, and after project execution. The paper presents the performance measures, examines their sensitivity based on operating conditions, defines thresholds for congestion and reliability, and demonstrates the measures using a set of Virginia safety projects. The data set consists of 10 projects totalling 92 mi and more than 1M data points. The study found that, overall, safety projects tended to have a positive impact on congestion and reliability after completion, and the congestion variability measures were sensitive to the threshold of reliability. The study concludes with practical recommendations for primary measures that may be used to measure overall impacts of safety projects: percent vehicle miles traveled (VMT) reliable with a customized threshold for Virginia; percent VMT delayed; and time to travel 10 mi. However, caution should be used when applying the results directly to other situations, because of the limited number of projects used in the study.
      Citation: Transportation Research Record
      PubDate: 2021-04-21T11:25:49Z
      DOI: 10.1177/03611981211006729
       
  • Impacts of School Reopening on Variations in Local Bus Performance in
           Sydney
    • Authors: Wenbo Yan, Hudson Yao, Linji Chen, Hema Rayaprolu, Emily Moylan
      Abstract: Transportation Research Record, Ahead of Print.
      During the COVID-19 pandemic, stay-at-home orders in conjunction with working from home, school closures, and event cancellations resulted in a decrease in travel demand. Under normal circumstances, these activities are components of trip chains and utilize a multimodal transport network. The overall performance of the network can be traced through delays in the bus system as buses capture both changes in ridership and fluctuations in mixed traffic conditions. This paper explores the hypothesis that resumption of a single component in trip chains (i.e., school reopening) is sufficient for a measurable change in transport system performance. This study used school reopening in Sydney, Australia as a case study to explore whether school-related trips affected bus system performance directly with higher student patronage or indirectly with heavier road congestion from parental car trips. Both stop dwell times and differences in delays between successive stops were used as bus service indicators. Dwell times reflect the travel demand for buses and delay differences capture local changes in service reliability. We found that increase in ridership had limited impacts on bus punctuality. However, the level of local bus performance worsened after schools reopened, and the effect was more pronounced in commercial areas in the afternoon when schools ended, suggesting secondary trip purposes such as leisure and shopping in addition to school pick-ups. This study revealed the interaction between different trip purposes during the postshutdown period and threw light on changes in travel behavior patterns as travel restrictions were relaxed in pandemic circumstances.
      Citation: Transportation Research Record
      PubDate: 2021-04-21T11:23:47Z
      DOI: 10.1177/03611981211006723
       
  • Modeling Capacity of Through Movement at Signalized Intersection Affected
           by Short Left-Turn Bay under Different Signal Settings
    • Authors: Zihang Wei, Yunlong Zhang, Xiaoyu Guo, Xin Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.
      Citation: Transportation Research Record
      PubDate: 2021-04-21T11:22:25Z
      DOI: 10.1177/03611981211006433
       
  • Local Calibration of Pavement Mechanistic-Empirical Faulting Reliability
           using Pavement Management Data
    • Authors: Lucio Salles de Salles, Lev Khazanovich
      Abstract: Transportation Research Record, Ahead of Print.
      The Pavement ME transverse joint faulting model incorporates mechanistic theories that predict development of joint faulting in jointed plain concrete pavements (JPCP). The model is calibrated using the Long-Term Pavement Performance database. However, the Mechanistic-Empirical Pavement Design Guide (MEPDG) encourages transportation agencies, such as state departments of transportation, to perform local calibrations of the faulting model included in Pavement ME. Model calibration is a complicated and effort-intensive process that requires high-quality pavement design and performance data. Pavement management data—which is collected regularly and in large amounts—may present higher variability than is desired for faulting performance model calibration. The MEPDG performance prediction models predict pavement distresses with 50% reliability. JPCP are usually designed for high levels of faulting reliability to reduce likelihood of excessive faulting. For design, improving the faulting reliability model is as important as improving the faulting prediction model. This paper proposes a calibration of the Pavement ME reliability model using pavement management system (PMS) data. It illustrates the proposed approach using PMS data from Pennsylvania Department of Transportation. Results show an increase in accuracy for faulting predictions using the new reliability model with various design characteristics. Moreover, the new reliability model allows design of JPCP considering higher levels of traffic because of the less conservative predictions.
      Citation: Transportation Research Record
      PubDate: 2021-04-21T11:20:26Z
      DOI: 10.1177/03611981211001392
       
  • Car Following and Microscopic Traffic Simulation Under Distracted Driving
    • Authors: Sunbola Zatmeh-Kanj, Tomer Toledo
      Abstract: Transportation Research Record, Ahead of Print.
      Microscopic simulation models have been widely used as tools to investigate the operation of traffic systems and different intelligent transportation systems applications. The fidelity of microscopic simulation tools depends on the driving behavior models that they implement. However, current models commonly do not consider human-related factors, such as distraction. The potential for distraction while driving has increased rapidly with the availability of smartphones and other connected and infotainment devices. Thus, an understanding of the impact of distraction on driving behavior is essential to improve the realism of microscopic traffic tools and support safety and other applications that are sensitive to it. This study focuses on car-following behavior in the context of distracting activities. The parameters of the well-known GM and intelligent driver models are estimated under various distraction scenarios using data collected with an experiment conducted in a driving simulator. The estimation results show that drivers are less sensitive to their leaders while talking on the phone and especially while texting. The estimated models are implemented in a microscopic traffic simulation model. The average speed, coefficient of variation of speed, acceleration noise and acceleration and deceleration time fractions were used as measures of performance indicating traffic flow and safety implications. The simulation results show deterioration of traffic flow with texting and to some extent talking on the phone: average speeds are lower and the coefficient of variation of speeds are higher. Further experimentation with varying fractions of texting drivers showed similar trends.
      Citation: Transportation Research Record
      PubDate: 2021-04-20T05:45:18Z
      DOI: 10.1177/03611981211000357
       
  • Using Probabilistic Fault Tree Analysis and Monte Carlo Simulation to
           Examine the Likelihood of Risks Associated with Ballasted Railway Drainage
           Failure
    • Authors: Kristianto Usman, Michael Peter Nicholas Burrow, Gurmel Singh Ghataora, Manu Sasidharan
      Abstract: Transportation Research Record, Ahead of Print.
      Inadequate track drainage can lead to a variety of issues, including flooding, accelerated track degradation, and progressive or sudden failure of railway track, slope, or embankment. These can result in unplanned track maintenance, additional passenger travel costs, and damage to third party property. However, railway drainage asset management is challenging because it involves the consideration of large interconnected assets, limited maintenance budgets, and unknown failure probabilities. To address this issue, this paper introduces a risk-informed approach for railway drainage asset management that uses fault tree analysis to identify the factors that contribute to railway drainage flood risk and quantifies the likelihood of the occurrence of these factors using Monte Carlo simulation. This rational approach enables drainage asset managers to evaluate easily the factors that affect the likelihood of railway track drainage failure, thereby facilitating the prioritization of appropriate mitigation measures and in so doing improve the allocation of scarce maintenance resources. The analysis identified 46 basic and 49 intermediate contributing factors associated with drainage failure of ballasted railway track (undesired event). The usefulness of the approach is demonstrated for three sites on the UK railway network, namely, Ardsley Tunnel, Clay Cross Tunnel, and Draycott. The analysis shows that the Clay Cross Tunnel had the highest probability of drainage failure and should be prioritized for maintenance over the other two sites. The maintenance required should focus on blockages because of vegetation overgrowth or debris accumulation.
      Citation: Transportation Research Record
      PubDate: 2021-04-20T05:41:38Z
      DOI: 10.1177/0361198120982310
       
  • Convolutional Neural Network-Based In-Vehicle Occupant Detection and
           Classification Method using Second Strategic Highway Research Program
           Cabin Images
    • Authors: Ioannis Papakis, Abhijit Sarkar, Andrei Svetovidov, Jeffrey S. Hickman, A. Lynn Abbott
      Abstract: Transportation Research Record, Ahead of Print.
      This paper describes an approach for automatic detection and localization of drivers and passengers in automobiles using in-cabin images. We used a convolutional neural network (CNN) framework and conducted experiments based on the Faster R-CNN and Cascade R-CNN detectors. Training and evaluation were performed using the Second Strategic Highway Research Program (SHRP 2) naturalistic dataset. In SHRP 2, the cabin images have been blurred to maintain privacy. After detecting occupants inside the vehicle, the system classifies each occupant as driver, front-seat passenger, or back-seat passenger. For one SHRP 2 test set, the system detected occupants with an accuracy of 94.5%. Those occupants were correctly classified as front-seat passenger with an accuracy of 97.3%, as driver with 99.5% accuracy, and as back-seat passenger with 94.3% accuracy. The system performed slightly better for daytime images than for nighttime images. Unlike previous work, this method is capable of presence classification and location prediction of occupants. By fine-tuning the object detection model, there is also significant improvement in detection accuracy as compared with pretrained models. The study also provides a fully annotated dataset of in-cabin images. This work is expected to facilitate research involving interactions between drivers and passengers, particularly related to driver attention and safety.
      Citation: Transportation Research Record
      PubDate: 2021-04-19T11:53:13Z
      DOI: 10.1177/0361198121998698
       
  • Changes in Travel Behavior, Attitudes, and Preferences among E-Scooter
           Riders and Nonriders: First Look at Results from Pre and Post E-Scooter
           System Launch Surveys at Virginia Tech
    • Authors: Ralph Buehler, Andrea Broaddus, Ted Sweeney, Wenwen Zhang, Elizabeth White, Mike Mollenhauer
      Abstract: Transportation Research Record, Ahead of Print.
      Shared micromobility such as electric scooters (e-scooters) has the potential to enhance the sustainability of urban transport by displacing car trips, providing more mobility options, and improving access to public transit. Most published studies on e-scooter ridership focus on cities and only capture data at one point in time. This study reports results from two cross-sectional surveys deployed before (n = 462) and after (n = 428) the launch of a fleet of shared e-scooters on Virginia Tech’s campus in Blacksburg, VA. This allowed for a pre–post comparison of attitudes and preferences of e-scooter riders and nonusers. E-scooter ridership on campus followed patterns identified in other studies, with a greater share of younger riders, in particular undergraduate students. Stated intention to ride before system launch was greater than actual ridership. The drop-off between prelaunch intention to ride and actual riding was strongest for older age groups, women, and university staff. As in city surveys, the main reasons for riding e-scooters on campus were travel speed and fun of riding. About 30% indicated using e-scooters to ride to parking lots or to access public transport service, indicating their potential as a connector to other modes of transport. Perceptions about convenience, cost, safety, parking, rider behavior, and usefulness of the e-scooter systems were more positive among nonriders after system launch, indicating that pilot projects may improve public perceptions of e-scooters. Building more bike lanes or separate spaces for e-scooters could help move e-scooter riders off sidewalks—a desire expressed by both pedestrians and e-scooter users.
      Citation: Transportation Research Record
      PubDate: 2021-04-19T09:23:41Z
      DOI: 10.1177/03611981211002213
       
  • Automated Asphalt Pavement Raveling Detection and Classification using
           Convolutional Neural Network and Macrotexture Analysis
    • Authors: Yung-An Hsieh, Yichang (James) Tsai
      Abstract: Transportation Research Record, Ahead of Print.
      Raveling is one of the most common asphalt pavement distresses. The survey of its condition is required for transportation agencies to ensure roadway safety and appropriately apply preservation and rehabilitation treatments. However, the traditional raveling condition survey, including the determination of the raveling severity, is typically manually conducted by in-field visual inspection methods that are time consuming, labor intensive, and error prone. Although automated raveling detection and severity classification models have been developed, these existing models have shortcomings. Therefore, there is an urgent need to develop a more accurate and reliable model to automatically detect and classify raveling. This study proposes the first convolutional neural network (CNN)-based model for automated raveling detection and classification. Compared with general CNNs, the proposed model combines the data-driven features learned from training data and macrotexture features of 3D pavement surface data to achieve better performance. The proposed model was evaluated and compared with existing machine learning models using real-world 3D pavement surface data collected from the state of Georgia, U.S. By combining data-driven features with macrotexture features, the proposed model achieved the highest accuracy of 90.8% on raveling classification. The proposed model also achieved classification precision and recall higher than 85% for all raveling severity levels, which is more accurate and robust than existing models. It is concluded that, with multi-type features extraction and proper model design, the proposed model can provide more accurate and reliable predictions for raveling detection and classification.
      Citation: Transportation Research Record
      PubDate: 2021-04-17T10:07:07Z
      DOI: 10.1177/03611981211005450
       
  • Designing Crossing Islands for Speed Control and Intersection Safety on
           Two-Lane Collectors and Arterials
    • Authors: Peter G. Furth, Milad Tahmasebi, Sepehr (Steve) Shekari, Jay Jackson, Zhao (Howie) Sha, Yousef Alsharif
      Abstract: Transportation Research Record, Ahead of Print.
      Crossing islands at unsignalized intersections, in addition to their pedestrian crossing safety benefits, can also serve as speed control chicanes by forcing vehicles to make a reverse curve. A method is developed for determining the chicane length (and thus, parking setback) needed for a two-lane road for a given lane width, island width, and target speed, based on models of the relationship between road geometry vehicle path radius, and speed. New data on the speed–radius relationship is presented. The concept of “informal flare” is also introduced; it is a common approach geometry that allows a left-turning vehicle to wait for a gap in opposing traffic without blocking through traffic behind it. Using informal flares can make it possible to prevent left-turn blockage without sacrificing a crossing island for a left-turn lane. Curb continuation lines at median openings are presented as a means to enhance informal flare function. Original data are presented relating informal flare function (the tendency of through vehicles to bypass a waiting left-turner) to a road’s half-width. Geometric analysis shows that intersections with crossing islands can fit on roads with right of way as narrow as 60 ft, and with curb-to-curb width as narrow as 40 ft, while still accommodating turning school buses and bike facilities and preventing left-turn blockage. Various performance measures are used to evaluate intersection geometry, including measures related to through vehicle speed, turning vehicles, and pedestrians. With crossing islands, pedestrian safety with respect to left-turning vehicles is substantially improved as the turning path becomes square to the crosswalks, making the vehicle path more predictable and reducing vehicle speed, conflict area size, and pedestrian exposure distance.
      Citation: Transportation Research Record
      PubDate: 2021-04-17T10:05:02Z
      DOI: 10.1177/03611981211004978
       
  • Comparative Performance of Different Warm Mix Asphalt Technologies under
           the Influence of High Aircraft Tire Pressure and Temperature
    • Authors: Navneet Garg, Hasan Kazmee, Lia Ricalde
      Abstract: Transportation Research Record, Ahead of Print.
      Warm mix asphalt (WMA) technologies allow the production and placement of asphalt concrete materials at a lower temperature than the traditional hot mix asphalt (HMA). These materials simultaneously reduce the production fuel costs, increase the available hauling distance, lengthen the paving season, are eco-friendly, and ensure safer working conditions. Airport authorities can use such materials for construction applications to minimize the downtime and user-delay costs. However, the existing Federal Aviation Administration (FAA) construction specifications do not provide guidance on the implementation of such technologies, especially under the conditions created by aircraft with high tire pressure. To this end, the FAA National Airport Pavement and Materials Research Center (NAPMRC) conducted accelerated pavement tests as part of Test Cycle 1 (TC-1) to study the application potential of WMA (using chemical additive) on airport pavements. TC-1 results showed WMA performance was comparable to P-401 HMA performance in rutting. Test Cycle 2 (TC-2) study investigated the rutting performance of chemical, organic, and hybrid additive-based warm mixes alongside an FAA specification P-401 HMA counterpart. Four different test lanes were constructed accordingly in the outdoor area of NAPMRC, each encompassing three different test sections. Using the sixth-generation airport heavy vehicle simulator (HVS-A), sections on the north side of the test lanes were trafficked with 61.3 kips (272.7 kN) moving wheel load at a controlled temperature of 120°F (48.9°C). The chemical additive-based warm mix appeared to exhibit comparable performance to the HMA. A laboratory characterization effort also seemed to corroborate the rutting observations from traffic tests.
      Citation: Transportation Research Record
      PubDate: 2021-04-17T10:02:18Z
      DOI: 10.1177/03611981211000753
       
  • Evaluation of Acceptance Risks through Percent within Limit for Highway
           Materials and Pavement Construction
    • Authors: Yunpeng Zhao, Dimitrios Goulias
      Abstract: Transportation Research Record, Ahead of Print.
      The majority of State Highway Agencies now employ statistical-based specifications for the acceptance of highway materials and pavement construction. The parameters of these statistical acceptance plans are specified based on engineering judgment and may result in a high level of risk to both the agency and contractor. To appropriately apply such specifications to the pavement construction industry, the associated production quality (i.e., materials and construction variability) must be well understood by all parties involved, and its potential effects need to be assessed. To address this, the objective of this study is to quantify the risks to the agencies and contractors (i.e., Type I and Type II errors) associated with the use of both single and multiple acceptance quality characteristics through constructing operating characteristic curves. It is also the purpose of this study to provide guidelines to properly implement the key components of an acceptance plan and its associated statistics. The methodology and findings identified in this study can be applied elsewhere to evaluate the acceptance plans and the associated risks related to highway materials and pavement construction.
      Citation: Transportation Research Record
      PubDate: 2021-04-16T06:18:09Z
      DOI: 10.1177/03611981211006436
       
  • Spatio-Temporal Analysis of Freight Flows in Southern California
    • Authors: Daniel Rivera-Royero, Miguel Jaller, Chang-Mo Kim
      Abstract: Transportation Research Record, Ahead of Print.
      This paper analyses the spatio-temporal patterns of freight flows in Southern California using weigh-in-motion (WIM) data between 2003 and 2015. The study explores the spatial relationships between truck volumes, load ratios, and gross vehicle weights for different vehicle classes, through econometric and centrographic analyses during the study period. Overall, the results confirmed the existence of the logistics sprawl phenomenon, highlighted the effect of the 2008 to 2009 major recession in the concentration of freight facilities and flows, indicated that the changes in flow patterns vary for different vehicle classes, and found low vehicle capacity utilization for light- (WIM classes 5–7) and medium- (WIM classes 8–10) heavy-duty trucks, though recently improving. These results are consistent with the growth in residential deliveries owing to e-commerce, showing increased light-heavy-duty trucks flows concentrated closer to the consumption areas, and experiencing larger flow reductions compared to heavy vehicle flows as the distance from the area increases; and showing that medium-heavy-duty vehicles used in both full-truck-load, and less-than-truck-load vocations are prevalent throughout the study area, whereas there is a trade-off between light- and heavy-heavy duty trucks (WIM classes 11–13) at the proximity, and the outskirts of the consumption markets, respectively. Moreover, the study shows the usefulness of the WIM data in identifying spatial and temporal dynamics in freight demand, providing additional information for planning, maintenance, and rehabilitation of the infrastructure. More importantly, the results, coupled with other evidence from the literature, show how major disruptions such as the recession significantly affect truck traffic.
      Citation: Transportation Research Record
      PubDate: 2021-04-16T06:16:48Z
      DOI: 10.1177/03611981211004130
       
  • Driver Yielding and Pedestrian Performance at Midblock Crossings on
           Three-Lane Roadways with Rectangular Rapid Flashing Beacons
    • Authors: Sirisha Kothuri, Frank Boateng Appiah, Christopher Monsere
      Abstract: Transportation Research Record, Ahead of Print.
      Rectangular rapid flashing beacons (RRFBs) have proven to be a useful tool for improving driver yielding and pedestrians’ safety at midblock crossings. This study analyzed driver yielding at 23 RRFB-enhanced midblock crossings on three-lane roadways with and without median refuge islands in Oregon. The locations were chosen to represent a range of posted speed limits and average daily traffic that aligns with existing guidance for median and beacon installations. Sites were classified either as (a) no median refuge, RRFBs placed outside the roadway, (b) median refuge, RRFBs placed outside the roadway, (c) median refuge, RRFBs placed on the island and outside the roadway. Yielding was determined following protocols established in prior research. Two hundred seventy-six hours of video footage were analyzed, resulting in 3,065 crossing events (1,338 staged; 1,727 naturalistic) undertaken by 3,683 pedestrians. High yielding rates were observed—the average near side yielding rate was 97%, with the lowest site having a rate of 89.9%. Yielding rates were generally higher on the far side. Owing to sample size and consistently high yielding rates, it was not possible to make conclusive observations about the relationship between driver yielding and the presence of median or additional beacons for the volume and speed combinations. The results generally indicated that yielding rates increased with the addition of median beacons. The findings also suggested median refuge islands with a beacon increased yielding. The increase in yielding was statistically significant at sites with average daily traffic of 12,000 to 15,000.
      Citation: Transportation Research Record
      PubDate: 2021-04-15T12:15:24Z
      DOI: 10.1177/03611981211004962
       
  • Simulation of Potential Use Cases for Shared Mobility Services in the City
           of Ann Arbor
    • Authors: Richard Twumasi-Boakye, Xiaolin Cai, James Fishelson, Andrea Broaddus
      Abstract: Transportation Research Record, Ahead of Print.
      In this paper, we model and simulate special use cases of on-demand shared mobility services for the City of Ann Arbor, MI. We define shared mobility as any motor-vehicle-served transportation option between private vehicles and public transit, such as taxis, demand-responsive transit, and dynamic shuttles. Here, we present and evaluate a suite of four different service types that could potentially complement existing transportation services in Ann Arbor. A novel aspect of this study is that it tests scenarios that were developed in consultation with city planners looking for insights into real-world problems. This study used fleet simulation software to test four service configuration scenarios for a hypothetical on-demand shared mobility service: citywide shuttle, a corridor-based downtown shuttle, a park and ride shuttle, and a transit-complementary service. Three levels of demand were tested for each scenario: 3%, 9%, and 15% of all private vehicle trips in the city. Findings indicated that citywide on-demand shared mobility services struggled to achieve higher vehicle occupancies than private vehicles at approximately 1.4. Service configurations with aggregated trip density resulted in slightly improved occupancies, as found in downtown- and park and ride shuttle scenarios. More impactful was aggregating demand by moving from “many-to-many” routing as with citywide floating services to “many-to-one” routing as with downtown- or park and ride shuttle services, which increased vehicle occupancy from 1.4 to almost 2. Lastly, we also discuss the potential benefits of reduced congestion and parking needs.
      Citation: Transportation Research Record
      PubDate: 2021-04-15T12:12:09Z
      DOI: 10.1177/03611981211004588
       
  • Measuring Changes in Multimodal Travel Behavior Resulting from Transport
           Supply Improvement
    • Authors: Elodie Deschaintres, Catherine Morency, Martin Trépanier
      Abstract: Transportation Research Record, Ahead of Print.
      Despite the desired transition toward sustainable and multimodal mobility, few tools have been developed either to quantify mode use diversity or to assess the effects of transportation system enhancements on multimodal travel behaviors. This paper attempts to fill this gap by proposing a methodology to appraise the causal impact of transport supply improvement on the evolution of multimodality levels between 2013 and 2018 in Montreal (Quebec, Canada). First, the participants of two household travel surveys were clustered into types of people (PeTys) to overcome the cross-sectional nature of the data. This allowed changes in travel behavior per type over a five-year period to be evaluated. A variant of the Dalton index was then applied on a series of aggregated (weighted) intensities of use of several modes to measure multimodality. Various sensitivity analyses were carried out to determine the parameters of this indicator (sensitivity to the least used modes, intensity metric, and mode independency). Finally, a difference-in-differences causal inference approach was explored to model the influence of the improvement of three alternative transport services (transit, bikesharing, and station-based carsharing) on the evolution of modal variability by type of people. The results revealed that, after controlling for different socio-demographic and spatial attributes, increasing transport supply had a significant and positive impact on multimodality. This outcome is therefore good news for the mobility of the future as alternative modes of transport emerge.
      Citation: Transportation Research Record
      PubDate: 2021-04-15T12:10:45Z
      DOI: 10.1177/03611981211003104
       
  • Simulation Framework for Analysis of Relief Distribution Efforts after
           Hurricane Maria in Puerto Rico
    • Authors: María X. Rojas Ibarra, Didier Valdés, José Holguín-Veras
      Abstract: Transportation Research Record, Ahead of Print.
      After massive disasters and catastrophes, communities’ infrastructure and communication systems can be severely affected to the point that they cease to function. Furthermore, the affected areas are supplied with significant amounts of donations, which need to be optimally inventoried, stored, and distributed to benefit those affected while minimizing logistics costs. In these events, it is vital to have disaster response plans in place, and readily available trained personnel who can reach and support the affected areas with critical supplies in time to prevent the loss of lives and property. In 2017, Puerto Rico was devastated by Hurricane Maria, a category five hurricane. Non-established relief groups (NERGs) formed immediately after the disaster to reduce the distress of the severely affected population. This research presents a conceptual framework with the key factors to improve the operation of NERGs when participating in the relief efforts after a catastrophic event. The proposed framework considers the steps required for an efficient relief effort, and it is intended to support a well-organized emergency response process by NERGs. Simulation tools were implemented to assess the operations performed by these groups to manage supplies. Various layouts for the space usage distribution and factors that affect the material convergence phenomenon were evaluated. Recommendations are provided for NERGs to improve the efficiency of their activities and increase the benefits offered to the affected communities.
      Citation: Transportation Research Record
      PubDate: 2021-04-15T08:39:16Z
      DOI: 10.1177/03611981211004170
       
  • Roundabouts in the United States: An International Comparison of
           Illuminance Requirements and Costs
    • Authors: Franklin E. Gbologah, Simon Berrebi, Angshuman Guin, Michael O. Rodgers
      Abstract: Transportation Research Record, Ahead of Print.
      United States federal guidelines recommend systematic illumination of roundabouts in both rural and urban areas. However, competing conventional intersections in rural areas can be kept unlit. Highway illumination is also a major contributor to intersection operating and maintenance costs. This paper reviews roundabout illumination policies from 44 countries to determine if systematic illumination is normal practice and if not, to identify the warranting conditions. In addition, this paper compares the illumination level requirements and implied costs for three reference U.S. rural roundabouts with their equivalents from 15 selected countries. Professional lighting design software, DIALux®, was used to build roundabout illumination models corresponding to the recommended illuminances in the study countries and the simulation outputs were converted into annual operating costs to facilitate the comparisons. The findings indicate that most countries (approximately 59%) do not require systematic illumination of roundabouts in rural areas. While a few countries (approximately 16%) do attempt to illuminate all roundabouts it is more common to find such a requirement in urban areas. The study also finds that the average minimum maintained illuminance is higher in the U.S.A. than in Europe and the United Kingdom. However, the U.S. tax payer pays significantly less than their counterparts in the other countries studied. These findings are significant because the desired proliferation of roundabouts in the U.S.A. would receive a significant boost if the U.S.A. were to adopt lower illuminance levels, a non-systematic illumination policy, or both, for rural roundabouts.
      Citation: Transportation Research Record
      PubDate: 2021-04-13T08:26:36Z
      DOI: 10.1177/03611981211002817
       
  • Real-Time Twitter Data Mining Approach to Infer User Perception Toward
           Active Mobility
    • Authors: Rezaur Rahman, Kazi Redwan Shabab, Kamol Chandra Roy, Mohamed H. Zaki, Samiul Hasan
      Abstract: Transportation Research Record, Ahead of Print.
      This study evaluates the level of service of shared transportation facilities through mining geotagged data from social media and analyzing the perceptions of road users. An algorithm is developed adopting a text classification approach with contextual understanding to filter out relevant information related to users’ perceptions toward active mobility. Using a heuristic-based keyword matching approach produces about 75% tweets that are out of context, so that approach is deemed unsuitable for information extraction from Twitter. This study implements six different text classification models and compares the performance of these models for tweet classification. The model is applied to real-world data to filter out relevant information, and content analysis is performed to check the distribution of keywords within the filtered data. The text classification model “term frequency-inverse document frequency” vectorizer-based logistic regression model performed best at classifying the tweets. To select the best model, the performances of the models are compared based on precision, recall, F1 score (geometric mean of precision and recall), and accuracy metrics. The findings from the analysis show that the proposed method can help produce more relevant information on walking and biking facilities as well as safety concerns. By analyzing the sentiments of the filtered data, the existing condition of biking and walking facilities in the DC area can be inferred. This method can be a critical part of the decision support system to understand the qualitative level of service of existing transportation facilities.
      Citation: Transportation Research Record
      PubDate: 2021-04-12T08:16:33Z
      DOI: 10.1177/03611981211004966
       
  • Development of a Simulated Three-Dimensional Truck Model to Predict Excess
           Fuel Consumption Resulting from Pavement Roughness
    • Authors: Xiuyu Liu, Imad L. Al-Qadi
      Abstract: Transportation Research Record, Ahead of Print.
      Excess vehicle fuel consumption, the percentage change in fuel consumption caused by road roughness, is an important part of the environmental and cost assessment of a pavement’s life cycle. Flexible and efficient computational methods make it possible to use mechanistic models to estimate excess fuel consumption. A stochastic pavement–vehicle interaction model was developed recently based on a half-truck model and stationary road roughness profiles. Although the introduced method was a step forward, it does not allow roll vibration. In addition, the error caused by stationary assumption on roughness profiles has not been quantified. This study proposes a numerical approach to assess the roughness-induced fuel consumption of a semi-trailer truck on non-deformable rough pavements. A three-dimensional (3D) semi-trailer truck model is formulated with a nonstationary parallel road roughness model. The simulation results of the integrated truck–pavement model are validated against empirical formulas. Tire stiffness is identified as the most important truck property, followed by suspension damping, suspension stiffness, and cargo loading. For road roughness characteristics, local roughness variance—overlooked by the stationary assumption—can underestimate excess fuel consumption by 42%. Using the 3D truck model and corresponding roughness profiles as excitation inputs would reduce the computation error by more than 10%. This study also proposes an extended roughness–speed–impact model, considering a second-order International Roughness Index term and effect of local roughness variance. The new regression model increases the prediction explanation R2 from 88.7% to 99.2%.
      Citation: Transportation Research Record
      PubDate: 2021-04-12T08:16:30Z
      DOI: 10.1177/03611981211007849
       
  • C-FLEX Advanced Finite Element Analysis Program for Flexible Pavement
           Analysis and Design
    • Authors: Jiayi Luo, Haohang Huang, Issam I. A. Qamhia, Erol Tutumluer, Jeb S. Tingle
      Abstract: Transportation Research Record, Ahead of Print.
      The U.S. Army Engineer Research and Development Center (ERDC) of the U.S. Army Corps of Engineers has initiated an effort to modernize the Department of Defense (DOD) pavement design and evaluation procedures initially developed in the 1950s. Flexible pavement analyses and evaluations are currently performed based on the elastic layered WESLEA and WESDEF software programs. To modernize the current pavement design and evaluation procedures used by the DOD, an advanced axisymmetric Finite Element Method (FEM) based analysis program, named C-FLEX, was developed and is introduced in this paper. The C-FLEX program is designed to feature accurate material models for all pavement layers with the capability to model the cross-anisotropic and nonlinear elastic properties of unbound base/subbase and subgrade layers, the viscoelastic behavior of the asphalt mixture, as well as mechanical reinforcement using geosynthetics in flexible pavements. The FEM formulation in C-FLEX and the program architecture and implementation details are introduced and discussed in this paper. The different analysis schemes and proper models used to characterize the cross-anisotropy and stress-dependent material nonlinearity are also described in detail. The viscoelastic analysis scheme and the geosynthetic characterization are currently under development and so are not included in this paper. Furthermore, two conventional flexible pavements with different layer properties are analyzed to verify the solutions and reliability of the C-FLEX program. Based on this development effort with ERDC, the C-FLEX program is envisioned to eventually serve as the flexible pavement analysis engine for the DOD’s new mechanistic design and evaluation platform.
      Citation: Transportation Research Record
      PubDate: 2021-04-12T08:16:26Z
      DOI: 10.1177/03611981211006724
       
  • Efficient Road Crack Detection Based on an Adaptive Pixel-Level
           Segmentation Algorithm
    • Authors: Nima Safaei, Omar Smadi, Babak Safaei, Arezoo Masoud
      Abstract: Transportation Research Record, Ahead of Print.
      Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for the development of robust automated distress evaluation systems that comprise a low-cost crack detection method for performing fast and cost-effective roadway health monitoring practices. Most of the current methods are costly and have labor-intensive learning processes, so they are not suitable for small local-level projects with limited resources or are only usable for specific pavement types.This paper proposes a new method that uses an adapted version of the weighted neighborhood pixels segmentation algorithm to detect cracks in 2-D pavement images. The method uses the Gaussian cumulative density function (CDF) as the adaptive threshold to overcome the drawback of fixed thresholds in noisy environments. The proposed algorithm was tested on 300 images containing a wide range of noise representative of various pavement noise conditions. The method proved to be time and cost-efficient as it took less than 3.15 s per 320 × 480 pixels image for a Xeon (R) 3.70 GHz CPU processor to generate the detection results. This makes the proposed method a perfect choice for county-level pavement maintenance projects requiring cost-effective pavement crack detection systems. The validation results were promising for the detection of medium to severe-level cracks (precision = 79.21%, recall = 89.18%, and F1 score = 83.90%).
      Citation: Transportation Research Record
      PubDate: 2021-04-12T08:16:05Z
      DOI: 10.1177/03611981211002203
       
  • Stop Sign Gap Assist Application in a Connected Vehicle Simulation
           Environment
    • Authors: Mahmoud Arafat, Mohammed Hadi, Thodsapon Hunsanon, Kamar Amine
      Abstract: Transportation Research Record, Ahead of Print.
      Assessment of the safety and mobility impacts of connected vehicles (CVs) and cooperative automated vehicle applications is critical to the success of these applications. In many cases, there may be trade-offs in the mobility and safety impacts depending on the setting of the parameters of the applications. This study developed a method to evaluate the safety and mobility benefits of the Stop Sign Gap Assist (SSGA) system, a CV-based application at unsignalized intersections, which utilizes a calibrated microscopic simulation tool. The study results confirmed that it was critical to calibrate the drivers’ gap acceptance probability distributions in the utilized simulation model to reflect real-world driver behaviors when assessing SSGA impacts. The simulation models with the calibrated gap parameters were then used to assess the impacts of the SSGA. The results showed that SSGA can potentially improve overall minor approach capacity at unsignalized intersections by approximately 35.5% when SSGA utilization reaches 100%. However, this increase in capacity depended on the setting of the minimum gap time in the SSGA and there was a clear trade-off between capacity and safety. The analysis indicated that as the minimum gap time used in the SSGA increased, the safety of the intersection increased, showing for example that with the utilization of an 8-s gap at a 750 vph main street flow rate, the number of conflicts could decrease by 30% as the SSGA utilization rate increased from 0% to 100%.
      Citation: Transportation Research Record
      PubDate: 2021-04-10T08:42:52Z
      DOI: 10.1177/03611981211006111
       
  • Detection of Pavement Maintenance Treatments using Deep-Learning Network
    • Authors: Lu Gao, Yao Yu, Yi Hao Ren, Pan Lu
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement maintenance and rehabilitation (M&R) records are important as they provide documentation that M&R treatment is being performed and completed appropriately. Moreover, the development of pavement performance models relies heavily on the quality of the condition data collected and on the M&R records. However, the history of pavement M&R activities is often missing or unavailable to highway agencies for many reasons. Without accurate M&R records, it is difficult to determine if a condition change between two consecutive inspections is the result of M&R intervention, deterioration, or measurement errors. In this paper, we employed deep-learning networks of a convolutional neural network (CNN) model, a long short-term memory (LSTM) model, and a CNN-LSTM combination model to automatically detect if an M&R treatment was applied to a pavement section during a given time period. Unlike conventional analysis methods so far followed, deep-learning techniques do not require any feature extraction. The maximum accuracy obtained for test data is 87.5% using CNN-LSTM.
      Citation: Transportation Research Record
      PubDate: 2021-04-10T08:42:34Z
      DOI: 10.1177/03611981211007846
       
  • Application of Advanced Multi-Sensor Non-Destructive Testing System for
           the Evaluation of Pavements Affected by Transverse Crack-Heaving
    • Authors: Eyoab Zegeye-Teshale, Thomas Calhoon, Eddie Johnson, Shongtao Dai
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement tenting, also referred to as crack-heaving, is a distress condition that primarily affects bituminous roads constructed in cold climates. This type of distress spreads over long stretches of roadways and can drastically affect drivers’ safety and comfort. The phenomenon occurs in freezing winter temperatures offering a limited and dire time window for testing. This paper discusses using an integrated multi-sensor non-destructive testing methodology to evaluate and characterize pavements affected by tenting. A survey van equipped with high-definition video and thermal cameras, LIDAR laser scanner, high-resolution accelerometer, and ground-penetrating radar (GPR) technologies was used to assess several roads suspected of tenting. The plurality of measuring devices and the data fusion and synchronization capabilities proved useful in revealing important pavement tenting characteristics that would have been otherwise overlooked. The data analysis led to the development of test parameters, derived from longitudinal profile measurements, that captured reasonably well the intensity and frequency of the tented cracks. The parameters were successfully employed to characterize the tested roads and determine the extent of critically affected segments. The study also showed the potential of GPR measurements to investigate underneath moisture conditions contributing to the formation of the tented cracks. Finally, the findings and tools developed in this study were discussed and compared with observations of local engineers who have extensive experience and insight on the subject matter. The knowledge and recommendations gathered in this final effort were also synthesized and incorporated into the paper.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T12:02:48Z
      DOI: 10.1177/03611981211006430
       
  • Assessing the Impact of Automated and Connected Automated Vehicles on
           Virginia Freeways
    • Authors: Bumsik Kim, Kevin P. Heaslip, Mirla Abi Aad, Antonio Fuentes, Noah Goodall
      Abstract: Transportation Research Record, Ahead of Print.
      This study assesses the impact of the introduction of connected and automated vehicles on Virginia freeway corridors. Three vehicle types: legacy vehicles (LV), automated vehicles (AV), and connected automated vehicles (CAV), were considered in mixed traffic scenarios. Previous relevant studies were reviewed and the proper operating parameters for LV, AV, and CAV identified. AV and CAV driving behavior models were developed in the VISSIM environment. According to the basic freeway test network results, AV and CAV increase road capacity by 29% and 91%. In the merging freeway test network, AV and CAV increase road capacity by 48% and 60% compared with LV, respectively. A model with diverse LV, AV, and CAV market penetration and diverse traffic demand was tested on I-95 in Virginia, where the research team tested the speed and throughput. Under the current traffic demand, the average speed was higher when there were more AV and no CAV in the traffic flow. However, the average speed of CAV in a congested segment is higher than LV. In the case of throughput, CAV shows poor performance under current traffic demand. With increased traffic demand, high penetrations of AV and CAV present better performance because of their short headway and homogeneity. Therefore, the study predicts that in the future, as the traffic demand grows, AV and CAV can reduce traffic congestion.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T12:01:21Z
      DOI: 10.1177/03611981211004979
       
  • Evaluating Correlations of External Factors and Performance Measures of
           the Multimodal Transportation System in Florida
    • Authors: Yanshuo Sun, Juyeong Choi, Navid Nickdoost, Sajeeb Kirtonia, Jessica VanDenBogaert
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this study is to quantify the correlation between nearly 100 external factors and over 70 performance measures of the Florida multimodal transportation system, based on the empirical data covering a 10 year period (2009–2018). We first use time-lagged cross-correlation to quantify the correlation between each pair of external factors and performance measures. We then identify the highly correlated external factors with all performance measures or a subset of them. We find that Percentage of Population in Poverty (Florida), Number of Housing Units (Florida), House Price Index (National), Consumer Price Index–Rent Price Index (Florida), and Percentage of Population in Poverty (National) are the external factors highly correlated with the whole system, while the external factors highly correlated with different modes vary. This paper thus contributes to the transportation performance measurement literature by proposing a practical procedure based on time series analysis to help transportation agencies identify important external factors for tracking and monitoring.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T11:59:52Z
      DOI: 10.1177/03611981211006107
       
  • Spatial Roadway Condition-Assessment Mapping Utilizing Smartphones and
           Machine Learning Algorithms
    • Authors: Charalambos Kyriakou, Symeon E. Christodoulou, Loukas Dimitriou
      Abstract: Transportation Research Record, Ahead of Print.
      The paper presents a data-driven framework and related field studies on the use of supervised machine learning and smartphone technology for the spatial condition-assessment mapping of roadway pavement surface anomalies. The study explores the use of data, collected by sensors from a smartphone and a vehicle’s onboard diagnostic device while the vehicle is in movement, for the detection of roadway anomalies. The research proposes a low-cost and automated method to obtain up-to-date information on roadway pavement surface anomalies with the use of smartphone technology, artificial neural networks, robust regression analysis, and supervised machine learning algorithms for multiclass problems. The technology for the suggested system is readily available and accurate and can be utilized in pavement monitoring systems and geographical information system applications. Further, the proposed methodology has been field-tested, exhibiting accuracy levels higher than 90%, and it is currently expanded to include larger datasets and a bigger number of common roadway pavement surface defect types. The proposed system is of practical importance since it provides continuous information on roadway pavement surface conditions, which can be valuable for pavement engineers and public safety.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T11:55:50Z
      DOI: 10.1177/03611981211006105
       
  • Using Large Linked Field Data Sets to Investigate Density’s Impact on
           the Performance of Washington State Department of Transportation Asphalt
           Pavements
    • Authors: Ryan Howell, Stephen Muench, Milad Zokaei Ashtiani, James Feracor, Mark Russell, Jeff Uhlmeyer
      Abstract: Transportation Research Record, Ahead of Print.
      Large data sets of Washington State Department of Transportation (WSDOT) pavement construction and condition data are linked together and used to investigate an implemented change in in-place density to lower specification limit (LSL) from 91% to 92%. This serves as a test case for using such large in-service data sets to create analysis value for a state DOT. Findings include: (1) WSDOT field density has remained relatively steady at 93% for over 20 years; (2) raising the density LSL to 92% will likely result in more contractor effort to achieve higher densities; (3) no clear trend links density with better pavement condition; (4) raising the density LSL will likely result in fewer problematically low densities; and (5) there is no evidence of differing pavement performance based on asphalt content, gradation, or nominal maximum aggregate size.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T11:49:21Z
      DOI: 10.1177/03611981211006101
       
  • Development of an Artificial Neural Network-Based Procedure for the
           Verification of Traffic Speed Deflectometer Measurements
    • Authors: Hossam Abohamer, Mostafa A. Elseifi, Zia U. A. Zihan, Zhong Wu, Nathan Kebede, Zhongjie Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Since the 1980s, the falling weight deflectometer (FWD) has been the primary deflection-measuring device in the United States to evaluate the structural conditions of in-service pavements. However, the stop and go nature of the FWD limits its application at the network level. In the early 2000s, the traffic speed deflectometer (TSD) was introduced as an alternate deflection-measuring device for network-level applications. TSD collects deflection measurements while traveling at traffic speed, which provides improved spatial coverage and no traffic disturbance. The verification of TSD measurements is of great interest as many agencies move toward widespread implementation. This study aims at developing a reliable and straightforward procedure for the verification of TSD measurements using limited FWD measured deflection measurements. The verification procedure employs a trained artificial neural network (ANN) model to shift TSD deflections to their corresponding FWD deflections. The ANN model was trained and verified based on FWD and TSD measurements from two deflection-testing programs. The developed model accurately predicted FWD measurements with a coefficient of determination (R2) of 0.994. The suitability of the proposed verification procedure was evaluated using statistical and engineering-based measures and showed acceptable accuracy. Results also validated that the proposed method could be used to verify TSD measurements before its use for conducting deflection measurements at the network level.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T11:46:55Z
      DOI: 10.1177/03611981211005774
       
  • Short-Term Field Performance and Cost-Effectiveness of Crumb-Rubber
           Modified Asphalt Emulsion in Chip Seal Applications
    • Authors: Md Nafiur Rahman, Md Tanvir Ahmed Sarkar, Mostafa A. Elseifi, Corey Mayeux, Samuel B. Cooper, Ken Free
      Abstract: Transportation Research Record, Ahead of Print.
      Chip sealing is a commonly used pavement maintenance technique that aims to delay pavement deterioration by reducing water infiltration and restoring skid resistance. The objective of this study was to evaluate the short-term field performance and cost-effectiveness of chip seals prepared with different types of asphalt emulsion and application rates. A newly introduced crumb-rubber modified asphalt emulsion was evaluated, one that allows chip seal installation at the same temperature as a standard emulsion. Types of emulsion included a crumb-rubber modified asphalt emulsion (CRS-2TR), a polymer-modified emulsion (CRS-2P), and a conventional unmodified emulsion (CRS-2). Application rates were obtained from the Louisiana Department of Transportation and Development (DOTD), the Texas Department of Transportation (DOT) specifications, and from the chip seal design method recommended in NCHRP Report 680. Seven chip seal sections were constructed and monitored regularly over a 12-month period. In the northbound lane, the chip seal section constructed with CRS-2TR (0.37 gal per square yard [gsy]) was the best performer statistically. In the southbound lane, the chip seal sections constructed with CRS-2TR and CRS-2P (0.31 gsy) performed similarly. Furthermore, the maximum Service Life Extension (SLE) was observed for the CRS-2TR (0.31 gsy) chip seal sections, whereas the chip seal sections constructed with CRS-2 had the lowest SLE. In addition, the most cost-effective chip seal section was achieved by the application of CRS-2TR emulsion at the Louisiana DOTD recommended emulsion application rate.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T11:43:55Z
      DOI: 10.1177/03611981211005469
       
  • Incorporating Low-Stress Bicycling Connectivity into Expanded Transit
           Service Coverage
    • Authors: Ting Zuo, Heng Wei, Na Chen
      Abstract: Transportation Research Record, Ahead of Print.
      The speed advantage in bicycling over walking is believed to ease first-and-last mile (F&LM) travel and expand transit service coverage. To quantitatively investigate the potential effect of using bicycle as a F&LM connector, the paper measures and compares the impacts of walking and bicycling F&LM access on transit service coverage. In the estimation of transit service coverage, F&LM travel decay functions representing the attractiveness of public transit that declines with increasing walking/biking time to access transit facilities and the spatial boundaries of transit catchment areas are developed using GPS trajectory data collected from the latest Cincinnati Household Travel Survey in Hamilton County, Ohio. Level of traffic stress is used to evaluate the bicycle suitability of streets and bike network connectivity. Based on the F&LM distance decay functions and low-stress bike network connectivity, the transit service coverage area as well as the transit-served population and employment in Hamilton County, Ohio, are estimated. Results show that more population can reach transit services and therefore employment by bicycling than walking. Meanwhile, disadvantaged groups, that is, low-income and zero-car population, can be better served by transit if using bicycle as the F&LM connector. In addition, low-stress bicycling connectivity is a significant factor determining the bicycle-transit service coverage, and a well-connected low-stress bike network with quality bikeways is crucial to guaranteeing that. These findings can be used as references to assist planners in their decision-making process to achieve better mobility and accessibility.
      Citation: Transportation Research Record
      PubDate: 2021-04-09T11:36:55Z
      DOI: 10.1177/0361198121998956
       
  • Evaluation of Chloride Intrusion along Concrete–Grout Interfaces for
           Post-Tensioned Concrete Durability
    • Authors: Garrett Tatum, Benjamin Colbert, Natassia Brenkus
      Abstract: Transportation Research Record, Ahead of Print.
      A pour-back is a critical component of a post-tensioned concrete system, affecting its durability by protecting anchorages and vents from corrosion. However, the material interface between the grout pour-back and the concrete member may serve as an accelerated pathway for chloride ion intrusion and may lead to premature corrosion of post-tensioning components. This study evaluates the vulnerability of concrete–grout interfaces through two experimental protocols: a novel electrical migration test and the standard electrical resistivity test. The results are used to predict the service life of pour-back systems using a concrete life-cycle assessment model. This research serves as a first step toward defining the chloride permeability of concrete–grout interfaces.
      Citation: Transportation Research Record
      PubDate: 2021-04-07T10:08:29Z
      DOI: 10.1177/03611981211006425
       
  • New Travel Time Reliability Methodology for Urban Arterial Corridors
    • Authors: Ernest O. A. Tufuor, Laurence R. Rilett
      Abstract: Transportation Research Record, Ahead of Print.
      The need for reliable performance measures of urban arterial corridors is increasing because of the rise in traffic congestion and the high value of users’ travel time. Consequently, travel time reliability (TTR), which attempts to capture the day-to-day variability in travel times, has recently received considerable research interest. The basis of all TTR metrics is the underlying travel time distribution (TTD) along the given link or corridor. Estimating and forecasting arterial corridor TTDs for TTR analysis is the focus of this paper. This paper proposes a TTR methodology that addresses some of the limitations of the current U.S. state-of-the-art methodology which was published in the 6th edition of the Highway Capacity Manual (HCM6). Specifically, HCM6 can only estimate average TTD and not the population TTD. However, the population TTD is needed for accurate trip decision-making by individual drivers and logistics companies. In addition, HCM6 cannot be used to analyze the effect of new technologies, such as connected and automated vehicles, nor can it be used easily for long corridors or networks. The proposed TTR methodology, which is traffic-microsimulation based, was applied on a 1.16 mi arterial testbed in Lincoln, Nebraska, U.S. It was shown that the proposed TTR methodology, when calibrated, could replicate the empirical population TTD at a 5% significance level. The population TTD could also be transformed into an average TTD that also replicated the corresponding empirical average TTD at a 5% significance level.
      Citation: Transportation Research Record
      PubDate: 2021-04-07T10:06:43Z
      DOI: 10.1177/03611981211006104
       
  • Application of Mobile Terrestrial LiDAR Scanning Systems for
           Identification of Potential Pavement Rutting Locations
    • Authors: Afshin Famili, Wayne A. Sarasua, Alireza Shams, William J. Davis, Jennifer H. Ogle
      Abstract: Transportation Research Record, Ahead of Print.
      Periodic measurement and identification of the presence and severity of pavement rutting are crucial for pavement management programs conducted by state transportation agencies. This paper proposes a novel analytical method for identifying pavement rutting locations using data collected by mobile terrestrial LiDAR scanning (MTLS). Four vendor MTLS systems were evaluated based on their ability to accurately reproduce a roadway’s transverse profile. To establish ground-truth measurements, 2 in. interval pavement transverse profiles, which included rutting sections, were collected using traditional surveying techniques. MTLS transverse profiles were evaluated using partial curve mapping, Fréchet distance, area, curve length, and dynamic time warping techniques. Resultant pavement transverse profiles were compared between vendors and a profile created from traditional surveying. Results indicate that calibrated MTLS systems can provide accurate transverse profiles for potential identification of pavement rut areas. Based on this determination, a novel method was developed for use in identifying locations of pavement rutting through analysis of the curvature of MTLS raster surfaces. After evaluating three grid cell sizes for elevation raster surfaces, a raster grid cell size of 1 ft × 1 ft was determined to be most suitable for identifying continuous concave raster cell groups along wheel path trajectories. These cell groupings were found to reliably identify pavement rutting locations. The analytical procedures employed through application of this method consist of an efficient workflow process that is not reliant on a time-consuming continuous comparison with an MTLS-modeled uniform surface.
      Citation: Transportation Research Record
      PubDate: 2021-04-07T10:04:43Z
      DOI: 10.1177/03611981211005777
       
  • Results of the 10-Year Arizona Quiet Pavement Pilot Program
    • Authors: Paul R. Donavan, Carrie J. Janello
      Abstract: Transportation Research Record, Ahead of Print.
      In April 2003, the Arizona Department of Transportation (ADOT) initiated a Quiet Pavement Pilot Program in cooperation with the Federal Highway Administration (FHWA). Under this program, many freeway segments in the Phoenix metropolitan area with Portland Cement Concrete pavement surfaces received 25.4-mm thick asphalt rubber friction course overlays to reduce highway-related traffic noise. This pilot program represented the first time that pavement type was allowed as a noise mitigation strategy on federally funded projects. As part of this program, ADOT developed a 10-year research program with FHWA to evaluate the long-term acoustic performance of this noise mitigation approach. The final measurements were completed in 2015. The program was done with three types of measurements: Type 1 examined tire/pavement noise at the source at 115 milepost locations; Type 2 examined noise in residential neighborhoods near the freeways; and Type 3 evaluated noise using direct measures of traffic noise adjacent to the freeways. Sound absorption measurements were also made at specific sites at various times throughout the project. Type 1 measurements documented an average initial reduction of 8.7 dBA and an average increase of 0.5 dB/year. The Type 2 measurements revealed an average initial reduction of 5.2 dBA, whereas the Type 3 measurements showed an average initial reduction of 9.1 dBA and an average increase of 0.5 dB/year. The measured reductions were also compared with ADOT and FHWA noise abatement criteria.
      Citation: Transportation Research Record
      PubDate: 2021-04-07T10:03:01Z
      DOI: 10.1177/03611981211005460
       
  • Engineered Semi-Flexible Composite Mixture Design and Its Implementation
           Method at Railroad Bridge Approach
    • Authors: Shuai Yu, Shihui Shen, Hai Huang, Cheng Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Considerable variation in the vertical displacement can cause railway tracks’ transition problems at the bridge approach. The vertical displacement gaps can result in amplification of the dynamic force and frequency, and gradually degrade the serviceability of the railway track. Many strategies, focusing on either modifying the track component or making changes to the entire structure, were used to mitigate transition problems. In particular, asphalt concrete underlayment as a structural adjustment method provides additional support to the ballast and protects the subgrade. However, its effect of reducing dynamic impact at the bridge approach is limited because asphalt mixture has a limited range of modulus and cannot make enough adjustments to the entire structure. Therefore, this paper aims to develop an engineered semi-flexible composite mixture (SFCM) design to mitigate the transition problem. The experiment showed that SFCM is a viscoelastic material with a wider modulus range, and its modulus can adjust with its air voids and the concrete slurry content. Track analysis using a 2.5D sandwich model was conducted to simulate the effects of the structure and material on the responses of the railway track under the dynamic loads and determine the arrangement of the transition zone. A four-segment transition zone design was eventually proposed for a special case of bridge approach. This method can be used to develop transition zones for achieving a smooth transition at the bridge approaches.
      Citation: Transportation Research Record
      PubDate: 2021-04-07T10:00:41Z
      DOI: 10.1177/03611981211004981
       
  • Deep Convolutional Neural Networks for Pavement Crack Detection using an
           Inexpensive Global Shutter RGB-D Sensor and ARM-Based Single-Board
           Computer
    • Authors: Pouria Asadi, Hamid Mehrabi, Alireza Asadi, Melody Ahmadi
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement distress assessment is a significant aspect of pavement management. Automated pavement crack detection is a challenging task that has been researched for decades in response to complicated pavement conditions. Current pavement condition assessment procedures are extensively time consuming, expensive, and labor-intensive. The primary goal of this paper is to develop a cost-effective and reliable platform using a red, green, blue, depth (RGB-D) sensor and deep learning detection models for automated pavement crack detection on a single-board ARM-based computer. To the best of our knowledge, for the first time, a pavement crack data set is prepared using a global shutter RGB-D sensor mounted on a car and annotated according to the Pascal visual object classes protocol, named PAVDIS2020. The proposed data set comprises 2,085 pavement crack images that are captured in a wide variety of weather and illuminance conditions with 5,587 instances of pavement cracks included in these images. A unified implementation of the Faster region-based convolutional neural networks and single shot multibox detector meta-architecture-based models is implemented to evaluate the accuracy, speed, and memory usage trade-off by using various convolutional neural networks-based backbones and various other training parameters on PAVDIS2020. The proposed pavement crack detection model was able to classify the cracks with 97.6% accuracy on PAVDIS2020 data set. The detection model is able to locate pavement crack patterns at the speed of 12 frames per second on a passively cooled Raspberry Pi 4 single-board computer.
      Citation: Transportation Research Record
      PubDate: 2021-04-07T09:59:02Z
      DOI: 10.1177/03611981211004974
       
  • Travel Patterns of Frequent and Non-Frequent Users on I-66 High-Occupancy
           Toll Lanes and Implications for the Value of Time Estimation
    • Authors: Mecit Cetin, Shanjiang Zhu, Hong Yang, Olcay Sahin
      Abstract: Transportation Research Record, Ahead of Print.
      Based on a three-month toll transaction data set that includes an anonymized unique identifier for each vehicle, this paper presents an in-depth analysis of traffic volumes and tolls on the I-66 High-Occupancy Toll (HOT) express lanes in Northern Virginia. The unique identifiers allow quantification of how frequently each vehicle travels through the corridor. Vehicles observed in selected time intervals are categorized into frequent and non-frequent groups based on the total number of trips made by each vehicle. For the morning commute, the analyses show that those traveling frequently on the HOT lanes are more sensitive to high tolls and typically travel earlier in the morning to avoid higher tolls. In other words, when tolls are relatively high (e.g., over $20), the fraction of frequent users in the traffic is much smaller as compared with that of non-frequent users (e.g., 25% versus 75%). To estimate how much toll the HOT-lane users are paying per unit of travel time saved, that is, value of travel time saving (VTTS), speeds on alternative routes parallel to the I-66 corridor are computed from probe data and compared with those on I-66 express lanes. The results show that the mean VTTS is $45.37 and $61.78 for frequent and non-frequent users, respectively, during the morning peak period. Whereas for the afternoon peak, the mean VTTS is $38.14 and $37.64 for frequent and non-frequent users. The implications of the difference in these value of time distributions for dynamic tolling are discussed.
      Citation: Transportation Research Record
      PubDate: 2021-04-05T07:06:46Z
      DOI: 10.1177/03611981211004192
       
  • Social Network Approach to Analyze Stability and Variability of Travel
           Decisions
    • Authors: Maike Puhe, Jens Schippl, Torsten Fleischer, Peter Vortisch
      Abstract: Transportation Research Record, Ahead of Print.
      Large-scale changes are expected for urban mobility systems, triggered by digitalization and various other factors such as climate concerns or urbanization. For researchers and planners, it is therefore becoming increasingly important to understand the determinants of variability and stability of travel decisions. The motivation for the study is that, in transportation research and modeling frameworks, travel choices usually derive from individual traits and accessibility variables. What is underrepresented by such an approach is that decisions are also socially embedded. The authors postulate that mobility patterns are strongly interwoven with the way people configure their social networks. The paper introduces and discusses an empirical approach to investigate the social embeddedness of mobility decisions. The basic premise of the approach is that social network configurations provide an important setting for daily life in general and individual travel decisions in particular. Analysis is based on a three-phase interview study, conducted in Karlsruhe, Germany. The analytical approach reveals that a substantial part of travel is only loosely coupled to generalized costs of transport. Instead, the motivational degree linked to certain relationships largely influences willingness to travel and the relative stability of everyday life. Relationships that are internally satisfying or extremely familiar to people appear highly persistent. Furthermore, relationships that provide a certain degree of flexibility appear changeable, though not necessarily in all dimensions. Only a very small number of relationships appear both substitutable and changeable.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T07:05:05Z
      DOI: 10.1177/03611981211002200
       
  • Almost Automating the Planner: Florida Department of Transportation’s
           Approach to Understanding Places through Context Classification
    • Authors: Margaret Kent, Jean Parlow, Deborah Chesna, DeWayne Carver, Patty Hurd, Jane Lim-Yap
      Abstract: Transportation Research Record, Ahead of Print.
      Context-based thinking is a transportation planning and design approach that aims to create infrastructure that serves diverse places and users. In Florida, context-based design is the approach Florida Department of Transportation (FDOT) has taken to implement its Statewide Complete Streets policy. FDOT intends to use the context of a roadway to better tailor design and planning solutions for the roadway, thereby putting the “right street in the right place.” To this end, FDOT developed a context classification system and guidance document for project corridors and has since applied the classification effort to the entire state road network. This paper shares a method that two FDOT districts, District One and District Five, used to accomplish their districtwide context classification efforts. The method leverages geographic information systems (GIS) to appropriately segment the road network, analyze connectivity, land use, and density measures, and evaluate the context classification for all state roads within each district. The resulting database is regularly updated using a GIS-based tool and serves as a rich source of information for FDOT and partner agency planners and designers.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T07:04:44Z
      DOI: 10.1177/03611981211002820
       
  • Effects of Pedestrian Crossing on Minor Road Capacity at Two-Way
           Stop-Controlled Intersections
    • Authors: Rui Yue, Guangchuan Yang, Yichen Zheng, Zong Tian
      Abstract: Transportation Research Record, Ahead of Print.
      Two-way stop-controlled (TWSC) intersections have been used extensively in the United States and other parts of the world when traffic signal control is not warranted. However, it was found that when a major road vehicle yields to crossing pedestrians, minor road traffic could use this extra gap, which tends to improve the capacity of some minor vehicle movements. The current capacity modeling methods did not take into account the effects of the pedestrian crossing on minor road capacity. This paper proposes an analytical model to quantify the increased capacity of minor street movements contributed by minor street pedestrian crossings and validates the model using both field data collected at a three-leg TWSC intersection and through the stochastic simulation method. A sensitivity analysis was performed to reveal the impacts of various factors on minor road capacity. In general, it was found that minor road left-turn capacity at the study intersection was positively correlated to pedestrian crossing volume, yielding rate, and pedestrian crossing time. Besides, modeling results showed that under relatively heavier conflict traffic volume conditions, the effect of the pedestrian crossing on increased capacity on the minor road was more significant.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T07:04:24Z
      DOI: 10.1177/03611981211002836
       
  • Predicting the Retroreflectivity Degradation of Waterborne Paint Pavement
           Markings using Advanced Machine Learning Techniques
    • Authors: Momen R. Mousa, Saleh R. Mousa, Marwa Hassan, Paul Carlson, Ibrahim A. Elnaml
      Abstract: Transportation Research Record, Ahead of Print.
      Waterborne paint is the most common marking material used throughout the United States. Because of budget constraints, most transportation agencies repaint their markings based on a fixed schedule, which is questionable in relation to efficiency and economy. To overcome this problem, state agencies could evaluate the marking performance by utilizing measured retroreflectivity of waterborne paints applied in the National Transportation Product Evaluation Program (NTPEP) or by using retroreflectivity degradation models developed in previous studies. Generally, both options lack accuracy because of the high dimensionality and multi-collinearity of retroreflectivity data. Therefore, the objective of this study was to employ an advanced machine learning algorithm to develop performance prediction models for waterborne paints considering the variables that are believed to affect their performance. To achieve this objective, a total of 17,952 skip and wheel retroreflectivity measurements were collected from 10 test decks included in the NTPEP. Based on these data, two CatBoost models were developed with an acceptable level of accuracy which can predict the skip and wheel retroreflectivity of waterborne paints for up to 3 years using only the initial measured retroreflectivity and the anticipated project conditions over the intended prediction horizon, such as line color, traffic, air temperature, and so forth. These models could be used by transportation agencies throughout the United States to 1) compare between different products and select the best product for a specific project, and 2) determine the expected service life of a specific product based on a specified threshold retroreflectivity to plan for future restriping activities.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T07:01:18Z
      DOI: 10.1177/03611981211002844
       
  • Inferring the Purposes of using Ride-Hailing Services through Data Fusion
           of Trip Trajectories, Secondary Travel Surveys, and Land Use Data
    • Authors: Sanjana Hossain, Khandker Nurul Habib
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a data fusion methodology for inferring trip purposes from GPS trajectories of ride-hailing services in Toronto. The methodology has a discrete choice model at its core that predicts the most probable purpose distributions using only basic trip-related information such as approximate pick-up and drop-off locations, trip start times, and land use characteristics around the origins and destinations. The choice model is estimated using revealed trip purpose data from a small-sample travel survey augmented by land use information from an enhanced point of interest database and the census. The methodology is applied to the trajectories of commercial ride-hailing trips made in Toronto between September 2016 and September 2018. For the core choice model, multinomial, nested, and mixed multinomial logit models are compared. Validation of the inferred trip purposes using the trip purpose proportions from another independent survey (not used in choice model estimation) reveal that the multinomial logit model can infer ride-hailing trip purpose distribution with reasonable accuracy. The inferred purpose distribution explains the nature of ride-hailing trips and provides important context of travel demand generated by the services. The results indicate that although ride-hailing services are mostly used for discretionary activities, they also play important roles in daily commuter travel. A quarter of the total weekday ride-hailing trips were made for work- and school-related activities. With increasing ridership, these services may start influencing conventional travel modes and thereby adversely affect the level of traffic congestion and transit ridership in the city.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T07:00:58Z
      DOI: 10.1177/03611981211003593
       
  • Spatiotemporal Demand Prediction Model for E-Scooter Sharing Services with
           Latent Feature and Deep Learning
    • Authors: Seung Woo Ham, Jung-Hoon Cho, Sangwoo Park, Dong-Kyu Kim
      Abstract: Transportation Research Record, Ahead of Print.
      The electric scooter (e-scooter) sharing service has attracted significant attention because of its extensive usage and eco-friendliness. Since e-scooters are mostly accessed by foot, the presence of e-scooters within walking distance has a crucial effect on the service quality. Therefore, to maintain appropriate service quality, relocation strategies are often used to properly distribute e-scooters within service areas. There are extensive literatures on demand forecasting for an efficient relocation. However, the study of the relocation of small-scale spatial units within walking distance level is still inadequate because of the sparsity of demand data. This research aims to establish an effective methodology for predicting the demand for e-scooters in high spatial resolution. A new grid-based spatial setting was created with the usage data. The model in the methodology predicts not only the identified demand but also the unmet demand to increase practicality. A convolutional autoencoder is used to obtain the latent feature that can reduce the problem of representing sparse data. An encoder–recurrent neural network–decoder (ERD) framework with a convolutional autoencoder resulted in a huge improvement in predicting spatiotemporal events. This new ERD framework shows enhanced prediction performance, reducing the mean squared error loss to 0.00036 from 0.00679 compared with the baseline long short-term memory model. This methodological strategy has its significance in that it can solve any prediction issue with spatiotemporal data, even those with sparse data problems.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:57:38Z
      DOI: 10.1177/03611981211003896
       
  • Designing Multiple Short-Turn Routes to Mitigate the Crowding on a Bus
           Network
    • Authors: Sedong Moon, Shin-Hyung Cho, Dong-Kyu Kim
      Abstract: Transportation Research Record, Ahead of Print.
      On a transit route, initiating a trip beyond a transit route’s departure terminus and terminating the trip before its arrival is called “short-turn.” This study develops a method to design short-turn services to alleviate crowding on a transit network consisting of multiple overlapping routes. The proposed method consists of two processes: (i) optimizing routes, turn-back points, and fleet sizes of short-turn services by a genetic algorithm to minimize the sum of waiting, in-vehicle, operation, and social costs; (ii) assigning passenger trip demands to short-turn and existing services. These processes are performed iteratively to design multiple short-turn routes. The proposed method is applied to a real-world transit network in Seoul, Republic of Korea, to design 10 short-turn routes. The results are compared with two naïve methods that introduce short-turn services to sections with the maximum occupancy and the maximum demand divided by the section length, respectively. The comparison results show the proposed method is much superior to both of the naïve methods in reducing total costs. The result of the sensitivity analysis suggests that the value of in-vehicle time needs to be estimated accurately and site-specifically. The proposed model contributes to enhancing the convenience of transit users by effectively mitigating the crowding under budget constraints.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:57:17Z
      DOI: 10.1177/03611981211003899
       
  • Construction of an Electrically Heated Asphalt Road Based on Ribbon
           Technology
    • Authors: Eyal Levenberg, Quentin Félix Adam
      Abstract: Transportation Research Record, Ahead of Print.
      Although asphalt pavements are the most common pavement type worldwide, there is no accepted heating solution for this infrastructure class for melting snow and preventing ice formation at the ride-surface. This study was concerned with utilizing electric ribbon technology as a suitable heating solution. A method was proposed to introduce ribbon heaters into the typical paving process in a practical manner, causing minimal disruption to the normal paving operations, that is potentially expandable to large areas. The advocated idea was to deploy ribbons after an asphalt concrete (AC) lift has been paved and compacted, and before paving and compacting the next AC lift(s). In this context, a special grooving machine was envisioned to make shallow channels in the AC for cradling each ribbon. Thus, the system survivability is guaranteed, with all ribbons protected against the maneuvering of trucks, paving equipment, and heavy rollers. Subsequently, the method was demonstrated through the full-scale construction of a heated road that included installing ribbons in-between AC lifts. For this purpose, the protective ribbon channels were grooved with a customized milling machine. The entire construction process was described in detail, and some initial findings from activating the system were also included. An overall system survivability of 97% was achieved, and the installation concept appears practical and up-scalable.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:56:38Z
      DOI: 10.1177/03611981211004175
       
  • Fuel Consumption Intersection Control Performance Index
    • Authors: Aleksandar Stevanovic, Suhaib Al Shayeb, Satya S. Patra
      Abstract: Transportation Research Record, Ahead of Print.
      The Performance Index (PI), a widely used composite measure of vehicular stops and delays, is one of the most popular traffic signal performance measures. Over the decades it has been used to achieve a proper balance between delays and stops. Its key component, the “stop penalty,” has been used to minimize excess fuel consumption from unnecessary stops caused by traffic control operations. In signal optimization practice this stop penalty, also known as the K factor, has been set as an invariable parameter with a relatively low value ∼10 to 20. This paper questions this widely accepted practice. It first explains the origins and meaning of the PI and the significance of the K factor. Then, it lists various studies, discusses their inconsistencies, and introduces a new Fuel Consumption Intersection Control PI (FCIC-PI). The paper also presents findings from field data collection and compares them with the other studies, including some simulation results. Outcomes of these various findings show some inconsistencies, but all point to the existing practice being wrong: the K factor is a variable dependent on at least one important factor—cruising speed. The outcomes also indicate that K values should, if fuel consumption is to be minimized, be larger than currently used. Future research should confirm these findings with a larger field data set, investigate other factors that affect the stop penalty, and consider a family of other emission-related PIs. Finally, a new methodology should be developed to properly integrate these new PIs into signal timing optimization.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:55:38Z
      DOI: 10.1177/03611981211004181
       
  • Operational Feasibility Assessment of Battery Electric Construction
           Equipment Based on In-Use Activity Data
    • Authors: Fuad Un-Noor, George Scora, Guoyuan Wu, Kanok Boriboonsomsin, Harikishan Perugu, Sonya Collier, Seungju Yoon
      Abstract: Transportation Research Record, Ahead of Print.
      Despite the significant progress in on-road vehicle electrification, the majority of construction equipment types are still using conventional diesel engines. Though there has been a steady flow of studies in this field, not all equipment types have yet been evaluated. This paper contributes to filling that data gap by analyzing real-world second-by-second activity data from 17 off-road vehicles across six equipment types to investigate their electrification potential. The collected data are used to determine real-world power and torque demands—which are then used to select currently available electric motors suited for electrification of these types of equipment. Required battery sizes for battery electric operation are also calculated considering recorded energy demands, and battery sizes are standardized across equipment types for realistic implementation. The resulting battery electric systems are simulated to determine their effectiveness in fulfilling real-world activity demands. The results show that four of the six types can be electrified to a significant extent using battery electric powertrains with a single-motor set-up, while the remaining two types are more suitable for hybridization because of their high energy needs.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:55:17Z
      DOI: 10.1177/03611981211004581
       
  • New Turner-Fairbank Alkali-Silica Reaction Susceptibility Test for
           Aggregate Evaluation
    • Authors: Jose F. Muñoz, Chandni Balachandran, Terence S. Arnold
      Abstract: Transportation Research Record, Ahead of Print.
      The ASTM C1260 and ASTM C1293 are generally accepted as being the best available accelerated tests to evaluate the alkali-silica reactivity of aggregates used in concrete. Unfortunately, these tests have limitations, such as the significant amount of false-positive and false-negative results in ASTM C1260 and the alkali leaching in ASTM C1293, that reduce their accuracy. This paper introduces an alternative test method, the Turner-Fairbank alkali-silica reaction (ASR) susceptibility test (T-FAST) that overcomes traditional limitations of both ASTM standards. In the new test, the ASR was accelerated by exposing the aggregates to a 1 N NaOH solution, three different amounts of CaO, and two temperatures for 21 days. The reactivity index (RI), calculated based on the 21-day concentrations of aluminum, calcium, and silicon in liquid phase, was used to assess the alkali-silica reactivity of 24 well-known aggregates—17 coarse and 7 fine. The results agreed with the classification of the same based on ASTM C1293 and historic field performance available in the literature. The alkali levels at which the ASR reaction was triggered in a selection of aggregates were measured using the T-FAST experimental set up. The threshold alkali values obtained matched those previously reported using accelerated concrete expansion tests as well as with concrete blocks in outdoor exposure sites. The alkali threshold determined for a river sand from Arkansas helped to understand the unexpected ASR distress observed in the field for an aggregate traditionally categorized as nonreactive. This case is a good example of mismatch between the information obtained from accelerated-ASR standard tests and field performance.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:54:58Z
      DOI: 10.1177/03611981211004584
       
  • Transportation Barriers among Immigrant Women Experiencing Intimate
           Partner Violence
    • Authors: Shamsun Nahar, Courtney Cronley
      Abstract: Transportation Research Record, Ahead of Print.
      The current study reports on transportation barriers among a transportation-underserved and under-recognized population—immigrant women who are survivors of intimate partner violence (IPV). Using an exploratory cross-sectional qualitative method, two focus groups were conducted with a total of 15 immigrant IPV survivors (25–68 years old) in North Texas, U.S. Three key themes highlight the essence of the transportation barriers among the participants: (1) “my mobility was in my ex-husband’s hand,” (2) transportation disadvantage blocks independence, and (3) public transit in/accessibility undercuts the move toward independence. The study found that transportation is used as a means of control and coercion among IPV perpetrators, and insufficient and inconsistent access to this basic resource impedes the process of exiting IPV situations and regaining independence and stability. The women described that their perpetrators denied them access to the family car or prevented them from going to work. On exiting IPV relationships, the women desired flexible and on-demand transportation whenever possible, and reported concerns with safety, flexibility, and reliability in public transit. First- and last-mile obstacles proved difficult, particularly given that the women had recently relocated to IPV shelters intentionally located in discrete neighborhoods away from their normal travel routes and less proximal to public transit stations. Findings highlight the need for transportation planners and engineers to consider more multi-modal and creative transportation solutions for such populations to overcome first/last-mile accessibility, increase flexibility, and enhance perceived safety in ridership.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:53:51Z
      DOI: 10.1177/03611981211004587
       
  • Signal Stability and the Height-Correction Method for Ground-Penetrating
           Radar In Situ Asphalt Concrete Density Prediction
    • Authors: Qingqing Cao, Imad L. Al-Qadi
      Abstract: Transportation Research Record, Ahead of Print.
      Ground-penetrating radar (GPR) has shown great potential for asphalt concrete density prediction used in quality control and quality assurance. One challenge of continuous GPR measurements is that the measured dielectric constant could be affected by signal stability and antenna height. This would jeopardize the accuracy of the asphalt concrete density prediction along the pavement. In this study, signal instability and shifting antenna height during continuous real-time GPR measurements were identified as main sources of error. After using a bandpass filter to preprocess the signal, a least-square adaptive filter, using gradient descent and least mean square methods, was developed to reconstruct the received signal to improve its stability. In addition, simulations were performed to evaluate the impact of geometric spreading caused by shifting antenna height during testing. A height correction was developed using a power model to correct the height-change impact. The proposed filter and height-correction method were assessed using static and dynamic tests. The least-square adaptive filter improved signal stability by 50% and the height-correction method removed the effect of shifting antenna height almost entirely.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:53:37Z
      DOI: 10.1177/03611981211004585
       
  • Optimization of Takeoff Departure Procedures for Airport Noise Mitigation
    • Authors: Ameya Behere, Dimitri N. Mavris
      Abstract: Transportation Research Record, Ahead of Print.
      The environmental effects of aviation, particularly community noise exposure, is one of the major barriers to a sustainable growth in passenger air traffic. With an increasing number of aircraft operations and growing urban population, several major airports around the world have implemented various noise mitigation strategies. One such mitigation strategy is to optimize the departure procedures utilized by aircraft for performing takeoff operations. Present-day noise abatement departure procedures are developed by airlines under the guidance of the International Civil Aviation Organization and regulatory entities such as the Federal Aviation Administration. These procedures are generally limited to two per aircraft type and are therefore developed for averaged flight conditions. A generic methodology has been developed here which accounts for external parameters, such as the elevation and weather conditions at the departure airport, and aims to design optimal departure procedures per set of external conditions. By retaining these variables in the procedure design process, their influence on various metrics of interest can be studied. A case study is performed using three different airports each at a standard day and a hot day weather condition. Noise metrics are evaluated at four locations relative to the runway. Fuel consumption is also calculated to account for airline operating costs. The results show that the optimality of a procedure is sensitive on both external factors, as well as metrics being evaluated. While some noise metrics require a tradeoff with fuel consumption over a set of pareto optimal solutions, at certain locations, the two are optimized simultaneously by a single procedure.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:53:24Z
      DOI: 10.1177/03611981211004967
       
  • Cost Escalation in Road Construction Contracts
    • Authors: Morten Welde, Roy Endre Dahl
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a study of cost escalation in unit price road construction contracts. The aim is to investigate why the final cost of contracts differs from the agreed contract cost following tendering, both to identify causes of observed discrepancies and to suggest measures that could improve the planning and delivery of future projects. Road projects often consist of several contracts and as they account for the biggest costs of the projects, cost escalation in the contracts may increase the risk of project cost overrun. Even if contract cost performance is an important indicator of project success, it may be too simplistic to equate this with project success. It is quite possible to deliver a project within budget even if contract costs escalate, as long as the project cost contingency is adequate to cover such escalations. However, escalations in contracts increase the risk of project overrun and may lead to other problems such as conflicts and delays. The results show that most of the studied contracts experienced cost escalation. The main cause of the escalation was change orders to the scope that were not covered by the original contract. In addition, the results indicate that complexity represented by contract size, duration, and urban location increases the risk and size of cost overrun. Based on these findings, the paper presents some recommendations on how contract delivery can be improved as well as some implications for future research.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:53:08Z
      DOI: 10.1177/03611981211005462
       
  • Impacts of Bike Sharing Program on Subway Ridership in New York City
    • Authors: Md Tanvir Ashraf, Md Amdad Hossen, Kakan Dey, Sarah El-Dabaja, Moathe Aljeri, Bhaven Naik
      Abstract: Transportation Research Record, Ahead of Print.
      Bike sharing programs have become increasingly popular in many cities. These services allow users to rent bikes for utilitarian and recreational trips in the urban area. Bike sharing has been considered a suitable mode to support the first- and last-mile connectivity problems of fixed-route transit services. Bike sharing has also emerged as a convenient mode for short-distance trips that previously would not have been possible without using public transit or personal bikes. This study investigated the impacts of Citi Bike—a bike sharing program—on the subway ridership in New York City (NYC), using Poisson-Gamma models. Bike sharing trips with destinations within a quarter-mile radius of a subway station were associated with subway ridership increase. A 10% increase in the number of bike trips increased the average daily subway ridership by 2.3%. However, a higher number of bike stations around a subway station decreased the subway ridership in instances where more bike trips originated (as opposed to ended) in the subway station’s service area. The presence of dedicated bike lanes and bike racks attracted more bike users and increased subway ridership. Findings from this study indicate that the development of bike-friendly infrastructure such as activities outlined in the recent NYC Department of Transport (DOT) “Green Wave” program can increase both bike sharing and subway ridership. In addition, policies and initiatives by transportation agencies to better integrate bike sharing programs with the transit system have the potential to increase the attractiveness of bike sharing programs and maximize the subway ridership.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:52:38Z
      DOI: 10.1177/03611981211004980
       
  • Development of a Novel Convolutional Neural Network Architecture Named
           RoadweatherNet for Trajectory-Level Weather Detection using SHRP2
           Naturalistic Driving Data
    • Authors: Md Nasim Khan, Mohamed M. Ahmed
      Abstract: Transportation Research Record, Ahead of Print.
      Driver performances could be significantly impaired in adverse weather because of poor visibility and slippery roadways. Therefore, providing drivers with accurate weather information in real time is vital for safe driving. The state-of-practice of collecting roadway weather information is based on weather stations, which are expensive and cannot provide trajectory-level weather information. Therefore, the primary objective of this study was to develop an affordable detection system capable of providing trajectory-level weather information at the road surface level in real-time. This study utilized the Strategic Highway Research Program 2 Naturalistic Driving Study video data combined with a promising machine learning technique, called convolutional neural network (CNN), to develop a weather detection model with seven weather categories: clear, light rain, heavy rain, light snow, heavy snow, distant fog, and near fog. A novel CNN architecture, named RoadweatherNet, was carefully crafted to achieve the weather detection task. The evaluation results based on a test dataset revealed that RoadweatherNet can provide excellent performance in detecting weather conditions with an overall accuracy of 93%. The performance of RoadweatherNet was also compared with six pre-trained CNN models, namely, AlexNet, ResNet18, ResNet50, GoogLeNet, ShuffleNet, and SqueezeNet, which showed that RoadweatherNet can provide nearly identical performance with a significant reduction in training time. The proposed weather detection model is cost-efficient and requires less computational power; therefore, it can be made widely available mainly owing to the recent thriving of smartphone cameras and can be used to expand and update the current weather-based variable speed limit systems.
      Citation: Transportation Research Record
      PubDate: 2021-04-03T06:48:58Z
      DOI: 10.1177/03611981211005470
       
  • Auditory Alerts and Safety with Simulated Bicycles and Motor Vehicles
    • Authors: Curtis M. Craig, Nichole L. Morris, Jacob D. Achtemeier, Katelyn R. Schwieters
      Abstract: Transportation Research Record, Ahead of Print.
      Bicycling has become an increasingly popular and environmentally friendly active transportation modality for many commuters across the nation. Consequently, as ridership increases so does the rate of bicycle–motor vehicle crashes, many of which are caused by reduced bicycle visibility and driver inattention. Therefore, one effective solution to improve bicyclist safety may be through the use of an audible bicycle alarm system to alert both the driver and the rider. A study was conducted to determine whether a unique auditory alert would be effective at reducing crash rates and whether a localized alert (i.e., an alert presented from the driver’s perspective) would improve the driver’s responsiveness in avoiding a potential collision. A driving simulator study tested car horn sounds, an experimental bike alert, and no auditory alert in different potential collision scenarios to measure collision rates and other collision avoidance metrics. Findings indicated that the experimental bike alert contributed to fewer relative crashes than the horn sound and no sound on bicycles, motor vehicles were struck more frequently than bicycles, collisions were more likely to occur from the front than the sides, and collisions were more likely for drivers going straight than when making turns. Taken together, the findings suggest that an alarm designed to be specifically compatible with bicycles is more effective than auditory alerts from other sources.
      Citation: Transportation Research Record
      PubDate: 2021-04-02T07:54:45Z
      DOI: 10.1177/03611981211002531
       
  • Evaluating Pedestrian Crash-Prone Locations to Formulate Policy
           Interventions for Improved Safety and Walkability at Sidewalks and
           Crosswalks
    • Authors: Mallikarjun Patil, Bandhan Bandhu Majumdar, Prasanta K. Sahu
      Abstract: Transportation Research Record, Ahead of Print.
      This study presents a methodology for evaluating a set of crash-prone sidewalk and crosswalk locations in an urban area with respect to their existing walkability condition and recommending improvement needs. Initially, a set of 15 sidewalk specific and 10 crosswalk specific attributes relevant to India were identified from the literature. Subsequently, the analytical hierarchy process was used to estimate relative weights associated with the attributes from the perspective of relevant experts. A weighted sum method was then used to formulate a Sidewalk Condition Index (SCI) and Crosswalk Condition Index (CCI) for evaluating the condition of the existing pedestrian sidewalks and crosswalk infrastructures. Ten locations across Hyderabad with the highest pedestrian fatalities during the last three calendar years were selected as study locations. The location specific SCI and CCI estimates were used to prioritize the locations with regard to their existing condition and infrastructural requirements. Results indicated that sidewalk attributes such as sidewalk lighting, cleanliness, physical separation of traffic, and traffic speed, and crosswalk attributes such as conflicts with crossing traffic, crosswalk illumination, and intersection control, influenced safety and walkability significantly. Measures such as the provision of exclusive right-of-way for pedestrians, maintaining the sidewalk quality, enforcing no jaywalking, re-design of signal timing with pedestrian phase, and provision of zebra crossings and refuge islands, would improve walkability at pedestrian crash-prone locations across Hyderabad. This proposed methodology and the research findings could act as a critical tool to improve the overall safety and walkability of sidewalks and crosswalks in Indian cities.
      Citation: Transportation Research Record
      PubDate: 2021-04-02T07:54:23Z
      DOI: 10.1177/03611981211004127
       
  • Systematic Review of Research on Driver Distraction in the Context of
           Advanced Driver Assistance Systems
    • Authors: Apoorva P. Hungund, Ganesh Pai, Anuj K. Pradhan
      Abstract: Transportation Research Record, Ahead of Print.
      Advanced driver assistance systems (ADAS) promise improved driving performance and safety. With ADAS taking on more vehicle control tasks, the driver’s role may be reduced to that of passive supervision. This in turn may increase drivers’ engagement in non-driving-related tasks, thereby potentially reducing any promised safety benefit. We conducted a systematic review, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, to study the relationship between ADAS use and driver distraction. Four research questions were addressed—two questions examined the effect of ADAS on secondary task engagement, and the quality of secondary task performance, and two addressed the effects of ADAS on driver attention and on driver behavior changes caused by secondary task engagement. Twenty-nine papers were selected for full text synthesis. The majority of the papers indicate an association between ADAS and increased secondary task engagement, as well as improved secondary task performance. Ten papers reported that drivers tend to divert their attention to secondary tasks and away from driving tasks. These outcomes highlight the continued importance of the role of the human driver despite vehicle automation, especially in the context of driver distraction, and that user understanding of ADAS functionalities and limitations is essential to appropriate and effective use of these systems.
      Citation: Transportation Research Record
      PubDate: 2021-04-02T07:54:03Z
      DOI: 10.1177/03611981211004129
       
  • Prototype Design of Cement/Emulsified Asphalt Based Piezoelectric
           Composites and its Potential Application in Vehicle Speed Sensing
    • Authors: Xingyi Zhu, Xudong Zhou, Fangyong Ye, Zhao Du
      Abstract: Transportation Research Record, Ahead of Print.
      Piezoelectric composites (PC) embedded in pavement have shown great potential in traffic information sensing. As the main form of transportation, the road is the source of much traffic information including vehicle load information. The research into PC can supplement the collection of traffic information used in the development of intelligent technologies and provide effective solutions to problems existing in the process of information gathering. In this study, a 2-2 cement/emulsified asphalt-based PC was prepared with the cutting-filling method. To optimize the PC preparation, the effects of the volume fraction of the piezoelectric phase and the matrix phase composition on the piezoelectric properties of the PC were investigated by employing the finite element method. The results indicated that the smaller the volume fraction of the piezoelectric phase, the higher the voltage output of the PC, and the higher the sensitivity to external load, but the greater the stress concentration at the interface between the piezoelectric phase and the matrix phase. In addition, the greater the amount of emulsified asphalt in the matrix phase, the higher the voltage output of the PC. However, a higher content of emulsified asphalt will undermine the fluidity of the matrix phase. Based on the simulation analysis, performance optimization of the cement/emulsified asphalt PC was achieved. According to the voltage output characteristic of PC under a moving load, a placement scheme of PCs in the asphalt pavement was also proposed, which enables vehicle speeds to be be sensed with high precision.
      Citation: Transportation Research Record
      PubDate: 2021-04-02T07:53:43Z
      DOI: 10.1177/03611981211004580
       
  • Systematic Safety Evaluation of Diverging Diamond Interchanges Based on
           Nationwide Implementation Data
    • Authors: Ahmed Abdelrahman, Mohamed Abdel-Aty, Jinghui Yuan, Ma’en M. A. Al-Omari
      Abstract: Transportation Research Record, Ahead of Print.
      Diverging diamond interchanges (DDIs) are designed as an alternative to the conventional diamond interchanges to enhance operational and safety performance. As the popularity of the DDI is increasing and more DDIs are being constructed and proposed, the need has arisen to measure the actual safety benefits of DDIs as compared with the traditional diamond interchanges. This study evaluates the safety of DDIs using three methods: before–after study with comparison group, Empirical Bayes before–after method, and cross-sectional analysis. This study collected a nationwide sample of 80 DDIs in 24 states. The estimated crash modification factors indicated that converting conventional diamond interchange to DDIs could significantly decrease the total, fatal-and-injury, rear-end, and angle/left-turn crashes by 14%, 44%, 11%, and 55%, respectively. Moreover, the developed safety performance functions implied that a longer distance between crossovers/ramp terminals and a lower speed limit on freeway exit ramps are significantly associated with lower crash frequency at diamond interchanges. This study contributes to the existing literature using a relatively large representative sample size, which provides more reliable evaluation results. In addition, this study also explored the effects of different traffic and geometric characteristics on the safety performance of DDIs.
      Citation: Transportation Research Record
      PubDate: 2021-04-02T07:53:23Z
      DOI: 10.1177/03611981211004961
       
  • Use of Time–Temperature Superposition Principle to Create Pavement
           Performance Master Curves and Relate Pavement Condition Index and
           International Roughness Index
    • Authors: Jose R. Medina, Ali Zalghout, Akshay Gundla, Samuel Castro, Kamil Kaloush
      Abstract: Transportation Research Record, Ahead of Print.
      The international roughness index (IRI) is one of the most popular indices to measure pavement roughness. State agencies and cities with plenty of resources often collect IRI and pavement distresses every year or every other year, but some others with fewer resources will collect this information every 3 to 5 years. Collecting IRI is much more affordable than collecting pavement distresses. With this in mind, the objective of this paper was to establish a relationship between IRI and pavement condition index (PCI) using pavement deterioration models for both PCI and IRI based on the concept of time–deterioration superposition similar to the time–temperature superposition principle, and then combine both models to establish this relationship. Additionally, this study was used to establish threshold limits for IRI measurements that can be used as a general reference for pavement condition. Data from the Long-Term Pavement Performance InfoPave was used to perform the analysis for three network samples from Arizona, California, and Wisconsin. This analysis only included flexible pavements. The results from Arizona, California, and Wisconsin showed a good relationship between IRI and PCI using the proposed approach with a coefficient of determination ranging from 0.71 to 0.85. Furthermore, the analysis showed that the change in IRI over time can be related to the change in PCI over time. The general thresholds developed in this study apply to the sections evaluated but the approach can be used to set limits for other networks.
      Citation: Transportation Research Record
      PubDate: 2021-04-02T07:51:04Z
      DOI: 10.1177/03611981211004965
       
  • Progressive Development of the Perched Water Zone in Highway Slopes Made
           of Highly Plastic Clay
    • Authors: Masoud Nobahar, Mohammad Sadik Khan, Mike Stroud, Farshad Amini, John Ivoke
      Abstract: Transportation Research Record, Ahead of Print.
      Based on National Oceanic and Atmospheric Administration data, after Hawaii and Louisiana, Mississippi is the rainiest state in the United States, having the most peak precipitation that occurs mainly in late winter. Development of perched water (DPW) has had a remarkable effect on the service life of highway slopes constructed on expansive clay. The objective of the current study is to map the DPW condition at highway slopes made of highly plastic clay (HPC) in Mississippi. Several highway slopes that are made of HPC in Jackson, MS, were instrumented using moisture sensors, water potential probes, and rain gauges. Based on the field investigations, it has been observed that a perched water condition exists in all the slopes constructed of Yazoo clay. To investigate the DPW condition and map the accumulation of the water within the slopes, a series of flow analyses have been conducted using the finite element method in Plaxis. The flow analysis is conducted considering the shrink/swell behavior of the Yazoo clay with the real-time rainfall events, as observed in the rain gauges. The numerical analysis was in good agreement with field monitoring results. Based on the analysis, it is observed that rainwater accumulated during the summer to fall season because of a high infiltration rate with the presence of desiccation cracks. On the other hand, the low permeability situation during the spring held the percolated water within the slopes. Repeated events of infiltration and water hold-up condition progressively develop the perched water zone in the slopes made of Yazoo clay.
      Citation: Transportation Research Record
      PubDate: 2021-03-31T12:43:21Z
      DOI: 10.1177/03611981211004178
       
  • Learnings from the Field Implementation of a Novel Ultra-High Performance
           
    • Authors: Alexandra Hain, Arash E. Zaghi
      Abstract: Transportation Research Record, Ahead of Print.
      Corrosion at steel beam ends is one of the most pressing challenges in the maintenance of aging bridges. To tackle this challenge, the Connecticut Department of Transportation (DOT) has partnered with the University of Connecticut to develop a repair method that benefits from the superior mechanical and durability characteristics of ultra-high performance concrete (UHPC) material. The repair involves welding shear studs to the intact portions of the web and encasing the beam end with UHPC. This provides an alternate load path for bearing forces that bypasses the corroded regions of the beam. The structural viability of the repair has been extensively proven through small- and full-scale experiments and comprehensive finite element simulations. Connecticut DOT implemented the repair for the first time in the field on a heavily trafficked four-span bridge in 2019. The UHPC beam end repair was chosen because of the access constraints and geometric complexities of the bridge that limited the viable repair options. Four of the repaired beam ends were fully instrumented to collect data on the performance of the repaired locations before casting, during curing, and for approximately 6 months following the application of the repair. This paper provides an overview of the successful repair implementation and presents the lessons learned during construction. Select data from the monitored beam ends are presented. It is expected that this information will provide engineers with a better understanding of the repair implementation process, and thus provide an additional repair option for states to enhance the safety of aging steel bridges.
      Citation: Transportation Research Record
      PubDate: 2021-03-31T12:41:41Z
      DOI: 10.1177/03611981211004128
       
  • Empirical Study of the Impacts of Bicycles on Passenger Car Speeds on
           Urban Roads without Bicycle Lanes
    • Authors: Jaclyn S. Schaefer, Miguel A. Figliozzi, Avinash Unnikrishnan
      Abstract: Transportation Research Record, Ahead of Print.
      Higher bicycle mode share has been suggested as part of a solution to reduce the burden of congestion in urban areas. As strategies to promote cycling are implemented, concerns have been raised by some road users and stakeholders citing simulation-based traffic studies that indicate that an increase in the bicycle mode share generates major travel time delays via reduced vehicle speeds unless bicycle lanes are provided. The current research investigates the effects bicycles may have on motorized vehicle speeds on a variety of lower speed and volume urban roads without bicycle lanes. A detailed comparative analysis of passenger car speeds was performed using two vehicle scenarios: (i) a passenger car that was preceded by a bicycle; and (ii) a passenger car that was preceded by another passenger car. The mean and 85th percentile speeds of scenarios (i) and (ii) were analyzed using t-tests. Relationships between speed and gap times with oncoming (opposite direction) traffic were also investigated. The results indicate that, at most sites (92%), bicycles do not reduce passenger car mean speeds by more than 1 mph. Speed reductions are not generally observed in local streets or facilities with adequate gaps in oncoming traffic for overtaking.
      Citation: Transportation Research Record
      PubDate: 2021-03-31T12:40:01Z
      DOI: 10.1177/03611981211004122
       
  • Rational Basis for Light Emitting Diode Street Lighting Retrofit Luminaire
           Selection
    • Authors: Jennifer A. Brons, John D. Bullough, Daniel C. Frering
      Abstract: Transportation Research Record, Ahead of Print.
      Many municipalities are beginning to undertake efforts to retrofit their existing high pressure sodium (HPS) street lighting with LED (light emitting diode) luminaires. Unlike HPS lighting systems, which are available in a limited range of standard wattages and configurations, LED street lighting systems vary widely in wattage and physical configuration. Moreover, the technological performance of LED lighting continues to improve, whereas HPS is a mature technology with substantial improvements unlikely in the future. To develop a sound basis for selecting LED lighting systems for retrofit street lighting, photometric simulation calculations under a range of pole spacing, road width and luminaire wattage were performed. The results indicated that LED luminaires can have substantially lower wattage than HPS luminaires to produce the same light levels on the road. Further, LED luminaires tend to direct more of their output onto the road compared with HPS luminaires. As a result, LED luminaires can be used that produce substantially fewer lumens overall than HPS systems. Because the white light from LED sources makes illuminated street scenes appear brighter than the yellowish light from HPS lamps, even further reductions in light output can be accomplished with LED street lighting systems to match the same visual effect under HPS.
      Citation: Transportation Research Record
      PubDate: 2021-03-31T12:38:41Z
      DOI: 10.1177/03611981211003890
       
  • Performance Evaluation of Different Insulating Materials using Field
           Temperature and Moisture Data
    • Authors: Yunyan Huang, Mohamad Molavi Nojumi, Leila Hashemian, Alireza Bayat
      Abstract: Transportation Research Record, Ahead of Print.
      Including insulation layers in pavement structures has become a common strategy to minimize frost penetration in cold regions. This study investigated the performance of two different insulation materials, extruded polystyrene board and bottom ash, in a test road in Edmonton, Alberta, Canada, eight years after construction. The two insulation materials were used in a fully instrumented test road, including three insulated sections 20 m in length. The insulated sections are as follows: the first section has 1 m of bottom ash (B. Ash), the second section has a 10 cm polystyrene layer (Poly-10), and the third section has a 5 cm polystyrene layer (Poly-5). Both B. Ash and polystyrene layers were placed on top of the subgrade layer, at a depth of 70 cm from the surface. A conventional section next to these three sections was used as the control section. Volumetric water content data and temperature variation were used to analyze the influence of the insulation materials on the subgrade. It was concluded that both B. Ash and Poly-10 layers protected the subgrade from freezing. The Poly-10 section showed the lowest rate of change in subgrade temperature during the monitoring period. B. Ash and Poly-10 reduced the frost depth by 23% and 70% compared with the control section, respectively. It was concluded that Poly-10 protected the subgrade soil from freezing and excessive moisture more effectively than B. Ash; however, the temperature in the layer above the insulation layers (pavement base layer) was significantly lower during winter for the Poly-10 section.
      Citation: Transportation Research Record
      PubDate: 2021-03-31T12:37:40Z
      DOI: 10.1177/03611981211003572
       
  • Extraction of Construction Quality Requirements from Textual
           Specifications via Natural Language Processing
    • Authors: JungHo Jeon, Xin Xu, Yuxi Zhang, Liu Yang, Hubo Cai
      Abstract: Transportation Research Record, Ahead of Print.
      Construction inspection is an essential component of the quality assurance programs of state transportation agencies (STAs), and the guidelines for this process reside in lengthy textual specifications. In the current practice, engineers and inspectors must manually go through these documents to plan, conduct, and document their inspections, which is time-consuming, very subjective, inconsistent, and prone to error. A promising alternative to this manual process is the application of natural language processing (NLP) techniques (e.g., text parsing, sentence classification, and syntactic analysis) to automatically extract construction inspection requirements from textual documents and present them as straightforward check questions. This paper introduces an NLP-based method that: 1) extracts individual sentences from the construction specification; 2) preprocesses the resulting sentences; 3) applies Word2Vec and GloVe algorithms to extract vector features; 4) uses a convolutional neural network (CNN) and recurrent neural network to classify sentences; and 5) converts the requirement sentences into check questions via syntactic analysis. The overall methodology was assessed using the Indiana Department of Transportation (DOT) specification as a test case. Our results revealed that the CNN + GloVe combination led to the highest accuracy, at 91.9%, and the lowest loss, at 11.7%. To further validate its use across STAs nationwide, we applied it to the construction specification of the South Carolina DOT as a test case, and our average accuracy was 92.6%.
      Citation: Transportation Research Record
      PubDate: 2021-03-31T05:27:36Z
      DOI: 10.1177/03611981211001385
       
  • Emission Implications of Plug-in Hybrid Electric Vehicles Through an
           Empirical Exploration of Engine Starts
    • Authors: Vaishnavi Chaitanya Karanam, Gil Tal
      Abstract: Transportation Research Record, Ahead of Print.
      This paper aims to characterize the engine start activity profiles and emission potential of various plug-in hybrid electric vehicle (PHEV) models by examining the characteristics associated with engine starts, identifying the travel conditions that trigger engine starts, and determining the frequency of different types of engine starts. The study analyzed on-road vehicle data from six PHEV models: Toyota Prius Plug-in, Ford C-Max Energi, Ford C-Max Fusion, Toyota Prius Prime, Chrysler Pacifica, and Chevrolet Volt. An analysis on travel conditions before engine starts revealed that low state-of-charge is the dominant engine start trigger for PHEVs with high all-electric range whereas high vehicle power requirement is the most critical trigger for PHEVs with low all-electric range. For PHEVs with mid-range capabilities, several vehicle specifications, ranging from peak electric motor power to curb weight, could be engine start determinants. A strong inverse correlation exists between battery capacity and the annual frequency of engine starts but this relationship does not hold for cold and high-power cold starts. Both the low and the high battery capacity PHEVs logged fewer cold starts than the mid-sized battery vehicles, indicating that there could be a fundamental tradeoff between engine start emissions and fuel displacement for PHEVs to a certain degree. Despite this tradeoff, all PHEV models in the study logged fewer cold starts than comparable conventional internal combustion engine vehicles, performing the same trips. Ultimately, long-range PHEVs with high battery capacity are found to be ideal for both curbing start emissions and reducing fuel use.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T11:05:57Z
      DOI: 10.1177/03611981211003895
       
  • Spatio-Temporal Influence of Extreme Weather on a Taxi Market
    • Authors: R. C. P. Wong, P. L. Mak, W. Y. Szeto, W. H. Yang
      Abstract: Transportation Research Record, Ahead of Print.
      Extreme weather conditions, strong gusts, and torrential rainfall threaten the safety of the general public and restrict people’s travel options. Most of the transportation modes are suspended because of safety reasons. Taxis are one of the only few available non-private transport modes to provide services to those who have urgent and unavoidable travel needs. This study uses global positioning system data collected from 460 Hong Kong urban taxis during nine ordinary and one tropical cyclone periods aiming to find out and explain the differences in relation to the percentage of taxis not in operation, the number of served passenger-trips, average time spent by vacant-taxi drivers finding a customer, and the percentage of taxi drivers in cross-district customer-search throughout the same 48 h duration. The findings show an inadequate level of taxi supply and a high passenger demand during the tropical-cyclone-affected period. Up to 80% of taxis were not in operation to serve the urgent and necessary trips. The average customer-search time for taxi drivers, which is anticipated inversely proportional to the demand for taxi rides, was very short (about 5 min). Policy measures are discussed and recommended to the government to improve the taxi services during extreme weather conditions.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:56:51Z
      DOI: 10.1177/03611981211003894
       
  • Examining Freeway Bottleneck Features During a Mass Evacuation
    • Authors: Brian M. Staes, Robert L. Bertini, Nikhil Menon, Eren Yuksel
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic features were investigated for a bottleneck that was observed on a 30 mi northbound section of Florida’s Turnpike (SR-91) during the mass evacuation in advance of Hurricane Irma that occurred in September 2017. Radar detector data (at 1 min intervals) from the Regional Integrated Transportation Information System were utilized to determine the periods when a bottleneck was active adjacent to a service plaza along the roadway. Three distinct time periods were identified during which a bottleneck was active at the service plaza off-ramp, for a total of 27.5 h during the evacuation period. To identify and confirm each bottleneck activation and duration, and to measure the traffic flow features that characterized the bottleneck, curves of cumulative vehicle count and occupancy were utilized. Analysis of these curves revealed time periods during which excess vehicle accumulation and delay occurred between successive detector stations along the Turnpike. Results demonstrate distinct queued and free flowing traffic states between adjacent detectors in the vicinity of an off-ramp into a service plaza. The apparent bottleneck discharge features presented substantially lower flows than what would be expected for a limited access facility with high operational speeds. Findings from this paper present important considerations for evacuation planning and modeling as roadway traffic features may only present themselves during evacuations and if not accounted for may drastically reduce the precision of models and simulations.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:54:49Z
      DOI: 10.1177/03611981211003588
       
  • Machine Learning Approach for Predicting Lane-Change Maneuvers using the
           SHRP2 Naturalistic Driving Study Data
    • Authors: Anik Das, Mohamed M. Ahmed
      Abstract: Transportation Research Record, Ahead of Print.
      Accurate lane-change prediction information in real time is essential to safely operate Autonomous Vehicles (AVs) on the roadways, especially at the early stage of AVs deployment, where there will be an interaction between AVs and human-driven vehicles. This study proposed reliable lane-change prediction models considering features from vehicle kinematics, machine vision, driver, and roadway geometric characteristics using the trajectory-level SHRP2 Naturalistic Driving Study and Roadway Information Database. Several machine learning algorithms were trained, validated, tested, and comparatively analyzed including, Classification And Regression Trees (CART), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), Support Vector Machine (SVM), K Nearest Neighbor (KNN), and Naïve Bayes (NB) based on six different sets of features. In each feature set, relevant features were extracted through a wrapper-based algorithm named Boruta. The results showed that the XGBoost model outperformed all other models in relation to its highest overall prediction accuracy (97%) and F1-score (95.5%) considering all features. However, the highest overall prediction accuracy of 97.3% and F1-score of 95.9% were observed in the XGBoost model based on vehicle kinematics features. Moreover, it was found that XGBoost was the only model that achieved a reliable and balanced prediction performance across all six feature sets. Furthermore, a simplified XGBoost model was developed for each feature set considering the practical implementation of the model. The proposed prediction model could help in trajectory planning for AVs and could be used to develop more reliable advanced driver assistance systems (ADAS) in a cooperative connected and automated vehicle environment.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:49:09Z
      DOI: 10.1177/03611981211003581
       
  • Understanding Urban Commercial Vehicle Driver Behaviors and Decision
           Making
    • Authors: Giacomo Dalla Chiara, Klaas Fiete Krutein, Andisheh Ranjbari, Anne Goodchild
      Abstract: Transportation Research Record, Ahead of Print.
      As e-commerce and urban deliveries spike, cities grapple with managing urban freight more actively. To manage urban deliveries effectively, city planners and policy makers need to better understand driver behaviors and the challenges they experience in making deliveries. In this study, we collected data on commercial vehicle (CV) driver behaviors by performing ridealongs with various logistics carriers. Ridealongs were performed in Seattle, Washington, covering a range of vehicles (cars, vans, and trucks), goods (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail). Observers collected qualitative observations and quantitative data on trip and dwell times, while also tracking vehicles with global positioning system devices. The results showed that, on average, urban CVs spent 80% of their daily operating time parked. The study also found that, unlike the common belief, drivers (especially those operating heavier vehicles) parked in authorized parking locations, with only less than 5% of stops occurring in the travel lane. Dwell times associated with authorized parking locations were significantly longer than those of other parking locations, and mail and heavy goods deliveries generally had longer dwell times. We also identified three main criteria CV drivers used for choosing a parking location: avoiding unsafe maneuvers, minimizing conflicts with other users of the road, and competition with other commercial drivers. The results provide estimates for trip times, dwell times, and parking choice types, as well as insights into why those decisions are made and the factors affecting driver choices.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:44:07Z
      DOI: 10.1177/03611981211003575
       
  • Measuring the Regional Economic Impact of Transportation Access
           Improvements in the Context of a Large Metropolitan Region
    • Authors: Glen Weisbrod, Jenna Goldberg, Parry Frank
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation planners are increasingly recognizing the importance of access in enabling employment growth and better paying job opportunities for residents. Although regional economic impact analysis is often an important element of transportation investment evaluation by state departments of transportation, it can be particularly challenging for metropolitan area planners because existing economic modeling methods do not fully account for the multifaceted roles that transportation links play in affecting access within large, polycentric metropolitan areas. This article examines these issues and presents information from a study of the Chicago region, to evaluate statistical relationships of employment cluster size and wage levels to zonal differences in business-to-business connectivity and population connectivity. It presents elasticities of employment and wage impact associated with various access measures for different sectors of the economy. These findings point to the importance of transportation planners considering the impacts on connectivity to both population markets and employment centers when evaluating the potential economic implications of proposed transportation system improvements in large, polycentric metropolitan areas. The article then lays out directions for future research and practice to improve transportation project evaluation and planning.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:40:25Z
      DOI: 10.1177/03611981211002520
       
  • Performance Comparison of Supply–Demand Matching Policies for
           On-Demand Mobility Services
    • Authors: Zacharie Chebance, Iliya Markov, Rafael Guglielmetti, Marco Laumanns
      Abstract: Transportation Research Record, Ahead of Print.
      In the context of on-demand mobility services, we compare the performance of three matching policies of increasing sophistication on scenarios based on real data from the city of Chicago in the United States. The comparative study examines the influence of prebooking and ridesharing on the gap between the different policies. We find that more sophisticated approaches can improve the acceptance ratio and the service-level key performance indicators at the expense of longer computation times. Prebooking appears to consistently give an edge to more sophisticated policies by providing advance information and thus the flexibility to make better plans. The effect of ridesharing is less straightforward to isolate. But, again, prebooking helps more sophisticated approaches reduce excess ride time, a direct consequence of ridesharing.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:37:45Z
      DOI: 10.1177/03611981211002840
       
  • Review of Methods for Estimating Construction Work Zone Capacity
    • Authors: Ali H. Mashhadi, Mohammad Farhadmanesh, Abbas Rashidi, Nikola Marković
      Abstract: Transportation Research Record, Ahead of Print.
      Road reconstruction and the resulting work zones are considered as a major source of traffic congestion and delays on freeways. The roadway capacity is decreased as a result of a reduced number of traffic lanes, narrower lanes, and work zone speed limits. Accurate prediction of construction work zone capacity helps traffic engineers to have a better estimation of the traffic flow characteristics. To this end, multiple methodologies have been developed to quantify the impacts of work zones on traffic flow. This paper presents a critical review of the three types of approaches to estimating construction work zone capacities, including parametric, non-parametric, and simulation. Then the most commonly considered factors and their frequency are presented. It also performs a detailed review of the approaches, their objectives, and weaknesses. Lastly, it provides recommendations for future research. The presented work could help researchers in the area of work zone capacity estimation by presenting all the previous methodologies in one place.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:34:03Z
      DOI: 10.1177/03611981211002202
       
  • Potential Effectiveness of Bicycle-Automatic Emergency Braking using the
           Washtenaw Area Transportation Study Data Set
    • Authors: Samantha H. Haus, Ryan M. Anderson, Rini Sherony, Hampton C. Gabler
      Abstract: Transportation Research Record, Ahead of Print.
      In the United States, fatalities from vehicle–bicycle crashes have been increasing since 2010. A total of 857 cyclists were struck and killed in 2018 which is an increase from 623 fatalities in 2010. One promising countermeasure is Automatic Emergency Braking (AEB), which can help prevent and/or mitigate many vehicle–bicycle crashes. AEB is a vehicle-based system that can detect and mitigate an impending crash. The goal of this study was to elucidate U.S. vehicle–bicycle crashes and examine related factors to estimate AEB effectiveness. This study used a unique in-depth vehicle–bicycle crash study dataset collected under the collaboration of the Washtenaw Area Transportation Study (WATS) and the Toyota Collaborative Research Center conducted in southeast Michigan from 2011 to 2013. The WATS database provides in-depth investigations of vehicle–bicycle crashes in the United States. The characteristics of the WATS vehicle–bicycle crashes were validated against the Fatality Analysis Reporting System and the General Estimate System. The WATS database cases were examined to estimate the potential effectiveness of AEB to prevent or mitigate vehicle–bicycle collisions. In 60% of the WATS cases, cyclists were in the road for more than 1 s before impact. Assuming that a hypothetical AEB system requires a minimum of 1 s for detection and brake activation, these collisions would potentially be avoided or mitigated. However, for the remaining cases with less than 1 s of time to react (40% of cases), that AEB system would be challenged to avoid or mitigate the collision.
      Citation: Transportation Research Record
      PubDate: 2021-03-30T10:32:24Z
      DOI: 10.1177/03611981211001377
       
  • Hazard-Based Duration Approach to Pedestrian Crossing Behavior at
           Signalized Intersections
    • Authors: Apurwa Dhoke, Abhinav Kumar, Indrajit Ghosh
      Abstract: Transportation Research Record, Ahead of Print.
      With the rapid urbanization of geographical spaces worldwide, pedestrian safety is a major concern on urban roads. In developing economies like India, an unprecedented increase in accidents involving pedestrians has been observed at intersections. The present study focuses on pedestrian behavior, specifically, violation of red signals while crossing at signalized intersections. With the help of hazard-based duration models, the waiting duration of red-light violators has been analyzed. In addition, the response time of pedestrians during conflict has also been modeled with the help of a hazard-based duration approach. Four signalized intersections from Nagpur City in India were selected for the survival analysis. Kaplan–Meier survival curves have been plotted for both waiting time and response time. With the help of the semi-parametric Cox proportional hazard model, various factors have been identified to describe the survival function of the pedestrians’ crossing. However, the model results were found to be unsatisfactory since the explanatory variables failed in the proportional hazard assumption. Therefore, the parametric accelerated failure time model was utilized to determine the various covariates that affected the waiting time and the response time. The Weibull model was found to be the best fit for waiting duration analysis, while the log-logistic model was considered for the study of response time. The developed models can help understand the external factors and personal features of pedestrians in relation to the risk involved during violation crossings.
      Citation: Transportation Research Record
      PubDate: 2021-03-29T12:10:32Z
      DOI: 10.1177/03611981211003102
       
  • Development of Pedestrian Recall Versus Actuation Guidelines for
           Pedestrian Crossings at Signalized Intersections
    • Authors: Burak Cesme, Peter G. Furth, Ryan Casburn, Kevin Lee
      Abstract: Transportation Research Record, Ahead of Print.
      At signalized intersections, pedestrian phases can be configured as recall or pushbutton actuated. While pedestrian recall results in a moderate reduction in pedestrian delay because, with recall, a pedestrian arriving during the time nominally reserved for the Walk interval will be served immediately rather than waiting to be served in the next cycle, it can also lead to longer cycle lengths, increasing delay for all users, including pedestrians. This research explores the impact of pedestrian recall along a coordinated-actuated arterial for pedestrians crossing the mainline (i.e., crossing the coordinated phase) to provide pedestrian recall versus actuation guidelines for agencies. The guidance was developed with the aim of balancing pedestrian delay with operational efficiency for vehicles. Two criteria were considered while developing the guidance: (1) pedestrian demand; and (2) vehicular green time duration for the concurrent vehicle phase that is parallel to the pedestrian crossing. VISSIM microsimulation software was used on a real network in Fairfax County, Virginia to model the effects of pedestrian recall and actuation. Results showed that pedestrian recall should be considered when pedestrian demand is large enough that there is a pedestrian call in most cycles (pedestrian probability in a given cycle is greater than 0.6 or pedestrian volume per cycle is greater than 0.9). The guidance also suggests setting pedestrian phases on recall when the length of the vehicular green for the concurrent phase is long enough in most cycles that a pedestrian phase would fit without constraining the signal cycle length.
      Citation: Transportation Research Record
      PubDate: 2021-03-29T12:09:28Z
      DOI: 10.1177/03611981211002846
       
  • Use of Exclusive and Pooled Ridehailing Services in Three Mexican Cities
    • Authors: Joanna Moody, Enrique Esparza-Villarreal, David Keith
      Abstract: Transportation Research Record, Ahead of Print.
      The global expansion of ridehailing platforms has been accompanied by a diversification of service offerings as platforms fit within new urban contexts. While ridehailing has been of great interest to transportation researchers, analysis of its adoption and use in developing cities that differentiates between service offerings is lacking. To help address this knowledge gap, this study analyzes primary survey data collected from frequent users of the DiDi Chuxing ridehailing platform in three Mexican cities: Mérida, Toluca de Lerdo, and Aguascalientes. It investigates how ridehailing fits into the travel behavior of its users, explicitly differentiating between express (exclusive) and comparte (pooled) services. Findings were that (i) frequent use of ridehailing is positively correlated with use of public transport—city-run and privately-operated buses—and taxi, but negatively correlated with use of private car and motorcycle; and (ii) ridehailing trips are more likely to substitute public transport and taxi trips, but that the mode substitution depends on the service offering, with high substitutability between express and comparte. This degree of substitutability suggests that there is potential to encourage ridehailing users to pool trips, increasing the occupancy rate of ridehailing vehicles and reducing their negative impacts on congestion. Among the many factors involved in choosing between exclusive and pooled services, study participants rated safety, travel time, travel time reliability, and price as key determinants, with a highly elastic relation between travel time and price. These results inform efforts by urban transportation policymakers and ridehailing operators to encourage pooling in the Latin American context.
      Citation: Transportation Research Record
      PubDate: 2021-03-29T12:07:28Z
      DOI: 10.1177/03611981211002835
       
  • Hybrid Machine Learning Algorithm for Identifying Feature Levels
           Associated with Safety Critical Events
    • Authors: Saleh Mousa, Ragab Mousa, Amany Fadaly, Khalid Jamil
      Abstract: Transportation Research Record, Ahead of Print.
      According to the National Highway Traffic Safety Administration (NHTSA), about seven million traffic accidents claimed more than 36,560 human lives in the U.S. in 2018 . These statistics have prompted researchers to investigate the driver characteristics associated with safety-critical events (SCE). This paper presents a hybrid CatBoost algorithm for identifying the feature levels associated with SCE. The model accounts for numerous difficulties and drawbacks reported in the literature. The model was trained and validated using the entire set of the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP2-NDS) events (crash/near-crash and normal/baseline). Results indicate that secondary tasks (interacting with object in-vehicle, reaching for objects in the vehicle, pet interaction, cellphone/tablet use, and writing/texting), intersection influence (parking lots/driveway/entrance/exit, uncontrolled intersections, traffic signals, interchanges, and stop signs), income (under $29,000 and $100,000–$149,000), age (16–19 and 20–24), traffic density (level of service C, D, and E/F), high sensation-seeking tendency (scoring 18–35 on a scale of 35), low driving knowledge (scoring 0–8.9 on a 19-point scoring system questionnaire), and gender = female are the feature levels having an association with SCE with a probability varying between 51% and 87%. Results also revealed that passenger interactions, eating/drinking, driving away from intersections or interchanges, being age 70—79, or driving in traffic density = A are more related to safe driving. Consideration of these results can contribute to reducing roadway crashes and improve traffic safety.
      Citation: Transportation Research Record
      PubDate: 2021-03-29T12:06:07Z
      DOI: 10.1177/0361198121999626
       
  • Using 3D Rule-Based Modeling to Interactively Visualize “Complete
           Streets” Design Scenarios
    • Authors: Ilir Bejleri, Soowoong Noh, Jamie N. Bufkin, Ruchen Zhou, David Wasserman
      Abstract: Transportation Research Record, Ahead of Print.
      “Complete Streets” has successfully emerged, and is increasingly being adopted around the U.S.A., as a transportation policy and design approach that aims to support the needs of all road users. Requiring complex street design configurations, Complete Streets initiatives can benefit from the power of three-dimensional (3D) visualization to share the design vision with stakeholders and citizens. Traditional modeling techniques present some challenges to respond to such needs because of low modeling efficiency. However, 3D procedural modeling, also known as rule-based modeling, provides exciting opportunities to overcome such challenges. This study investigates 3D rule-based modeling as a scenario-oriented street design tool. It employs a case study approach that utilizes a set of rules designed for Complete Streets and applies rule-based modeling to visually compare design scenarios using a study area in Florida. Findings show that the rule-based modeling approach is proven to effectively visualize scenario-oriented street designs. Its ability to modify design parameters easily and generate scenarios rapidly, enables effective visual comparison of alternatives. Its ability to be customized and extended makes it applicable to thousands of communities around the country that are looking to implement Complete Streets designs. Finally, with the ability to support 3D web-based visualization and virtual reality, the rule-based approach can serve as an effective integrated collaboration platform. The Complete Streets rules are available and can be utilized by practitioners immediately. For researchers, the rule-based street modeling approach adds another tool in their methodological toolbox that can help bridge modeling and visualization with Complete Streets research.
      Citation: Transportation Research Record
      PubDate: 2021-03-29T12:03:07Z
      DOI: 10.1177/0361198121999051
       
  • Predictive Artificial Neural Network Laboratory Fatigue Endurance Limit
           Model for Asphalt Concrete Pavements Based on the Volumetric Properties
           and Loading Conditions
    • Authors: Mayzan M. Isied, Mena I. Souliman, Waleed A. Zeiada, Nitish R. Bastola
      Abstract: Transportation Research Record, Ahead of Print.
      Asphalt concrete healing is one of the important concepts related to flexible pavement structures. Fatigue endurance limit (FEL) is defined as the strain limit under which no damage will be accumulated in the pavement and is directly related to asphalt healing. Pavement section designed to handle a strain value equivalent to the endurance limit (EL) strain will be considered as a perpetual pavement. All four-point bending beam fatigue testing results from the NCHRP 944-A project were extracted and utilized in the development of artificial neural network (ANN) EL strain predictive model based on mixture volumetric properties and loading conditions. ANN model architecture, as well as the prediction process of the EL strain utilizing the generated model, were presented and explained. Furthermore, a stand-alone equation that predicts the EL strain value was extracted from the developed ANN model utilizing the eclectic approach. Moreover, the EL strain value was predicted utilizing the new equation and compared with the EL strain value predicted by other prediction models available in literature. A total of 705 beam fatigue lab test data points were utilized in model training and evaluation at ratios of 70%, 15%, and 15% for training, testing, and validation, respectively. The developed model is capable of predicting the EL strain value as a function of binder grade, temperature, air void content, asphalt content, SR, failure cycles number, and rest period. The reliability of the developed stand-alone equation and the ANN model was presented by reasonable coefficient of determination (R2) value and significance value (F).
      Citation: Transportation Research Record
      PubDate: 2021-03-29T12:01:08Z
      DOI: 10.1177/0361198121999657
       
  • Improvement of Strength and Volume-Change Properties of Expansive Clays
           with Geopolymer Treatment
    • Authors: Rinu Samuel, Anand J. Puppala, Aritra Banerjee, Oscar Huang, Miladin Radovic, Sayantan Chakraborty
      Abstract: Transportation Research Record, Ahead of Print.
      Expansive soils are conventionally treated with chemical stabilizers manufactured by energy-intensive processes that significantly contribute to carbon dioxide emissions globally. Geopolymers, which are synthesized from industrial byproducts rich in aluminosilicates, are a viable alternative to conventional treatments, as they are eco-friendly and sustainable. In this study, a metakaolin-based geopolymer was synthesized, and its effects on the strength and volume-change behavior of two native expansive soils from Texas, with a plasticity index over 20 were investigated. This paper elaborates on the geopolymerization process, synthesis of the metakaolin-based geopolymer, specimen preparation, and geopolymer treatment of soils. Comprehensive material testing revealed two clays with a plasticity index over 20. They were each treated with three dosages of the metakaolin-based geopolymer and cured in 100% relative humidity for three different curing periods. The efficiency of geopolymer treatment was determined by testing the control and geopolymer-treated soils for unconfined compressive strength (UCS), one-dimensional swell, and linear shrinkage. Field emission scanning electron microscope (FESEM) imaging was performed on the synthesized geopolymer, as well as on the control and geopolymer-treated soils, to detect microstructural changes caused by geopolymerization. A significant increase in UCS and reduction in swelling and shrinkage were observed for both geopolymer-treated soils, within a curing period of only 7 days. The FESEM imaging provided new insights on the structure of geopolymers and evidence of geopolymer formation in treated soils. In conclusion, the metakaolin-based geopolymer has strong potential as a lower-carbon-footprint alternative to conventional stabilizers for expansive soils.
      Citation: Transportation Research Record
      PubDate: 2021-03-27T07:06:14Z
      DOI: 10.1177/03611981211001842
       
  • Benchmarking Unmanned Aerial Systems-Assisted Inspection of Steel Bridges
           for Fatigue Cracks
    • Authors: Sattar Dorafshan, Leslie E. Campbell, Marc Maguire, Robert J. Connor
      Abstract: Transportation Research Record, Ahead of Print.
      Inspection agencies have been increasingly implementing unmanned aerial systems (UAS) for bridge inspections. Currently, UAS are typically used for long-range monitoring and surveillance tasks, but bridge managers are hopeful that they may be utilized for detailed inspection, such as condition assessments and the inspection of fracture critical members (FCMs) in the near future. As an assistive tool for visual inspections, the accuracy of UAS-assisted inspections is unknown. This study investigates the relationship between the characteristics of the individual inspectors and a set of performance metrics associated with UAS-assisted FCM inspections. Four bridge inspectors used a UAS to inspect a series of full-sized bridge specimens with known fatigue cracks. The inspection videos were later shared with 19 bridge inspectors for a desk review. The performance of each inspector was evaluated and compared with the results from 30 hands-on inspections of the same specimens. The results showed that an inspector’s past experience with UAS, licensure, and academic degree could have a significant influence on one or more of the three defined performance metrics. The comparison between the results of the UAS-assisted inspections and the hands-on inspections revealed that crack detection was comparable. However, the hands-on inspections were more accurate.
      Citation: Transportation Research Record
      PubDate: 2021-03-26T12:46:05Z
      DOI: 10.1177/03611981211001073
       
  • Assessing the Impact of Large-Scale Trends on Ontario’s Pedestrian
           Fatality Rate
    • Authors: Sarah C. Plonka, Sara Volo, Patrick A. Byrne, Ian Sinclair, Thadsha Prabha
      Abstract: Transportation Research Record, Ahead of Print.
      Pedestrian-involved collisions are a key contributor to roadway fatalities in Ontario; pedestrian deaths have been growing as a proportion of total road fatalities. This study aimed first to determine trends in the pedestrian fatality rate in Ontario over time and, second, to assess the impact of select large-scale trends on pedestrian fatalities. Large-scale trends were identified through a review of the literature and hypotheses were tested using Ontario collision data from 2002 to 2016. The following four key areas were assessed for their impact: (1) the aging demographic; (2) the impact of increasing consumer preference for light trucks; (3) the potential for an increase in alcohol-consuming pedestrians associated with a decrease in alcohol-consuming drivers, and; (4) increasing inattention, caused, in part, by pedestrians and drivers using electronic devices. A quadratic model, with a minimum at 2010, best described changes in Ontario’s pedestrian fatality rate, suggesting a transition from a decreasing to increasing trend at that time. Results of the four key areas were: (1) the proportion of pedestrians aged 75 and older being killed has been increasing over time, a trend that can be fully explained by their increased representation in Ontario’s population, a trend which is expected to continue; (2) similarly, the increase in the proportion of pedestrians killed by a light truck can be explained by their increased representation in Ontario’s registered vehicle population; (3) the odds of a pedestrian being alcohol positive have been decreasing over time; and (4) the odds are higher that a driver who kills a pedestrian is inattentive.
      Citation: Transportation Research Record
      PubDate: 2021-03-26T12:43:38Z
      DOI: 10.1177/0361198121999625
       
  • Considering Roadway Context in Setting Posted Speed Limits
    • Authors: Kay Fitzpatrick, Subasish Das, Timothy Gates, Karen K. Dixon, Eun Sug Park
      Abstract: Transportation Research Record, Ahead of Print.
      The National Cooperative Highway Research Program (NCHRP) Project 17-76 investigated factors that influence operating speed and safety through a review of the literature and an analysis of the relationships for speed, safety, and roadway characteristics on urban/suburban streets. That knowledge, along with a review of existing speed limit setting practices, was used to develop a Speed Limit Setting Procedure (SLS-Procedure) as well as a user manual to explain the SLS-Procedure. In addition, the SLS-Procedure was automated via a spreadsheet-based Speed Limit Setting Tool (SLS-Tool). These products will permit engineers to make informed decisions about the setting of speed limits. The SLS-Procedure is fact based and transparent, relying on a set of decision rules that consider both driver speed choice and safety associated with the roadway. The SLS-Procedure was designed to be applicable across different roadway types and contexts by having a set of unique decision rules for four combinations of roadway types and contexts: limited-access, undeveloped, developed, and full-access facilities. The SLS-Procedure uses the operating speed distribution as a starting point for the suggested speed limit, with the resulting suggested value based on consideration of roadway type, context, safety performance, and other characteristics.
      Citation: Transportation Research Record
      PubDate: 2021-03-26T12:41:38Z
      DOI: 10.1177/0361198121999618
       
  • Determination of Sample Size and Influencing Factors to Characterize
           Faulting in Jointed Concrete Pavements
    • Authors: Ruohan Li, Jorge A. Prozzi
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this study is to evaluate the field variability of jointed concrete pavement (JCP) faulting and its effects on pavement performance. The standard deviation of faulting along both the longitudinal and transverse directions are calculated. Based on these, the overall variability is determined, and the required sample sizes needed for a given precision at a certain confidence level are calculated and presented. This calculation is very important as state departments of transportation are required to report faulting every 0.1 mi to the Federal Highway Administration as required by the 2015 FAST Act. On average, twice the number of measurements are needed on jointed reinforced concrete pavements (JRCP) to achieve the same confidence and precision as on jointed plain concrete pavements (JPCP). For example, a sample size of 13 is needed to achieve a 95% confidence interval with a precision of 1.0 mm for average faulting of JPCP, while 26 measurements are required for JRCP ones. Average faulting was found to correlate with several climatic, structural, and traffic variables, while no significant difference was found between edge and outer wheelpath measurements. The application of Portland cement concrete overlay and the use of dowel bars (rather than aggregate interlock) are found to significantly reduce faulting. Older sections located on higher functional classes, and in regions of high precipitation or where the daily temperature change is larger, tend to have higher faulting, and might require larger samples sizes as compared with the rest when faulting surveys are to be conducted.
      Citation: Transportation Research Record
      PubDate: 2021-03-26T12:38:59Z
      DOI: 10.1177/0361198121996704
       
  • Pavement Distress and Debris Detection using a Mobile Mapping System with
           2D Profiler LiDAR
    • Authors: Radhika Ravi, Darcy Bullock, Ayman Habib
      Abstract: Transportation Research Record, Ahead of Print.
      Regular pavement monitoring over highways and airport runways is vital for public agencies to ensure the safe riding of vehicles and aircrafts. Highways are mostly subject to cracking and potholes along with a few instances of debris around construction work zones. Airports are also concerned with debris but have much lower tolerance for the presence of foreign object debris (FOD) that could possibly damage the aircraft. LiDAR is rapidly emerging in a variety of mobile mapping systems (MMS) and will likely be integrated into many transportation vehicles over the next decade for pavement inspection. This paper proposes a unique algorithm for pavement surface inspection with the help of MMS driven at highway speeds. The study analyzed LiDAR data acquired for 8 mi of highway collected at approximately 55 to 60 mph. This study indicates that an adequately designed MMS along with the proposed algorithm can efficiently detect pavement anomalies as small as 2 cm in the form of cracking, potholes, surface debris, or any combination of these. This is more than sufficient for highways, where debris such as ladders and tires are an order of magnitude larger. For evaluating the effectiveness of detecting smaller airport FOD, a validation dataset was created by driving the MMS at 15 mph adjacent to a debris field of 50 sample pieces of FOD collected from an airport. The study found that 100% of the FOD items larger than 2 cm in size (12 out of 50 samples) were detected successfully at 15 mph. Both datasets suggest that MMS LiDAR is sufficient for pavement inspection and as sensor fidelity increases, even small FOD will be able to be detected with the algorithm proposed in this paper.
      Citation: Transportation Research Record
      PubDate: 2021-03-25T12:43:18Z
      DOI: 10.1177/03611981211002529
       
  • Consistent Three-Dimensional Elasto-Plastic Model to Study Unsaturated
           Soil Behavior with Considerations of Coupled Hydro-Mechanical Hysteresis
    • Authors: Beshoy Riad, Xiong Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a consistent three-dimensional elasto-plastic model to study unsaturated soil behavior with consideration of coupled hydro-mechanical hysteresis. The model was first formulated under isotropic conditions with special consideration to the non-linearity of the hydraulic behavior. Only one yield curve is used to represent the yielding of both mechanical and hydraulic behaviors (i.e., the occurrence of plastic water content changes and mechanical strains). Later, the model is extended to general three-dimensional stress conditions. It was formulated in a way that a smooth transition between the saturated and unsaturated soil states is guaranteed. The model provides consistent predictions for different soil phases that is considered a significant limitation in many existing models. One of the characteristic features of the proposed model is the ability to represent the hydro-mechanical coupling during shearing. Moreover, the model is able to represent the degree of saturation increase or decrease during shearing that is closely related to the soil’s contractive or dilative behavior, respectively. The model is validated through the prediction of several hydro-mechanical behavioral features. The paper also compares the model predictions with published experimental results performed under different loading conditions. The response of the model is satisfactory in relation to both mechanical and hydraulic behaviors.
      Citation: Transportation Research Record
      PubDate: 2021-03-25T12:42:18Z
      DOI: 10.1177/03611981211002217
       
  • Topic Models from Crash Narrative Reports of Motorcycle Crash Causation
           Study
    • Authors: Subasish Das, Anandi Dutta, Ioannis Tsapakis
      Abstract: Transportation Research Record, Ahead of Print.
      The Motorcycle Crash Causation Study (MCCS) is a matched case-control study that contains a very wide list of crash contributing factors associated with motorcycle crash occurrences. It contains information such as motorcycle information, rider information, and associated trip information. This study also provides crash narrative information that presents an in-depth narrative discussion of the crash causation. Because of the plethora of information, it is critical to investigate MCCS-related data. Some studies examined the structured information in MCCS datasets. There is no in-depth study that has examined the unstructured textual contents in the MCCS data. This study aims to mitigate this research gap by applying different natural language processing tools (e.g., text mining, topic modeling). Fatal and non-fatal crash narratives are clustered separately to gain insights pertaining to the injury level. The findings of this study will contribute to the ongoing studies on MCCS to better understand the crash causation mechanism associated with motorcycle crashes.
      Citation: Transportation Research Record
      PubDate: 2021-03-24T12:37:51Z
      DOI: 10.1177/03611981211002523
       
  • Precast Concrete Paving Repairs at Vancouver International Airport
    • Authors: Christopher T. Senseney, Peter J. Smith, Mark B. Snyder
      Abstract: Transportation Research Record, Ahead of Print.
      In 2019, Vancouver International Airport conducted a precast concrete panel replacement pilot project on Taxiway Victor to establish whether precast concrete was a viable option for a planned runway repair project. This was the first major use of precast airfield pavement in North America in nearly 20 years. Twelve panels measuring 6 m × 7.5 m with a thickness of 360 mm and weighing up to 43 metric tons each were installed to demonstrate the viability of in-situ concrete panel replacement in 8-h night work windows. The panels were designed as heavily reinforced “ductile slabs”; conventional pavement design procedures would have required much greater slab thickness and removal/replacement of base material, which would have greatly slowed panel replacements. Load transfer was provided by 38-mm diameter galvanized steel dowels, which were spaced nonuniformly along each panel edge. The use of bottom slots presented a clean surface with minimal potential for foreign object damage. Five of the panels included embedded airfield light cans, which required great placement precision to ensure their proper alignment and function. Seven of the panels were nonplanar, requiring a special first-of-its-kind warped casting bed that was large enough to produce nonplanar airfield-sized panels to the specified fabrication tolerances. Many valuable lessons were learned during this pilot project, which confirmed that long-life jointed precast concrete pavement repairs could be successfully constructed in 8-h overnight work windows on an active airfield using large repair panels and doweled joints, while adhering to strict panel-to-panel elevation tolerances.
      Citation: Transportation Research Record
      PubDate: 2021-03-24T12:24:59Z
      DOI: 10.1177/03611981211002518
       
  • Highway Asset and Pavement Condition Management using Mobile
           Photogrammetry
    • Authors: Mohammad Farhadmanesh, Chandler Cross, Ali H. Mashhadi, Abbas Rashidi, Jessica Wempen
      Abstract: Transportation Research Record, Ahead of Print.
      Highway asset condition is of the utmost importance for transportation maintenance and pedestrian safety. Transportation facility managers must have up-to-date information on the status of all transportation assets to keep the transportation facilities operating at their highest level. Because of the sheer volume of transportation assets, an efficient and affordable data-collection procedure is necessary to gather the as-is status of the assets and create an asset inventory. Some pioneer departments of transportation in the United States use mobile Light Detection and Ranging (LiDAR) to monitor highway assets and pavement condition data. Not only is the laser scanning equipment expensive, but the operator in charge of using the equipment must have special technical knowledge that may not be accessible to every individual. More recently, image-based reconstruction, known as photogrammetry, has emerged as a cheaper and simpler technology than LiDAR. Image-based 3D reconstruction can be done using a digital camera, such as a digital single-lens reflex camera or even a smartphone. This paper presents a full review of various research studies conducted on highway asset management and pavement condition assessment using spatial data modeling by the use of LiDAR and photogrammetry. This paper also presents two case studies to fill the current research gap in highway asset inventorying using photogrammetry. The results show the superiority of mobile LiDAR for highway asset inventorying and the possibility of having photogrammetry as a reliable alternative technology only in favorable illumination conditions.
      Citation: Transportation Research Record
      PubDate: 2021-03-24T12:23:18Z
      DOI: 10.1177/03611981211001855
       
  • Collection, Analysis, and Reporting of Kentucky Traffic Incident
           Management Performance
    • Authors: Xu Zhang, Reginald R. Souleyrette, Eric Green, Teng Wang, Mei Chen, Paul Ross
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic incidents remain all too common. They negatively affect the safety of the traveling public and emergency responders and cause significant traffic delays. Congestion associated with incidents can instigate secondary crashes, exacerbating safety risks and economic costs. Traffic incident management (TIM) provides an effective approach for managing highway incidents and reducing their occurrence and impacts. The paper discusses the establishment and methods of calculation for five TIM performance measures that are used by the Kentucky Transportation Cabinet (KYTC) to improve incident response. The measures are: roadway clearance time, incident clearance time, secondary crashes, first responder vehicle crashes, and commercial motor vehicle crashes. Ongoing tracking and analysis of these metrics aid the KYTC in its efforts to comprehensively evaluate its TIM program and make continuous improvements. As part of this effort, a fully interactive TIM dashboard was developed using the Microsoft Power BI platform. Dashboard users can apply various spatial and temporal filters to identify trends at the state, district, county, and agency level. The dashboard also supports dynamic visualizations such as time-series plots and choropleth maps. With the TIM dashboard in place, KYTC personnel, as well as staff at other transportation agencies, can identify the strengths and weaknesses of their incident management strategies and revise practices accordingly.
      Citation: Transportation Research Record
      PubDate: 2021-03-24T12:21:31Z
      DOI: 10.1177/03611981211001077
       
  • Self-Regulating Demand and Supply Equilibrium in Joint Simulation of
           Travel Demand and a Ride-Pooling Service
    • Authors: Gabriel Wilkes, Roman Engelhardt, Lars Briem, Florian Dandl, Peter Vortisch, Klaus Bogenberger, Martin Kagerbauer
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents the coupling of a state-of-the-art ride-pooling fleet simulation package with the mobiTopp travel demand modeling framework. The coupling of both models enables a detailed agent- and activity-based demand model, in which travelers have the option to use ride-pooling based on real-time offers of an optimized ride-pooling operation. On the one hand, this approach allows the application of detailed mode-choice models based on agent-level attributes coming from mobiTopp functionalities. On the other hand, existing state-of-the-art ride-pooling optimization can be applied to utilize the full potential of ride-pooling. The introduced interface allows mode choice based on real-time fleet information and thereby does not require multiple iterations per simulated day to achieve a balance of ride-pooling demand and supply. The introduced methodology is applied to a case study of an example model where in total approximately 70,000 trips are performed. Simulations with a simplified mode-choice model with varying fleet size (0–150 vehicles), fares, and further fleet operators’ settings show that (i) ride-pooling can be a very attractive alternative to existing modes and (ii) the fare model can affect the mode shifts to ride-pooling. Depending on the scenario, the mode share of ride-pooling is between 7.6% and 16.8% and the average distance-weighed occupancy of the ride-pooling fleet varies between 0.75 and 1.17.
      Citation: Transportation Research Record
      PubDate: 2021-03-24T12:15:30Z
      DOI: 10.1177/0361198121997140
       
  • Examining the Effects of the Built Environment on Travel Mode Choice
           across Different Age Groups in Seoul using a Random Forest Method
    • Authors: Kyusik Kim, Kyusang Kwon, Mark W. Horner
      Abstract: Transportation Research Record, Ahead of Print.
      It is important to analyze factors that influence travel mode choice and to predict individual mode choice because this shapes people’s movement and determines their level of mobility. While there have been studies investigating how built-environment elements are associated with travel mode choice, most efforts have neglected evaluating the heterogeneity of effects that the built environment has on travel mode choice across different age groups. This study aims to examine the effects of the built environment in influencing travel mode choice across age groups in Seoul, South Korea, using a random forest approach. Our random forest model demonstrates what factors are important and how they are associated with the effects on travel mode choice. As a result, the built environment has a greater impact on the subway selection for older adults than other age groups and the random forest approach captures non-linear relationships between certain predictors and travel mode choices. Applying this approach to the travel mode choice analysis, we can examine the heterogeneous effects of the built environment on travel mode choice across different age groups.
      Citation: Transportation Research Record
      PubDate: 2021-03-23T01:01:41Z
      DOI: 10.1177/03611981211000750
       
  • Understanding the Stiffness of Porous Asphalt Mixture through
           Micromechanics
    • Authors: Hong Zhang, Kumar Anupam, Tom Skarpas, Cor Kasbergen, Sandra Erkens
      Abstract: Transportation Research Record, Ahead of Print.
      Micromechanics, which can be used to relate the properties of a composite to the properties of individual constituents, is considered a good approach to understanding the fundamental mechanisms behind the behavior of asphalt materials. Compared with the semi-empirical and numerical micromechanical models, analytical micromechanical models do not need calibration factors. In addition, they can provide analytical solutions on the basis of a series of assumptions. Using these models, researchers have separated the effects of different stiffening mechanisms (i.e., the volume-filling reinforcement, the physicochemical reinforcement, and the particle-contact reinforcement) for mastic. However, similar research work has not been conducted for asphalt mixtures and, moreover, the characteristics of the particle-contact reinforcement have not been deeply analyzed by researchers. Therefore, this paper aims to understand the stiffness of asphalt mixture through micromechanics. The focus of this study was on porous asphalt mixture where particle-contact reinforcement plays an important role in its behavior. The stiffening effects of different mechanisms were separated using analytical micromechanical models. The effects of temperature/frequency and the properties of the matrix phase on the stiffening effect of the particle-contact reinforcement were analyzed.
      Citation: Transportation Research Record
      PubDate: 2021-03-23T01:00:21Z
      DOI: 10.1177/0361198121999060
       
  • Data-Driven Approach to Quantify and Reduce Error Associated with
           Assigning Short Duration Counts to Traffic Pattern Groups
    • Authors: Giuseppe Grande, Puteri Paramita, Jonathan D. Regehr
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic monitoring agencies collect traffic data samples to estimate annual average daily traffic (AADT) at short duration count sites. The steps to estimate AADT from sample data introduce error that manifests as uncertainty in the AADT statistic and its applications. Past research suggests that the assignment of a short duration count site to a traffic pattern group (TPG), characterized by known traffic periodicities, represents a significant but poorly quantified source of error. This paper presents an approach to quantify the range of errors arising from such assignments and to mitigate these errors using a novel data-driven assignment method. The approach uses simulated 48-hour short duration counts sampled from continuous count sites with known AADT to develop a benchmark of the total error expected when AADT is estimated from such samples. Likewise, the analysis produces a set of AADT estimates using temporal factors from pre-defined TPGs to quantify the range of assignment errors. The data-driven assignment method aims to mitigate these errors by minimizing the absolute mean deviation in AADT estimates produced from multiple short duration counts in a single year. The approach is applied to traffic data collected in Manitoba, Canada, as a case study. The results indicate that the mean absolute error from 48-hour short duration counts is 6.40% of the true AADT and that improper assignment can lead to a range in mean absolute errors of 9%. When applied to previously unassigned sites, the data-driven assignment method reduced mean absolute errors from 10.32%, using a conventional assignment method, to 7.86%.
      Citation: Transportation Research Record
      PubDate: 2021-03-22T12:02:02Z
      DOI: 10.1177/03611981211001831
       
  • Development of Cost-Effective Restriping Strategies using Standard Width
           
    • Authors: Momen R. Mousa, Marwa Hassan, Paul Carlson, Jason Davis, Saleh R. Mousa
      Abstract: Transportation Research Record, Ahead of Print.
      In Louisiana, most districts restripe their roadways using waterborne paints every other year; this strategy is questionable in relation to efficiency and economy. Previous studies show substantial variability in paint service life throughout the U.S.A., ranging between 0.25 and 6.2 years. Shortcomings in modeling the retroreflectivity of waterborne paints appear to significantly contribute to these variations as several studies predicted these values using degradation curves with a coefficient of determination (R2) as low as 0.1. Therefore, the objective of this study was to develop new cost-effective restriping strategies using 4 in. and 6 in. wide waterborne paints (15 and 25 mils thickness) when applied on asphalt pavements in hot and humid climates. To achieve this objective, National Transportation Product Evaluation Program data were collected and analyzed to evaluate the field performance of waterborne paints commonly used in southern states of the U.S.A. and to develop a decision making model that may be used by transportation agencies to predict when to restripe their roadways. Results indicated that 4 in. wide standard paints exhibited service life up to four years depending on the line color, traffic and initial retroreflectivity, while 4 in. wide high build paints had a service life of at least three years. Based on a life-cycle cost analysis, it was concluded that Louisiana Department of Transportation and Development could restripe its district roads every three years instead of the current two-year period using the same product (4 in. or 6 in. wide) saving about $20 million or $2 million, respectively, every year when restriping a 5,000-mi network.
      Citation: Transportation Research Record
      PubDate: 2021-03-22T12:00:22Z
      DOI: 10.1177/03611981211001872
       
  • Spatiotemporal Analysis of Highway Traffic Patterns in Hurricane Irma
           Evacuation
    • Authors: Mahyar Ghorbanzadeh, Simone Burns, Linoj Vijayan Nair Rugminiamma, Eren Erman Ozguven, Wenrui Huang
      Abstract: Transportation Research Record, Ahead of Print.
      The State of Florida is significantly vulnerable to catastrophic hurricanes that cause widespread infrastructural damage and claim lives annually. In 2017, Hurricane Irma, a Category 4 hurricane, took on the entirety of Florida, causing the state’s largest evacuation ever as 7 million residents fled the hurricane. Floridians fleeing the hurricane faced the unique challenge of where to go, since Irma made an unusual landfall from the south, enveloping the entire state, forcing evacuees to drive farther north, and creating traffic jams along Florida’s evacuation routes that were worse than during any other hurricane in Florida's history. This study aimed to assess the spatiotemporal traffic impacts of Irma on Florida’s major highways based on real-time traffic data before, during, and after the hurricane made landfall. First, we conducted a time-series-based analysis to evaluate the temporal evacuation patterns of this large-scale evacuation. Second, we developed a metric, namely the congestion index (CI), to assess the spatiotemporal evacuation patterns on I-95, I-75, I-10, I-4, and turnpike (SR-91) highways with a focus on both evacuation and returning traffic. Third, we employed a geographic information system-based analysis to visually illustrate the CI values of corresponding highway sections with respect to different dates and times. Findings clearly showed that imperfect forecasts and the uncertainty surrounding Irma’s predicted path resulted in high levels of congestion and severe delays on Florida’s major evacuation routes.
      Citation: Transportation Research Record
      PubDate: 2021-03-22T11:58:22Z
      DOI: 10.1177/03611981211001870
       
  • Evaluating the Performance of Wicking Geotextile in Providing Drainage for
           Flexible Pavements Built over Expansive Soils
    • Authors: Nripojyoti Biswas, Anand J. Puppala, Md Ashrafuzzaman Khan, Surya Sarat Chandra Congress, Aritra Banerjee, Sayantan Chakraborty
      Abstract: Transportation Research Record, Ahead of Print.
      The longevity and performance of a pavement section depend on the characteristics of the subgrade soil. A majority of the pavements in North Texas, U.S., are constructed on expansive soils. The deterioration of the pavement performance because of rutting, cracking, and differential heaving is a regular phenomenon in the regions predominantly distributed with expansive soils. The pavements, particularly those built for low-volume traffic conditions, experience distress because of the high swelling and shrinkage characteristics of the underlying problematic soils. Geosynthetics have been traditionally used to improve such poor subgrades because of their many benefits, such as ease of installation, and ample mechanical and hydraulic properties. In the last decade, a newly available wicking geotextile, with a moisture redistribution capacity, has been developed to improve the performance of pavements constructed over expansive and frozen soils. In this study, small-scale laboratory and full-scale field studies were conducted to comprehend the wicking ability of this innovative geotextile in an expansive soil environment. Full-scale test sections were constructed with reclaimed asphalt pavement aggregate and traditional crushed stone aggregates in the base layer near North Texas. Details of the construction and instrumentation procedure are discussed in this paper. A comparative study between the performance of the pavement sections subjected to traffic loads and moisture intrusion was also performed. Furthermore, the rutting life of the sections, estimated using a linear elastic model, was compared and validated using the in situ data. The observations during the initial phase indicated that the wicking geotextile has the potential to improve the long-term pavement performance.
      Citation: Transportation Research Record
      PubDate: 2021-03-22T11:55:41Z
      DOI: 10.1177/03611981211001381
       
  • Equity-Oriented Criteria for Project Prioritization in Regional
           Transportation Planning
    • Authors: Agustina Krapp, Jesus M. Barajas, Audrey Wennink
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation inequities, the consequences of decades of auto-oriented planning alongside discriminatory land-use and transportation planning and policy decisions resulting from structural racism, severely limit opportunities for people of color and other marginalized populations. While a growing body of work has examined inequities with respect to long-range transportation planning, less research examines how equity is incorporated in short-term planning processes via the Transportation Improvement Program. This research reviewed how the metropolitan planning organizations (MPOs) that serve the 40 largest U.S. urbanized areas used equity-based criteria for transportation project prioritization in regional planning. Just over half deployed at least one equity criterion for allocating transportation funds, which fell into one of six categories with varying degrees of complexity and potential for impact. While most MPOs included equity in their prioritization criteria, the methods could be improved to align better with more complete definitions of transportation equity, focusing on how targeted groups are defined, more comprehensive methods for equity evaluation, and an increase in the weight that equity is given in prioritization. MPOs and other agencies implementing transportation projects should adopt a justice-oriented framework for project prioritization that ensures that projects first affirmatively remedy historical inequities and work with affected communities to adopt appropriate and meaningful solutions.
      Citation: Transportation Research Record
      PubDate: 2021-03-22T11:54:01Z
      DOI: 10.1177/03611981211001072
       
  • Predicting Coordinated Actuated Traffic Signal Change Times using Long
           Short-Term Memory Neural Networks
    • Authors: Seifeldeen Eteifa, Hesham A. Rakha, Hoda Eldardiry
      Abstract: Transportation Research Record, Ahead of Print.
      Vehicle acceleration and deceleration maneuvers at traffic signals result in significant fuel and energy consumption levels. Green light optimal speed advisory systems require reliable estimates of signal switching times to improve vehicle energy/fuel efficiency. Obtaining these estimates is difficult for actuated signals where the length of each green indication changes to accommodate varying traffic conditions and pedestrian requests. This study details a four-step long short-term memory (LSTM) deep learning based methodology that can be used to provide reasonable switching time estimates from green to red and vice versa while being robust to missing data. The four steps are data gathering, data preparation, machine learning model tuning, and model testing and evaluation. The input to the models includes controller logic, signal timing parameters, time of day, traffic state from detectors, vehicle actuation data, and pedestrian actuation data. The methodology is applied and evaluated on data from an intersection in Northern Virginia. A comparative analysis is conducted between different loss functions including the mean squared error, mean absolute error, and mean relative error used in LSTM and a new loss function that is proposed in this paper. The results show that while the proposed loss function outperforms conventional loss functions in overall absolute error values, the choice of the loss function is dependent on the prediction horizon. Specifically, the proposed loss function is slightly outperformed by the mean relative error for very short prediction horizons (less than 20 s) and the mean squared error for very long prediction horizons (greater than 120 s).
      Citation: Transportation Research Record
      PubDate: 2021-03-22T11:52:02Z
      DOI: 10.1177/03611981211000748
       
  • I-RIPRAP Computer Vision Software for Automated Size and Shape
           Characterization of Riprap in Stockpile Images
    • Authors: Haohang Huang, Jiayi Luo, Issam Qamhia, Erol Tutumluer, John M. Hart, Andrew J. Stolba
      Abstract: Transportation Research Record, Ahead of Print.
      Riprap rocks and large-sized aggregates have been used extensively in geotechnical and hydraulic engineering applications to serve as a key component for erosion/sediment control and scour protection. Toward sustainable and reliable use of riprap rocks, an efficient and accurate method to characterize the size and shape properties is deemed necessary. Current state-of-the-practice methods mostly assess riprap properties with labor-intensive and time-consuming inspection routines that involve manual size and weight measurements. Recent advances in the field of computer vision have been leveraged in this paper to apply deep learning for the development of an innovative image analysis tool for quantitative and efficient riprap characterization. Based on the single-aggregate and stockpile-aggregates studies conducted on this topic, this paper introduces a newly developed computer program, named I-RIPRAP, for the advanced characterization of aggregate size and shape from images of riprap stockpile(s). The essential features and software workflow, as well as the function and mechanism of each module, are described and discussed in detail. In addition to the deep learning methods for segmentation, I-RIPRAP also improves the morphological analyses with a volume/weight estimation module and a riprap category reference module to generate useful results that can facilitate quality assurance/quality control tasks. The I-RIPRAP software is envisioned to serve as an efficient and innovative tool for field and in-place evaluations of riprap and large-sized aggregates.
      Citation: Transportation Research Record
      PubDate: 2021-03-20T12:09:15Z
      DOI: 10.1177/03611981211001375
       
  • Grayscale Drone Inspection Image Enhancement Framework for Advanced Bridge
           Defect Measurement
    • Authors: Euiseok Jeong, Junwon Seo, James Wacker
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a framework to better identify and measure defects in a bridge using drone-based inspection images integrated with grayscale image enhancement techniques. For this study, a DJI Matrice 210 drone was used for the inspection of a three-span timber bridge with concrete decking located in Keystone, South Dakota. During the inspection, the drone recorded a series of videos of the bridge using the MOVie (MOV, video file extension) video format. MOV-based image analysis was conducted to identify a variety of defect types (i.e., efflorescence, water leakage, spalling, and discoloration) on the bridge. For improvement of defect visibility, the grayscale image enhancement technique was applied to determine visually enhanced images for the individual defect. The technique used grayscale image histogram processing that can adjust images using realignment of contrast histograms, in which contrasts of each pixel of the grayscale images have their own number from 0 for black to 255 for white in the image. With the enhanced images, pixel-based measurement was conducted to quantify the defects, including efflorescence (3.75 m2), water leakage (4.21 m2), spalling (0.74 m2), and discoloration (2.12 m2). Based on these findings, the grayscale drone inspection image enhancement technique enabled the demonstration of defect visibility adjustment and improvement for more reliable identification and measurement of the defects in the bridge.
      Citation: Transportation Research Record
      PubDate: 2021-03-20T12:03:53Z
      DOI: 10.1177/0361198121999605
       
  • Redevelopment of Artificial Neural Networks for Predicting the Response of
           Bonded Concrete Overlays of Asphalt for use in a Faulting Prediction Model
           
    • Authors: John W. DeSantis, Julie M. Vandenbossche
      Abstract: Transportation Research Record, Ahead of Print.
      Transverse joint faulting is a common distress in bonded concrete overlays of asphalt pavements (BCOAs), also known as whitetopping. However, to date, there is no predictive faulting model available for these structures. Therefore, the intended research is to develop a predictive faulting model for BCOAs. In addition, it is important to be able to account for conditions unique to BCOA when characterizing the response in a faulting prediction model. To address this, computational models were developed using a three-dimensional finite element program, ABAQUS, to accurately predict the response of these structures. These models account for different depths of joint activation, as well as full and partial bonding between the concrete overlay and existing asphalt pavement. The models were validated with falling weight deflectometer (FWD) data from existing field sections at the Minnesota Road Research Facility (MnROAD) as well as at the University of California Pavement Research Center (UCPRC). A fractional factorial analysis was executed using the computational models to generate a database to be used in the development of the predictive models. The predictive models, based on artificial neural networks (ANNs), are used to rapidly estimate the structural response at the joint in BCOA to environmental and traffic loads so that these responses can be incorporated into the design process. The structural response obtained using the ANNs is related to damage using the differential energy concept. Future work includes the implementation of the ANNs developed in this study into a faulting prediction model for designing BCOA.
      Citation: Transportation Research Record
      PubDate: 2021-03-20T12:01:43Z
      DOI: 10.1177/03611981211001075
       
  • Alternative Regression Model Structure for the HCM-6 Equal-Capacity
           Passenger Car Equivalency Methodology
    • Authors: Antonio Hurtado-Beltran, Laurence R. Rilett
      Abstract: Transportation Research Record, Ahead of Print.
      In the current version of the Highway Capacity Manual (HCM-6), equal-capacity passenger car equivalencies (EC-PCEs) are used to account for the effect of trucks for capacity analyses. The EC-PCEs for freeway segments were estimated using a microsimulation-based methodology where the capacities of the mixed-traffic and car-only flow scenarios were modeled. A nonlinear regression (NLR) model was used to develop capacity adjustment factor (CAF) models using the microsimulation data as input. The NLR model has a complex model structure and includes 15 model parameters. It is argued in this paper that simpler regression models could provide comparable results. This would allow CAF and EC-PCE equations to be used directly in the HCM-6 rather than tables. It would also allow for the development of new regression models for exploring new technologies such as connected and automated vehicles (CAVs). The objective of this paper was to develop alternative and simpler regression models of CAFs needed to derive the EC-PCE values in the HCM-6 methodology for freeway and multilane highway segments. It was found that simpler regression models provided similar results as those obtained with the current NLR model. Additionally, it was found that the current NLR model may not be adequate for analyzing CAV traffic conditions. If the HCM-6 EC-PCE methodology is expected to be used to analyze traffic conditions beyond the scope of the HCM-6, it is important to perform a deeper assessment of the form and error of the regression models used in fitting the simulated and estimated data.
      Citation: Transportation Research Record
      PubDate: 2021-03-20T11:59:31Z
      DOI: 10.1177/0361198121995827
       
  • Investigation of Grouted Coupler Connection Details for Accelerated Bridge
           Construction
    • Authors: Brent Phares, Yoon-Si Lee, Travis K. Hosteng, Jim Nelson
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a laboratory investigation on the performance of grouted rebar couplers with the connection details similar to those utilized on the precast concrete elements of the Keg Creek Bridge on US 6 in Iowa. The testing program consisted of a series of static load tests, a fatigue test, and evaluation of the chloride penetration resistance of laboratory specimens. The goal of this testing was to evaluate the ability of the grouted rebar couplers to develop flexural capacity at the joint between the precast elements as well as the durability of the connection. For structural load testing, seven full-scale specimens, each with #14 epoxy-coated rebars spliced by epoxy-coated grouted couplers, were fabricated and tested in three different loading cases: four-point bending, axial tension plus bending, and a cyclic test of the system in bending. The static load testing demonstrated that the applied axial load had a minimal effect on the formation of cracks and overall performance of the connection. When ultra-high performance concrete was used as a bedding grout, the initiation of crack was slightly delayed but no considerable improvement was observed in the magnitude of the crack width during loading or the crack closure on unloading. The results of the seventh specimen, tested in fatigue to 1 million cycles, showed little global displacement and crack width throughout the test, neither of which expanded measurably. No evidence of moisture or chloride penetration was detected at the grouted joint during the 6-month monitoring.
      Citation: Transportation Research Record
      PubDate: 2021-03-19T09:18:32Z
      DOI: 10.1177/0361198121999393
       
  • Analysis of Vehicle–Pedestrian Interactive Behaviors near
           Unsignalized Crosswalk
    • Authors: Byeongjoon Noh, Dongho Ka, David Lee, Hwasoo Yeo
      Abstract: Transportation Research Record, Ahead of Print.
      Road traffic accidents are a leading cause of premature deaths and globally pose a severe threat to human lives. In particular, pedestrians crossing the road present a major cause of vehicle–pedestrian accidents in South Korea, but we lack dense behavioral data to understand the risk they face. This paper proposes a new analytical system for potential pedestrian risk scenes based on video footage obtained by road security cameras already deployed at unsignalized crosswalks. The system can automatically extract the behavioral features of vehicles and pedestrians, affecting the likelihood of potentially dangerous situations after detecting them in individual objects. With these features, we can analyze the movement patterns of vehicles and pedestrians at individual sites, and understand where potential traffic risk scenes occur frequently. Experiments were conducted on four selected behavioral features: vehicle velocity, pedestrian position, vehicle–pedestrian distance, and vehicle–crosswalk distance. Then, to show how they can be useful for monitoring the traffic behaviors on the road, the features are visualized and interpreted to show how they may or may not contribute to potential pedestrian risks at these crosswalks: (i) by analyzing vehicle velocity changes near the crosswalk when there are no pedestrians present; and (ii) analyzing vehicle velocities by vehicle–pedestrian distances when pedestrians are on the crosswalk. The feasibility of the proposed system is validated by applying the system to multiple unsignalized crosswalks in Osan city, South Korea.
      Citation: Transportation Research Record
      PubDate: 2021-03-19T09:17:51Z
      DOI: 10.1177/0361198121999066
       
  • Mining Route Set Distribution Range and Affecting Factor Threshold Based
           on Global Positioning System Data
    • Authors: Yajuan Deng, Sanghuiyu Yan, Xianbiao Hu, Peng Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Traditional route generation algorithms may result in many routes that few drivers choose in reality, whereas other route generation algorithms need to determine thresholds for route set generation but lack data support. To avoid invalid route generation, reduce computation time, and provide a scientific basis for the generation of navigation routes and traffic assignment, this paper confines the route set size by mining the spatial distribution range of route sets and the threshold of factors affecting route set generation. Global positioning system data are used to determine hotspots based on a hotspot origin–destination identification method. The route set spatial distribution range is mined by the standard deviational ellipse. Finally, the factors affecting the generation of route sets are selected, and the classification and regression trees algorithm is used to mine their thresholds. The results show that the spatial distribution range of route sets is elliptical, and the threshold values of the number of turns per kilometer for medium and long travel distances are 1.794 and 2.508, respectively. The maximum travel time per kilometer for long travel distance is 4.773 min. The maximum numbers of road intersections for short, medium, and long travel distance per kilometer are 1.648, 0.984, and 0.592, respectively. The implications of results on reducing the search range and time of the route set and their applications to traffic network design and route navigation are also discussed.
      Citation: Transportation Research Record
      PubDate: 2021-03-19T09:16:20Z
      DOI: 10.1177/0361198121999059
       
  • Time Delay Effects on Compactability of Soil-Cement Materials during
           Proctor Testing
    • Authors: W. Griffin Sullivan, Isaac L. Howard
      Abstract: Transportation Research Record, Ahead of Print.
      The Proctor test method, as specified in AASHTO T134 and ASTM D558, continues to play a vital role in design and construction quality control for soil-cement materials. However, neither test method establishes a methodology or standardized protocols to characterize the effects of time delay between cement addition and compaction, also known as compaction delay. Compaction delay has been well documented to have a notably negative effect on compactability, compressive strength, and overall performance of soil-cement materials, but specification tools to address this behavior are not prevalent. This paper aims to demonstrate the extent of compaction delay effects on several soil-cement mixtures used in Mississippi and to present recommended new test method protocols for AASHTO T134 to characterize compaction delay effects. Data presented showed that not all soil-cement mixtures are sensitive to compaction delay, but some mixtures can be very sensitive and lead to a meaningful decrease in specimen dry density. Recommended test method protocols were presented for AASHTO T134 and commentary was presented to provide state Departments of Transportation and other specifying agencies a few examples of how the new compaction delay protocols could be implemented.
      Citation: Transportation Research Record
      PubDate: 2021-03-19T09:15:52Z
      DOI: 10.1177/0361198121998700
       
  • Effectiveness of Warning Piles on Driving Behavior on the Curve of
           Low-Grade Highway
    • Authors: Yibing Liu, Xiaohua Zhao, Jia Li, Yang Bian, Jianming Ma
      Abstract: Transportation Research Record, Ahead of Print.
      To develop a scientific and practicable guideline for implementing warning piles on Chinese low-grade highways, it is necessary to study the effect of warning piles on driving performance in different road alignments and environments. Based on a driving simulator, this paper evaluates the effect of unilateral and bilateral warning piles on vehicle speed and lateral position on a two-lane rural highway curve with different road geometries. The results show a significant effect of bilateral warning piles on speed control, which becomes more obvious as the radius of the curve decreases and the superelevation increases. In sharp curves, vehicle speed increases rapidly in the second half of the curve, and bilateral warning piles could significantly control speed increase to prevent danger. Meanwhile, the effect of bilateral warning piles on keeping vehicles in a safer lane position is also statistically significant in the second half of the curve. With a decreasing radius and an increasing superelevation, the value of the maximum lateral position will increase. Bilateral warning piles could reduce the lateral position to keep the vehicle on a stable track. Moreover, bilateral warning piles could also perform better at night. This paper studies both unilateral and bilateral warning piles’ effects on driving behavior in different road geometries, thus providing a theoretical basis for the engineering application of warning piles.
      Citation: Transportation Research Record
      PubDate: 2021-03-19T09:15:39Z
      DOI: 10.1177/0361198121996358
       
  • Transport Networking Companies Demand and Flow Estimation in New York City
    • Authors: Bibhas Kumar Dey, Sudipta Dey Tirtha, Naveen Eluru
      Abstract: Transportation Research Record, Ahead of Print.
      Given the burgeoning growth in transport networking companies (TNC)-based ride hailing systems and their growing adoption for trip making, it is important to develop modeling frameworks to understand TNC ride hailing demand flows at the system level. Two choice dimensions are identified: (1) a demand component that estimates origin level TNC demand at the taxi zone level and (2) a distribution component that analyzes how these trips from an origin are distributed across the region. The origin level demand is analyzed using linear mixed models while flows from origin to multiple destinations is analyzed using a multiple discrete-continuous extreme value (MDCEV) model. The data for the analysis is drawn from New York City Taxi and Limousine Commission for 12 months from January through December 2018. For this analysis, weekday morning peak hour demand and distribution patterns are examined. The model components are developed using a comprehensive set of independent variables. The model estimation results offer very intuitive results for origin demand and distribution of flows across destinations. The model was validated by predicting trips to destination taxi zones and it was found that predicted model performs well in identifying high preference destination zones. In addition, elasticity effects are computed by evaluating the percentage change in baseline marginal utility in response to increasing the value of exogenous variables by 10%, 25% and 50%, respectively.
      Citation: Transportation Research Record
      PubDate: 2021-03-19T09:15:30Z
      DOI: 10.1177/03611981211000752
       
  • Online and Proactive Vehicle Rerouting with Uppaal Stratego
    • Authors: Alexander Bilgram, Emil Ernstsen, Peter Greve, Harry Lahrmann, Kim G. Larsen, Marco Muñiz, Peter Taankvist, Thomas Pedersen
      Abstract: Transportation Research Record, Ahead of Print.
      Modern navigation systems warn the user of traffic jams ahead and suggest alternative routes. However, a lemming effect can cause the alternative routes also to become congested, as the system suggests the same route to all users. As such, in an attempt to optimize for the individual driver, the welfare of the traffic network is punished. In this paper we introduce an online and proactive method for collective rerouting recommendations based on real-time data and stochastic optimization. Our system periodically monitors the status of the network to identify potentially congested roads together with vehicles affected by them. The system then uses Uppaal Stratego to perform machine learning and approximate the best rerouting scenarios. As a proof of concept, we build a SUMO model of a representative traffic network. We perform exhaustive experiments considering different traffic loads and different traffic light controllers. Our results are promising, showing considerable improvement in travel times, queue lengths, and CO2 emissions.
      Citation: Transportation Research Record
      PubDate: 2021-03-19T09:15:12Z
      DOI: 10.1177/03611981211000348
       
  • Long-Term Safety Analysis of Hard Shoulder Running on Freeways in Germany
    • Authors: Helen Waleczek, Justin Geistefeldt
      Abstract: Transportation Research Record, Ahead of Print.
      On freeways with high traffic demand, hard shoulder running (HSR) can be an effective traffic management measure to increase the capacity by providing an additional travel lane during peak hours. While the positive effects of HSR on traffic flow quality were documented in several studies, the implications of HSR on road safety are more ambiguous. This paper presents results of a study in which accident data for seven freeway sections with HSR on freeways in Germany were analyzed over a long period of 13 years. All investigated sections are equipped with variable speed limits. The evaluation of crash frequencies on the investigated freeway sections revealed a high safety level. By combining crash data and traffic data it is shown that crash occurrence depends on the prevailing traffic conditions, with congestion being the most critical traffic state in relation to safety. Therefore, safety improvements upstream of HSR segments can be related to the improved traffic flow and the reduction of congestion. In conclusion, the results of the investigation provide evidence that the implementation of HSR can improve road safety if state-of-the-art traffic control technology is applied and congestion can be relieved.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T12:06:07Z
      DOI: 10.1177/0361198121997836
       
  • Effects of Asphalt Foaming on Damage Characteristics of Foamed Warm Mix
           Asphalt
    • Authors: Biswajit K. Bairgi, Md Amanul Hasan, Rafiqul A. Tarefder
      Abstract: Transportation Research Record, Ahead of Print.
      In the asphalt foaming process, the foaming water content (FWC) controls the formation and characteristics of water bubbles. These water bubbles are expected to be expelled from the foamed warm mix asphalt (WMA) during mixing and compaction. However, foaming water may not be completely expelled, rather some of the microbubbles may be trapped in the foamed WMA even after compaction. These microbubbles, or undissipated water, can diffuse over time and cause damage to the foamed WMA. To this end, this study has determined the effects of foaming on the fatigue, moisture damage, and permanent deformation characteristics of foamed WMA. Foamed asphalt and mixtures were designed with varying FWCs and they were tested using linear amplitude sweep, multiple stress creep recovery, four-point flexural beam, and Hamburg wheel tracking tests. Primarily, asphalt foaming dynamics were assessed with a laser-based non-contact method. A simplified viscoelastic continuum damage concept and a three-phase permanent deformation model were used for damage evaluation. The study reveals that foaming softens the binder, which results in slightly higher rutting and moisture susceptibility, though an equivalent or slightly improved fatigue characteristic compared with the regular hot mix asphalt.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T12:03:43Z
      DOI: 10.1177/0361198121997823
       
  • Strategic Route Planning to Manage Transit’s Susceptibility to
           Disease Transmission
    • Authors: Sylvan Hoover, J. David Porter, Claudio Fuentes
      Abstract: Transportation Research Record, Ahead of Print.
      Transit agencies have experienced dramatic changes in service and ridership because of the COVID-19 pandemic. As communities transition to a new normal, strategic measures are needed to support continuing disease suppression efforts. This research provides actionable results to transit agencies in the form of improved transit routes. A multi-objective heuristic optimization framework employing the non-dominated sorting genetic algorithm II algorithm generates multiple route solutions that allow transit agencies to balance the utility of service to riders against the susceptibility of routes to enabling the spread of disease in a community. This research uses origin–destination data from a sample population to assess the utility of routes to potential riders, allows vehicle capacity constraints to be varied to support social distancing efforts, and evaluates the resulting transit encounter network produced from the simulated use of transit as a proxy for the susceptibility of a transit system to facilitating the transmission of disease among its riders. A case study of transit at Oregon State University is presented with multiple transit network solutions evaluated and the resulting encounter networks investigated. The improved transit network solution with the closest number of riders (1.2% more than baseline) provides a 10.7% reduction of encounter network edges.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T12:01:43Z
      DOI: 10.1177/0361198121997815
       
  • Analyzing Traffic Impacts of Planned Major Events
    • Authors: Genevieve Giuliano, Yougeng Lu
      Abstract: Transportation Research Record, Ahead of Print.
      Major events are a significant source of traffic congestion, especially in large metropolitan areas. This paper presents a case study of football games played at the Los Angeles Memorial Coliseum, a venue near downtown Los Angeles, California, with a capacity of about 80,000. Two teams play home games at the Coliseum: the Los Angeles Rams and the University of Southern California (USC) Trojans. These events take place in an area that has a high level of recurrent congestion. The traffic impacts of game days are analyzed by comparing game day traffic with traffic on control days on both the highway and arterial systems. The data include speed records from in-road detectors. Two sets of models are estimated to test relationships between game attributes and traffic performance. The first set is traditional regression models controlling for spatial and temporal correlation. The second set is random forest (RF), a type of machine learning estimation. RF is found to perform better, as it allows for complex non-linearities in variables. The results show that Rams and USC impacts are different. Rams fans arrive in a more concentrated time interval closer to the start time of games and, therefore, have a greater impact on the major approach routes than USC fans. The greatest impacts on highways are around nearby freeway-to-freeway interchanges. Arterial traffic is more consistently affected by distance from the venue. This case study provides the basis for better management of major planned events.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T11:59:43Z
      DOI: 10.1177/0361198121998710
       
  • Effect of Price and Time on Private and Shared Transportation Network
           Company Trips
    • Authors: Scott R. Middleton, Kyle A. Schroeckenthaler, Deepak Gopalakrishna, Allen Greenberg
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation network companies (TNCs) offer two types of service: private-party ridehailing and shared ridehailing. Policymakers have an interest in encouraging shared over private ridehailing to promote more efficient use of the transportation network. While transportation researchers have analyzed ridehailing behavior before, there is limited literature describing the effect of price and time on a rider’s choice between private-party and shared ridehailing. This paper fills this gap by analyzing revealed preferences for private-party and shared ridehailing trips in 15 American cities coupled with a survey of 4,365 users of a large TNC that includes stated preference questions focused on various alternative options for their most recent trip choice. This study finds that an increase in the relative price difference of $1 per mile increases an individual’s probability of sharing by over 8%, while a decrease in the relative travel time difference of 1 min per mile increases the probability of sharing by over 33%. The survey results also show that that a sizable proportion of private-party TNC trips (approximately 35%) will be difficult or even impossible to convert to shared rides through a price-based incentive. Market segmentation analysis reveals user and trip types where price- and time-based incentives have a relatively greater effect on the choice between private and shared rides. Finally, heterogeneity in user time versus money trade-offs suggests new product possibilities that would increase TNC sharing.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T11:58:22Z
      DOI: 10.1177/0361198121998702
       
  • Exposure-Based Models of Trail User Crashes at Roadway Crossings
    • Authors: Robert J. Schneider, Andrew Schmitz, Greg Lindsey, Xiao Qin
      Abstract: Transportation Research Record, Ahead of Print.
      Multi-use trails are popular for transportation and recreation, but pedestrians and bicyclists are exposed to motor vehicle traffic at trail crossings (locations where trails cross roadways), creating the risk of crashes, injuries, and fatalities. Many trail crossing design guidelines suggest best practices to make trail crossings safe, but few studies have quantified the statistical relationship between trail user crashes and a broad set of trail crossing characteristics. Our study developed one of the first trail crossing crash models using trail user crashes reported at 197 crossings in the city of Minneapolis, MN, and in the Milwaukee, WI, region between 2011 and 2018. We took advantage of widespread trail counting programs and historic aerial and street-level imagery to create and test more than 30 theoretically important potential explanatory variables. We addressed the challenge that many crossings had small numbers of crashes (or zero crashes) during the study period by using a Poisson-lognormal model. Our model showed significant associations between trail crossing crashes and trail traffic volume, roadway motor vehicle volume, three-way intersections where the trail crosses perpendicular to the mainline roadway, and total crossing length. Although not statistically significant, signalized intersections and limited sight lines between drivers and trail users near crossings may also be associated with more crashes. Future research can build on this study and expand systemic efforts to improve trail crossing safety.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T11:56:20Z
      DOI: 10.1177/0361198121998692
       
  • Approach to Quantify the Impact of Disruptions on Traffic Conditions using
           Dynamic Weighted Resilience Metrics of Transport Networks
    • Authors: Elise Henry, Angelo Furno, Nour-Eddin El Faouzi
      Abstract: Transportation Research Record, Ahead of Print.
      Transport networks are essential for societies. Their proper operation has to be preserved to face any perturbation or disruption. It is therefore of paramount importance that the modeling and quantification of the resilience of such networks are addressed to ensure an acceptable level of service even in the presence of disruptions. The paper aims at characterizing network resilience through weighted degree centrality. To do so, a real dataset issued from probe vehicle data is used to weight the graph by the traffic load. In particular, a set of disrupted situations retrieved from the study dataset is analyzed to quantify the impact on network operations. Results demonstrate the ability of the proposed metrics to capture traffic dynamics as well as their utility for quantifying the resilience of the network. The proposed methodology combines different metrics from the complex networks theory (i.e., heterogeneity, density, and symmetry) computed on temporal and weighted graphs. Time-varying traffic conditions and disruptions are analyzed by providing relevant insights on the network states via three-dimensional maps.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T11:54:42Z
      DOI: 10.1177/0361198121998663
       
  • Exploring the Different Patterns for Generation Process of Driving Fatigue
           Based on Individual Driving Behavior Parameters
    • Authors: Zhibiao Peng, Jian Rong, Yiping Wu, Chenjing Zhou, Yuan Yuan, Xiansheng Shao
      Abstract: Transportation Research Record, Ahead of Print.
      Driving fatigue is one of the main causes of traffic accidents in monotonous environments such as grassland highways. However, the process of generation of driving fatigue on grassland highways is still not clear. A driving simulation experiment with 23 participants was performed to collect data on driving behavior, reaction time and electrocardiogram (ECG) results when driving on a grassland highway. The effective feature indicators of driving fatigue based on driving behavior data were calculated by Pearson correlation coefficient and principal component analysis method. The matter-element model based on entropy weight method was used to quantify the generation process of driving fatigue (GPDF). GPDF was classified as different patterns by the eigenvalue of GPDF curves. Reaction time and ECG data were utilized to verify the rationality of GPDF. Results show that there were 13 feature indicators of driving behavior suitable for driving fatigue description. GPDF was not completely consistent among different participants and was classified into three patterns (i.e., mild, moderate and severe fatigue). The mean similarity for GPDF in each pattern was 0.87, 0.61 and 0.50. Validation test demonstrated that driving fatigue detection accuracy by GPDF was 72%. The mean similarity of the GPDF between driving behavior and ECG was 0.72. Driving fatigue tended to occur with driving time of 19 min or 33 min. This study is helpful to understand GPDF on grassland highways from the perspective of individual driving behavior, which would provide suggestions for the reasonable setting of anti-fatigue devices.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T11:49:54Z
      DOI: 10.1177/0361198121998351
       
  • Examining Correlation and Trends in Seatbelt Use among Occupants of the
           Same Vehicle using a Bivariate Probit Model
    • Authors: Meghna Chakraborty, Harprinderjot Singh, Peter T. Savolainen, Timothy J. Gates
      Abstract: Transportation Research Record, Ahead of Print.
      Research has consistently demonstrated that seatbelt use is critically important in reducing the likelihood of fatal and serious injuries resulting from traffic crashes. However, after years of nationwide increases in seatbelt use, these rates have largely plateaued, motivating the need for research to better understand those circumstances under which seatbelt use remains relatively low. At an aggregate level, research has shown that occupants in the same vehicle tend to exhibit correlation in seatbelt use or non-use. This suggests that social dynamics may play a role in occupants’ decisions as to whether or not to wear a seatbelt. To that end, this study examines trends in seatbelt use among pairs of drivers and front-seat passengers using data from direct observation roadside surveys. Bivariate probit models are estimated to examine the relationship between seatbelt use and various demographic, vehicle, and site-specific factors. The bivariate framework is also able to account for correlation among important unobserved factors associated with seatbelt use. The results show significantly better fit as compared with independent univariate probit models. The results also suggest both direct and indirect relationships between seatbelt use and various demographic, vehicle, and site characteristics. Seatbelt use rates are found to vary based on occupants’ age, gender, and race. Furthermore, seatbelt use by both the driver and front-seat passenger is also shown to vary based on the other occupant’s age. Heterogeneity is also shown across various geographic regions and roadway functional classes.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T11:47:35Z
      DOI: 10.1177/0361198121995487
       
  • Evaluation of Strategies to Mitigate Culvert-Involved Crashes
    • Authors: Hitesh Chawla, Megat-Usamah Megat-Johari, Peter T. Savolainen, Christopher M. Day
      Abstract: Transportation Research Record, Ahead of Print.
      The objectives of this study were to assess the in-service safety performance of roadside culverts and evaluate the potential impacts of installing various safety treatments to mitigate the severity of culvert-involved crashes. Such crashes were identified using standard fields on police crash report forms, as well as through a review of pertinent keywords from the narrative section of these forms. These crashes were then linked to the nearest cross-drainage culvert, which was associated with the nearest road segment. A negative binomial regression model was then estimated to discern how the risk of culvert-involved crashes varied as a function of annual average daily traffic, speed limit, number of travel lanes, and culvert size and offset. The second stage of the analysis involved the use of the Roadside Safety Analysis Program to estimate the expected crash costs associated with various design contexts. A series of scenarios were evaluated, culminating in guidance as to the most cost-effective treatments for different combinations of roadway geometric and traffic characteristics. The results of this study provide an empirical model that can be used to predict the risk of culvert-involved crashes under various scenarios. The findings also suggest that the installation of safety grates on culvert openings provides a promising alternative for most of the cases where the culvert is located within the clear zone. In general, a guardrail is recommended when adverse conditions are present or when other treatments are not feasible at a specific location.
      Citation: Transportation Research Record
      PubDate: 2021-03-18T11:46:03Z
      DOI: 10.1177/0361198121992070
       
  • Investigation of Breaking Points in the Airline Industry with Airline
           Optimization Studies Through Text Mining before the COVID-19 Pandemic
    • Authors: Metehan Atay, Yunus Eroğlu, Serap Ulusam Seçkiner
      Abstract: Transportation Research Record, Ahead of Print.
      In this study, current literature in the field of airline optimization has been examined by the text mining method to understand trends and commercial threats in the airline industry. Prominent types of work and popular topics have been revealed to understand the importance of global events. This research summarizes trends and some important points relating to airline optimization. The results are striking. It analyzes studies conducted on behalf of aviation before the global COVID-19 pandemic. The economic contribution made by the aviation sector as well as the costs it suffers as a result of crisis situations are clearly explained. Reasons for differences in studies conducted by different countries in the field of aviation are also explained. This study is intended to give an idea of how the aviation sector shapes academic studies, how studies on aviation optimization could contribute in the future, and how the countries have addressed important challenges to the aviation industry in the past.
      Citation: Transportation Research Record
      PubDate: 2021-03-17T12:59:29Z
      DOI: 10.1177/0361198120987238
       
  • Automatic Vehicle Counting and Tracking in Aerial Video Feeds using
           Cascade Region-based Convolutional Neural Networks and Feature Pyramid
           Networks
    • Authors: Yomna Youssef, Mohamed Elshenawy
      Abstract: Transportation Research Record, Ahead of Print.
      Unmanned aerial vehicles, or drones, are poised to solve many problems associated with data collection in complex urban environments. Drones are easy to deploy, have a great ability to move and explore the environment, and are relatively cheaper than other data collection methods. This study investigated the use of Cascade Region-based convolutional neural network (R-CNN) networks to enable automatic vehicle counting and tracking in aerial video streams.The presented technique combines feature pyramid networks and a Cascade R-CNN architecture to enable accurate detection and classification of vehicles.The paper discusses the implementation and evaluation of the detection and tracking techniques and highlights their advantages when they are used to collect traffic data.
      Citation: Transportation Research Record
      PubDate: 2021-03-17T01:02:54Z
      DOI: 10.1177/0361198121997833
       
  • Review of Key Findings and Future Directions for Assessing Equitable
           Cycling Usage
    • Authors: Danial Jahanshahi, Subeh Chowdhury, Seosamh B. Costello, Bert van Wee
      Abstract: Transportation Research Record, Ahead of Print.
      Research studies on mode shift toward sustainable transport, particularly cycling, have become more common in the last decade. Despite some success in increasing cycling usage, there exist many barriers, both environmental and societal. This study provides a review of the key equity findings to date in cycling usage and identifies knowledge gaps. Barriers to cycling from an equity perspective are examined from three perspectives: policy and planning, infrastructure and cycling facilities, and population groups. The review includes both peer-reviewed and grey papers. Using a systematic review process, out of 73 documents, 33 which met the scope of the study were carefully examined. The review showed that accessibility is the most common measure for bicycling equity. A key knowledge gap is the lack of robust measures to determine inequities in cycling and evaluate the distribution of benefits across population groups. This is attributed to the lack of measures to effectively evaluate a program or policy from an equity perspective. Consequently, this review emphasizes the need to develop and evaluate equity measures for effective policymaking, to ensure that the needs of different population groups are met. The paper concludes with recommendations for future research, given the identified knowledge gaps.
      Citation: Transportation Research Record
      PubDate: 2021-03-17T01:01:31Z
      DOI: 10.1177/0361198121995193
       
  • Pedestrian Traffic Signal Data Accurately Estimates Pedestrian Crossing
           Volumes
    • Authors: Patrick A. Singleton, Ferdousy Runa
      Abstract: Transportation Research Record, Ahead of Print.
      Existing methods of pedestrian travel monitoring are generally inefficient for collecting pedestrian data in many locations over long time periods. In this study, we demonstrate the validity of using a novel and relatively ubiquitous big data source—pedestrian data from high-resolution traffic signal controller logs—as a way of estimating pedestrian crossing volumes. Every time a person presses a pedestrian push button or a pedestrian call is registered at a signal, this information can be logged and archived. To validate these pedestrian signal data against observed pedestrian counts, we recorded over 10,000 h of video at 90 signalized intersections in Utah, and counted around 175,000 people walking. For each hour and crossing, we compared these observed counts to measures of pedestrian activity calculated from traffic signal data, using a set of five simple piecewise linear and quadratic regression models. Overall, our results show that traffic signal data can be successfully used to estimate pedestrian crossing volumes with good accuracy: model-predicted volumes were strongly correlated (0.84) with observed volumes and had a low mean absolute error (3.0). We also demonstrate how our models can be used to estimate annual average daily pedestrian volumes at signalized intersections and identify high pedestrian volume locations. Transportation agencies can use pedestrian signal data to help improve pedestrian travel monitoring, multimodal transportation planning, traffic safety analyses, and health impact assessments.
      Citation: Transportation Research Record
      PubDate: 2021-03-15T09:01:38Z
      DOI: 10.1177/0361198121994126
       
  • Protocol to Assess the Impact of Crude Oil Price Fluctuations on Future
           Asphalt Prices
    • Authors: Kaylyn M. Cardinal, Mohamed Khalafalla, Jorge Rueda-Benavides
      Abstract: Transportation Research Record, Ahead of Print.
      It is clear for the transportation industry that asphalt prices are heavily affected by changes in the crude oil market. This occurs because asphalt is a byproduct of the process of refining crude oil. However, there is still a lack of research on assessing the economic implications of this relationship. This paper assesses those implications through an innovative statistical process designed to quantify the economic correlation between asphalt and crude oil price fluctuations in Alabama. The proposed statistical process is used in this paper to model the relationship between the Alabama Department of Transportation’s (ALDOT’s) monthly asphalt price index and a national crude oil index published by the US Energy Information Administration. The process quantifies the relationship between these two commodities in relation to two metrics: (1) the time gap between an observed change in the crude oil index and its corresponding impact on the asphalt price index and (2) the magnitude of that impact. It was found that the most likely time gap between crude oil and asphalt price fluctuations in Alabama is 3 months, with a change ratio of 0.58. This means that a 1% increase in the price of crude oil would most likely affect the Alabama asphalt market 3 months later with a price increase of about 0.58%. Recognizing that these are just average values, the paper also presents a risk assessment tool that provides ALDOT with the probability of occurrence of different scenarios taking into consideration the observed variability in time gaps and change ratios.
      Citation: Transportation Research Record
      PubDate: 2021-03-15T08:58:55Z
      DOI: 10.1177/0361198121992072
       
  • Optimized Railway Track Condition Monitoring and Derailment Prevention
           System Supported by Cloud Technology
    • Authors: C. Chellaswamy, T. S. Geetha, M. Surya Bhupal Rao, A. Vanathi
      Abstract: Transportation Research Record, Ahead of Print.
      This paper describes an easy way to monitor railway track abnormalities and update information on the track’s status to the cloud. Abnormalities present in railway tracks should be identified promptly and rectified to ensure safe and smooth travel. In this paper, a cloud-based track monitoring system (CTMS) is proposed for the monitoring of track conditions. The micro-electro mechanical systems (MEMS) accelerometers which are mounted in the axle are used to measure the railway track abnormality. The measured signal is optimized using the flower pollination optimization algorithm (FPOA). Because of signaling problems in the global positioning system (GPS), it is difficult to estimate the exact location of the abnormality in real time. A new method is introduced to overcome this problem. It provides the location of an abnormality even when the GPS signal is absent. The performance of the CTMS is compared with three different speed scenarios of the vehicle. The information about the abnormality on the track can be shared with other trains that pass through the same location so that the driver can reduce speed in that location to avoid derailment. Finally, an experimental setup was developed and the performance of CTMS is studied under four different irregularity cases.
      Citation: Transportation Research Record
      PubDate: 2021-03-15T08:55:13Z
      DOI: 10.1177/0361198120980438
       
  • Quantifying Environmental Benefits of Ridesplitting based on Observed Data
           from Ridesourcing Services
    • Authors: Xinghua Liu, Wenxiang Li, Ye Li, Jing Fan, Zhiyong Shen
      Abstract: Transportation Research Record, Ahead of Print.
      The increasing emissions from the transportation sector pose substantial hazards to the environment and human health around the world. With the rapid development of information and communication technologies, ridesplitting, a form of ridesourcing service accessed via smartphone applications, enables passengers with similar origins and destinations to be matched to the same driver and share the ride. This is regarded as a promising travel mode that could mitigate air pollution. However, because of a lack of quantitative analysis, the environmental benefits of ridesplitting have not been rigorously justified. As vast amounts of observed data of ridesourcing have become increasingly available, this study quantifies the environmental benefits of ridesplitting based on the global positioning system (GPS) trajectory and trip order datasets of DiDi Chuxing in Chengdu, China. First, the saved distances of ridesplitting are calculated by analyzing the travel distances of both ridesplitting trips and the corresponding trips under non-ridesplitting conditions. Then, the emission factors of CO, NOx, and HC are estimated by a localized MOVES model. Combining the saved distances and emission factors, the emission reductions from each ridesplitting trip can be calculated. The results show that ridesplitting can decrease the travel distance by 22% on average compared with non-ridesplitting. As a consequence, the average emission reductions per ridesplitting trip are 10.601 g of CO, 0.691 g of NOx, and 1.424 g of HC, respectively. This study provides a better understanding of the environmental benefits of ridesplitting and theoretical guidance for the government’s decision-making in green transport planning.
      Citation: Transportation Research Record
      PubDate: 2021-03-12T12:26:43Z
      DOI: 10.1177/0361198121997827
       
  • Assessing the Impact of Geosynthetic Interlayers on Laboratory Cracking
           and Delamination of Hot-Mix Asphalt Mixtures
    • Authors: Sean Cullen, Daniel Offenbacker, Ayman Ali, Yusuf Mehta, Christopher Decarlo, Mohamed Elshaer
      Abstract: Transportation Research Record, Ahead of Print.
      This study evaluated the impact of geosynthetic interlayers on crack retardation and delamination within hot-mix asphalt mixtures. Five different geosynthetic interlayers (three geogrids, one geotextile, and one geocomposite) were considered in this study and varied in opening size, tensile strength, and bonding additive. Two asphalt binder tack coats—PG 64-22 and PG 76-22—were selected and applied at a rate of 0.95 L/m2 (0.21 gal/yd2) based on literature and manufacturer recommendations. Three-point bending (3PB) tests were conducted to assess the cracking and delamination resistance of geosynthetic interlayers. Digital images were recorded during 3PB testing and analyzed using digital image correlation to track specimen movements at the interface under flexural loading. The results showed that specimens with geosynthetic interlayers had higher fracture energy and slower crack propagation rates compared with control specimens. More specifically, fiberglass geogrid interlayers showed the greatest ability to retard crack propagation, with crack propagation rates of 0.07 mm per second (mm/s) compared with control (0.14 mm/s) and other geosynthetics (between 0.08 mm/s and 0.10 mm/s). With respect to delamination, control two-lift and geotextile interlayer (GTX-P) specimens showed the least amount of horizontal delamination. When evaluating the rate at which delamination spread, geotextile specimens (GTX-P) and geocomposite specimens showed slower spread of delamination compared with geogrid interlayers. Overall, the results from this study showed the use of geosynthetic interlayers improved cracking resistance and caused little to no delamination along the asphalt interface.
      Citation: Transportation Research Record
      PubDate: 2021-03-11T12:23:13Z
      DOI: 10.1177/0361198121996712
       
  • Evaluating the Quality of Curing Applications on Concrete Pavements with
           Ground-Penetrating Radar
    • Authors: Alireza Joshaghani, Dan G. Zollinger
      Abstract: Transportation Research Record, Ahead of Print.
      The management of concrete pavement curing must take several factors into account, such as the type of curing compound, the rate of the curing application, the uniformity of the curing application, the timing of the application, and the ambient weather conditions. This paper aims to elucidate a new curing application protocol for new concrete pavement construction and introduce a technique to address curing viability. Data for the development of the protocol were obtained from field investigations involving a series of test sections associated with concrete paving projects in: Victoria, TX; Itasca, IL; and Jacksonville, FL. For this undertaking, ground-penetrating radar technology was used to evaluate the efficacy of curing in relation to repeatability and uniformity. Statistical analysis was used to validate the utility of using dielectric measurements to qualify the curing quality. The rate of decrease in the dielectric constant was the critical parameter for evaluating a curing practice. Also, based on the coefficient of variation of data collection, the repeatability of data was acceptable. Finally, as a new method for checking the uniformity of curing applications, percent within limits (PWL) was implemented. Based on the PWL results, the hand-spraying led to a higher degree of non-uniformity in the spraying patterns compared with the spraying machine.
      Citation: Transportation Research Record
      PubDate: 2021-03-11T12:20:53Z
      DOI: 10.1177/0361198121996361
       
  • Free Transit Passes and School Attendance among High School Students
    • Authors: Noah Wexler, Galen Ryan, Kirti Das, Yingling Fan
      Abstract: Transportation Research Record, Ahead of Print.
      In multiple U.S. cities, school districts and transit providers collaborate to provide students free public transit access, either replacing or supplementing the yellow school bus service. Although practitioners widely acknowledge these programs as a promising and innovative solution to absenteeism, there is no empirical research evidence to date confirming the benefits of these programs to individual students’ school attendance. We respond to this research gap by investigating the impacts of the Minneapolis Go-To Student Pass Program—a transportation program that began to provide student access to public transit in August 2013—on individual student school attendance. Using Poisson regression, we estimate both the traditional Difference-in-differences models and Two-Way Fixed Effects models to quantify effects of pass use and pass eligibility on student attendance. We find that student-reported pass use and pass eligibility reduce excused absences by 11.5% and 27.5%, respectively. Restricting our sample to students living in the School Walk Zone—the area within 2 mi of one’s school—we find that these effects are even more substantial, with pass use and pass eligibility reducing excused absences by 30.5% and 37.6% respectively. These findings imply that providing free access to public transit is broadly useful to improve student attendance, even for students who live within walking distance of the school and may not use transit passes regularly.
      Citation: Transportation Research Record
      PubDate: 2021-03-11T12:18:13Z
      DOI: 10.1177/0361198121996360
       
  • Forensic Analyses and Rehabilitation of a Failed Highway Embankment Slope
           in Texas
    • Authors: Burak Boluk, Anand J. Puppala, Sayantan Chakraborty, Puneet Bhaskar
      Abstract: Transportation Research Record, Ahead of Print.
      A comprehensive investigation was designed and conducted to identify the potential causes of failure of a highway embankment slope in Texas and evaluate the effectiveness of lime treatment to rehabilitate the failed slope. Highway slopes built with high plasticity clays often experience shallow slope failures after exposure to repeated wet–dry weathering cycles. Lime stabilization generally reduces the swell–shrink potential, enhances the engineering properties of problematic clayey soils, and can potentially prevent surficial slope failures. However, exposure to wet–dry cycles can negate some of the benefits of lime treatment and therefore a study was conducted to address the use of this lime treatment to stabilize embankment slopes. Extensive laboratory tests were conducted to study the effect of weathering cycles on the degradation of hydro-mechanical properties of untreated and lime-treated soils. Rainfall-induced slope stability analyses were performed to investigate the probable causes of slope failure and evaluate the stability of lime-treated surficial slope. The optimum stabilizer dosage and treated layer thickness required for the slope rehabilitation were determined based on laboratory tests and numerical analysis results. The stability analysis results indicate that the degradation of surficial soil’s hydro-mechanical properties and the development of a perched water table during prolonged rainfall possibly caused the slope failure. The post-treatment increase in shear strength properties, reduction in moisture fluctuations recorded by embedded moisture sensors, and the presence of newly installed underlying drains are expected to prevent recurrence of surficial slope failures. Salient results from this study are covered in this paper.
      Citation: Transportation Research Record
      PubDate: 2021-03-11T12:15:53Z
      DOI: 10.1177/0361198121996359
       
  • Assessing the Impacts of Weather on Pedestrian Signal Activity at 49
           Signalized Intersections in Northern Utah
    • Authors: Ferdousy Runa, Patrick A. Singleton
      Abstract: Transportation Research Record, Ahead of Print.
      A deeper understanding of how weather variables affect pedestrian volumes is important, as active travelers are an essential part of a sustainable transportation system. Pedestrian data are limited for investigating the impacts of weather on walking levels, with most studies having data at only a couple of locations. Pedestrian actuation data (from push-buttons at traffic signals) overcomes this limitation. The Utah Department of Transportation archives pedestrian push-button press data for use in its Automated Traffic Signal Performance Measures system. In this study, pedestrian actuation data was used as a proxy for walking activity and weather data was collected from the National Oceanic and Atmosphere Administration. Using 15 months of daily time series data in Cache County, the impacts of weather on pedestrian signal activity were examined at 49 signalized intersections, using a log-linear time series regression analysis with categorical step-wise weather variables. The findings revealed that snow depth had the most frequent negative effect on walking activity. Snowfall (> 0.6 in.) also tended to have negative impacts when significant. Very hot maximum temperatures (≥ 90°F) were associated with lower pedestrian activity at around one-third of signals. Very low minimum temperatures (
      Citation: Transportation Research Record
      PubDate: 2021-03-11T12:13:32Z
      DOI: 10.1177/0361198121994111
       
  • Adaptive Differential Evolution Optimization-Based Noise-Level Measurement
           for High-Speed Railways
    • Authors: R. Ganesh Babu, C. Chellaswamy, T. S. Geetha
      Abstract: Transportation Research Record, Ahead of Print.
      This paper deals with the possibilities of estimating noise pollution created by high-speed railway systems in nearby locations. Railway systems have significant effects on the environment. Therefore, a college campus situated near a high-speed railway was selected as the study area. In this paper, an adaptive differential evolution optimization (ADEO) algorithm-based noise-level measurement is proposed. Various measurements such as the noise levels indoors, outdoors, and near the track were carried out in the college area and applied to ADEO for optimization. A study of the impact of railway noise on student learning was made. ADEO was used to predict the maximum noise level and the maximum noise distribution in the college area through the model. An experimental study was performed, and the results were compared with the estimated results. The results indicated the consistency of both the estimated and experimental results and the error as less than 1 dBA; the noise level exceeded 65 dBA in a few classrooms. Therefore, the proposed noise measurement for high-speed railway based on the ADEO technique has been considered as the most effective and superior optimization tool.
      Citation: Transportation Research Record
      PubDate: 2021-03-11T12:11:49Z
      DOI: 10.1177/0361198120983008
       
  • Assessing the Elastic Moduli of Pavement Marking Tapes using the Tape
           Drape Test
    • Authors: Mitchell L. Rencheck, Jared A. Gohl, Hugh P. Grennan, Kendra A. Erk, Chelsea S. Davis
      Abstract: Transportation Research Record, Ahead of Print.
      Temporary pavement marking (TPM) tape adhesion with roadway surfaces is critical for tape performance. The two main TPM performance issues both stem from the adhesive strength. Weak adhesion results in premature detachment and excessive adhesion requires extensive removal processes that often leave ghost markings, both of which can cause dangerous confusion in road construction zones. Tape adhesion is directly related to the elastic modulus [math] of TPM tapes. Thus, accurate characterization of [math] before tape installation is essential to fully understand and predict the adhesion performance and ultimately the durability of TPMs. To determine the most appropriate [math] characterization technique for three different commercial TPM tape brands, two commonly used techniques—tensile and three-point bend testing—were compared with a less common technique, the Peirce cantilever testing or “Tape Drape Test” (ASTM D1388-18). The Tape Drape Test was the only method that accurately characterized [math] of tapes with raised surface features. Measured [math] values from tensile and three-point bend testing showed significant variation caused by the structural features of the tapes. The Tape Drape Test, which can be implemented quickly in the field before tape installation with little equipment, effectively characterized [math] for all the tapes to inform tape adhesion performances and installation procedures.
      Citation: Transportation Research Record
      PubDate: 2021-03-11T01:10:42Z
      DOI: 10.1177/0361198121999623
       
  • Optimizing Right-Turn Signals to Benefit Pedestrian–Vehicle
           Interactions
    • Authors: Jiawen Wang, Chengcheng Yang, Jieshuang Dong, Xizhao Zhou
      Abstract: Transportation Research Record, Ahead of Print.
      In most right-driving urban signalized intersections, right-turn vehicle signals do not usually control turns. To address the problem of signal control in a pedestrian–vehicle interaction, this paper establishes a right-turn signal optimization (RTSO) model that considers both efficiency and safety. First, the main factors influencing the behavior of vehicle and pedestrian during pedestrian–vehicle interaction are analyzed, and a pedestrian–vehicle interaction model (PVI model) at an urban road crosswalk is established. This model is used to determine the probabilities of four pedestrian–vehicle interaction situations. Then, based on the traffic conflict theory, the next step was to construct an objective function that minimizes the total delay of traffic participants considering pedestrian–vehicle interactions, and another objective function that minimizes the potential conflicts considering pedestrian–vehicle interactions. Then, an RTSO model is obtained by introducing a safety-efficiency coefficient to combine the previously described two constructed functions. Finally, the PVI model and delay model are verified through video observation data and the establishment of a cellular automata simulation platform of pedestrian–vehicle interaction. Using these models, a field signal plan, the delay minimization scheme, the conflict minimization scheme, and the proposed scheme are numerically analyzed under different yielding rates. This proposed scheme is further numerically analyzed under different safety-efficiency coefficients. The results show that this paper’s RTSO model has certain advantages in increasing safety and reducing delay. In addition, using these results, this paper gives a recommended value for the safety-efficiency coefficients in different application scenarios.
      Citation: Transportation Research Record
      PubDate: 2021-03-10T12:40:48Z
      DOI: 10.1177/0361198121995511
       
  • Critical Station Practical Capacity on a Bus Rapid Transit Line with
           Nonstopping Buses
    • Authors: Jonathan M. Bunker, Faheema Hisham
      Abstract: Transportation Research Record, Ahead of Print.
      Bus rapid transit (BRT) can offer transit mobility to meet growing travel demands by cost-effectively providing high capacity and quality of service. It is adaptable to a wide range of operating conditions and technological advancements. Stations are elements that typically control BRT line capacity, so it is essential to understand the operation of any potentially critical station to understand and manage the facility. The Transit Capacity and Quality of Service Manual (TCQSM) provides the standard methodology for capacity estimation. However, that model does not account for important operational aspects including the stochastic nature of many parameters beyond dwell time, along with nonstopping buses’ capacity, the degrees of saturation of the stopping and nonstopping bus streams, and the upstream average waiting time and queue length of stopping buses. We adapted the theory developed by Hisham et al. for an onstreet bus stop, to reflect the operational conditions of a BRT station and to account for these aspects. This new reliability-based capacity model tailored to BRT facilities provided superior insight into station bus capacity and quality of service to the TCQSM model.
      Citation: Transportation Research Record
      PubDate: 2021-03-09T11:44:33Z
      DOI: 10.1177/0361198121999397
       
  • Non-Linear Evaluation Model to Analyze Saturation Flow under
           Weak-Lane-Disciplined Mixed Traffic Stream
    • Authors: Satyajit Mondal, Ankit Gupta
      Abstract: Transportation Research Record, Ahead of Print.
      Saturation flow is an essential parameter for the performance evaluation and signal cycle design of an intersection. However, in a weak-lane-disciplined mixed traffic stream, vehicles (mainly motorized two- and three-wheelers) are more interested in forming queues with the behavior of creeping and infiltration through the larger vehicles for a quick dispersion. Consequently, a high rate of discharge can be found in the first few seconds of green, followed by a wavering discharge pattern to the end of the green period. In this context, the present study frames a non-linear evolutionary model (NLEM) to analyze passenger car unit (PCU) and saturation flow value by minimizing the vehicle encroachment and wavering in discharge for mixed traffic stream. Field traffic data was collected from 10 signalized intersections from three different cities of India. The NLEM considers the vehicle discharge during the saturated green interval in the optimization process to analyze PCU and saturation flow value. The result indicates an appropriate estimation of PCU and saturation flow concerning the Highway Capacity Manual. The discharge profile obtained using the proposed model also specifies the model’s aptness in analyzing the effect of vehicle encroachment and wavering throughout the green period. Thus, the proposed NLEM is probably suitable for analyzing the PCU and saturation flow of an intersection where vehicle interaction is sensitive because of a mixed scenario.
      Citation: Transportation Research Record
      PubDate: 2021-03-08T06:25:53Z
      DOI: 10.1177/0361198121998370
       
  • Bender Element Field Sensor for the Measurement of Pavement Base and
           Subbase Stiffness Characteristics
    • Authors: Mingu Kang, Issam I. A. Qamhia, Erol Tutumluer, Won-Taek Hong, Jeb S. Tingle
      Abstract: Transportation Research Record, Ahead of Print.
      Layer modulus values are important input parameters in mechanistic pavement design and evaluation methods. Direct measurement of the stiffness characteristics of pavement base/subbase has been a challenging task. Nondestructive testing methods that are commonly used based on surface deflection measurements not only require a backcalculation process, but also have limitations on measuring local stiffness within the layer. This paper presents the result of a recent research effort at the University of Illinois aimed to develop a new sensor for the direct measurement of the in-situ moduli of constructed unbound pavement layers. The new sensor employs bender element (BE) shear wave transducers embedded in a granular base/subbase to evaluate the layer modulus from shear wave velocity measured at any depth and any orientation. To provide appropriate protection for the BE sensor and its cable connections, a stainless-steel cable guide, a sensor protection module, and a protection cover for the sensor were designed and optimized. A laboratory calibration box containing sand-sized crushed aggregates was used in the development stage of the BE sensor design. The BE sensor results were also studied for a typical dense-graded base course aggregate commonly used in Illinois. Finally, the BE sensor was installed in a field trial in newly constructed airport pavement test sections, and its layer modulus measurements were compared with results estimated from Dynamic Cone Penetrometer testing. The new BE field sensor has proven to be a viable direct measurement technique in transportation geotechnics applications to monitor stiffness characteristics of pavement granular base/subbase layers.
      Citation: Transportation Research Record
      PubDate: 2021-03-05T12:59:14Z
      DOI: 10.1177/0361198121998350
       
  • Using Deep Learning to Understand Travel Demands in Different Urban
           Districts
    • Authors: Shunhua Bai, Junfeng Jiao
      Abstract: Transportation Research Record, Ahead of Print.
      Travel demand forecast plays an important role in transportation planning. Classic models often predict people’s travel behavior based on the physical built environment in a linear fashion. Many scholars have tried to understand built environments’ predictive power on people’s travel behavior using big-data methods. However, few empirical studies have discussed how the impact might vary across time and space. To fill this research gap, this study used 2019 anonymous smartphone GPS data and built a long short-term memory (LSTM) recurrent neural network (RNN) to predict the daily travel demand to six destinations in Austin, Texas: downtown, the university, the airport, an inner-ring point-of-interest (POI) cluster, a suburban POI cluster, and an urban-fringe POI cluster. By comparing the prediction results, we found that: the model underestimated the traffic surge for the university in the fall semester and overestimated the demand for downtown on non-working days; the prediction accuracy for POI clusters was negatively related to their adjacency to downtown; and different POI clusters had cases of under- or overestimation on different occasions. This study reveals that the impact of destination attributes on people’s travel demand can vary across time and space because of their heterogeneous nature. Future research on travel behavior and built environment modeling should incorporate the temporal inconsistency to achieve better prediction accuracy.
      Citation: Transportation Research Record
      PubDate: 2021-03-05T12:57:12Z
      DOI: 10.1177/0361198121994582
       
  • Structural Performance of Sections Treated with Thin Overlays for Pavement
           Preservation
    • Authors: Md Rahman, Adriana Vargas-Nordcbeck
      Abstract: Transportation Research Record, Ahead of Print.
      Over the last decades, increased efforts have been made to identify cost-effective alternatives to achieve a longer pavement life by applying preservation treatments. The application of thin overlays to restore the surface condition of the pavement is widely practiced across the United States. Benefits include a long service life, a better riding surface, reduced noise, grade and slope geometry preservation, recyclability, and fewer maintenance regimes. Although thin overlays can provide significant improvements in both the immediate and long-term functional performance of the pavement, there is little information on how these treatments affect the structural performance of pavements. Although not expected to significantly improve structural capacity, thin overlays may be able to maintain a structurally sound pavement in good condition for longer. The objective of this study was to evaluate the structural performance of pavements treated with thin overlays as a preservation technique. To accomplish this objective, falling weight deflectometer and field performance data from six full-scale thin overlay test sections and a control section with high cracking were collected and analyzed over a period of nearly 8 years. The results indicated that, based on deflection basin parameters (DBPs), the treated sections had better performance and were projected to reach the “warning” zone much later than the untreated sections. The observed surface condition correlated well with these parameters as, in general, sections with higher DBPs also exhibited more cracking and rutting. The test sections continue to be monitored to fully quantify the extent of the structural benefit obtained from the treatments.
      Citation: Transportation Research Record
      PubDate: 2021-03-05T12:56:53Z
      DOI: 10.1177/0361198121997816
       
  • Experimental Investigation into Driver Behavior along Curved and Parallel
           Diverging Terminals of Exit Interchange Ramps
    • Authors: Alberto Portera, Marco Bassani
      Abstract: Transportation Research Record, Ahead of Print.
      Current design manuals provide guidance on how to design exit ramps to facilitate driving operations and minimize the incidence of crashes. They also suggest that interchanges should be built along straight roadway sections. These criteria may prove ineffective in situations where there is no alternative to terminals being located along curved motorway segments. The paper investigates driving behavior along parallel deceleration curved terminals, with attention paid to the difference in impact between terminals having a curvature which is the same sign as the motorway segment (i.e., continue design), and those having an opposite curvature (i.e., reverse design). A driving simulation study was set up to collect longitudinal and transversal driver behavioral data in response to experimental factor variations. Forty-eight drivers were stratified on the basis of age and gender, and asked to drive along three randomly assigned circuits with off-ramps obtained by combining experimental factors such as motorway mainline curve radius (2 values), terminal length (3), curve direction (2), and traffic conditions (2). The motorway radius was found to be significant for drivers’ preferred speed when approaching the terminal. Terminal length and traffic volume do not have a significant impact on either longitudinal or transversal driver outputs. However, the effect of curve direction was found to be significant, notably for reverse terminals which do not compel drivers to select appropriate speeds and lane change positions. This terminal type can give rise to critical driving situations that should be considered at the design stage to facilitate the adoption of appropriate safety countermeasures.
      Citation: Transportation Research Record
      PubDate: 2021-03-04T11:57:00Z
      DOI: 10.1177/0361198121997420
       
  • Cross-National Focus Group Response to Autonomous Vehicles
    • Authors: Thomas A. Norton, Melissa Ruhl, Tim Armitage, Brian Matthews, John Miles
      Abstract: Transportation Research Record, Ahead of Print.
      The development of autonomous vehicles (AVs) is advancing quickly in some enclaves around the world. Consequently, AVs exist in the public consciousness, featuring regularly in mainstream media. As the form and function of AVs emerge, the attitudes of potential users become more important. The extent to which the public trusts AV technology and anticipates benefits, will drive consumer willingness to use AVs. Broadly, public attitudes will determine whether AVs can attract public investment in infrastructure and become a feature of the future transport mix or fail to realize the potential their developers assert. As part of UK Autodrive, a program trialing the introduction of AVs in the United Kingdom, researchers conducted focus groups in five UK cities, and a comparison focus group in San Francisco (December 2017 to September 2018) using representative samples (total n = 137). Focus group facilitators guided discussions in three areas considered central to usage decisions: trust in the technology, ownership models, and community benefit. This paper describes findings from a quasi-quantitative study supported with qualitative insights. This research provides three key takeaways centering on trust in the technology and in delivering benefit. First, some participants gain trust through experience and others through evidence. Second, participants had difficulty discriminating between AV developers, indicating a need for industry cooperation. Third, partnerships were found to demonstrate trust, highlighting the need for more and deeper partnerships moving forward. Generally, participants had positive attitudes toward AVs and expect AVs to provide benefits. However, these attitudes and expectations could change as AV development progresses.
      Citation: Transportation Research Record
      PubDate: 2021-03-03T12:52:35Z
      DOI: 10.1177/0361198121992363
       
  • Levels of Uncertainty in Infrastructure Asset Management
    • Authors: Amir R. Hessami, Stuart D. Anderson, Roger E. Smith
      Abstract: Transportation Research Record, Ahead of Print.
      The management of infrastructure assets is often challenged by uncertain factors such as changing weather trends and usage patterns. To reliably maintain the assets above a specified level of service, the extent of this uncertainty should be identified, and adequate methods for analyzing the risk factors should be implemented. The analysis of risk is well-defined in the field of strategic management. In the current study, four levels of uncertainty that are widely discussed in strategic management were used as a benchmark to determine the levels of uncertainty in infrastructure asset management. These levels range from known issues, to statistically predictable factors, to complete indeterminacy. The current methods of treating uncertainty in infrastructure asset management were reviewed to determine how they overlap with the four levels of uncertainty and whether or not asset managers handle this uncertainty in an optimal fashion. The current approaches in asset management were found to be primarily deterministic and probabilistic. A shortcoming was found in regard to the incorporation of risk analysis into asset management planning for large-scale networks. The researchers concluded that the level of uncertainty present in asset management at the network planning level can be best described as a range and addressed through the use of representative scenarios within that range.
      Citation: Transportation Research Record
      PubDate: 2021-03-03T12:50:55Z
      DOI: 10.1177/0361198121991844
       
  • Methodology to Increase Flexibility in Inter-Region Flow Control for Urban
           Traffic
    • Authors: Sunghoon Kim, Monica Menendez, Hwasoo Yeo
      Abstract: Transportation Research Record, Ahead of Print.
      Perimeter control is used to regulate transfer flows between urban regions. The greedy control (GC) method takes either the minimum or the maximum for the control inputs. Although it has the advantage of simplicity for real-time feasibility, a few existing studies have shown that it can sometimes have negative impacts because of unnecessary transfer flow restrictions. To reduce unnecessary restrictions, this study provides a method that gives flexibility to ease the strict conditions of the conventional GC. First, we propose a modification as a way of granting exceptions to the flow restriction under specific conditions. Second, we develop an algorithm to determine the threshold dynamically for accepting the exception, by comparing the possible outflow loss of the subject region and the possible outflow gain of its neighboring regions. The test results show that this flexible greedy control can handle the balance between the transfer demands and the greed of regions for securing the supply level, while increasing the performance in both vehicle hours traveled and trip completion.
      Citation: Transportation Research Record
      PubDate: 2021-03-02T06:32:20Z
      DOI: 10.1177/0361198121997424
       
  • Continuous Approximation Model for Hybrid Flexible Transit Systems with
           Low Demand Density
    • Authors: Charalampos Sipetas, Eric J. Gonzales
      Abstract: Transportation Research Record, Ahead of Print.
      Flexible transit systems are a way to address challenges associated with conventional fixed route and fully demand responsive systems. Existing studies indicate that such systems are often planned and designed without established guidelines, and optimization techniques are rarely implemented on actual flexible systems. This study presents a hybrid transit system where the degree of flexibility can vary from a fixed route service (with no flexibility) to a fully flexible transit system. Such a system is expected to be beneficial in areas where the best transit solution lies between the fixed route and fully flexible systems. Continuous approximation techniques are implemented to model and optimize the stop spacing on a fixed route corridor, as well as the boundaries of the flexible region in a corridor. Both user and agency costs are considered in the optimization process. A numerical analysis compares various service areas and demand densities using input variables with magnitudes similar to those of real-world case studies. Sensitivity analysis is performed for service headway, percent of demand served curb-to-curb, and user and agency cost weights in the optimization process. The analytical models are evaluated through simulations. The hybrid system proposed here achieves estimated user benefits of up to 35% when compared with fixed route systems, under different case scenarios. Flexible systems are particularly beneficial for serving corridors with low or uncertain demand. This provides value for corridors with low demand density as well as communities in which transit ridership has dropped significantly because of the COVID-19 pandemic.
      Citation: Transportation Research Record
      PubDate: 2021-03-02T06:30:38Z
      DOI: 10.1177/0361198121997131
       
  • Recursive Bivariate Probit Analysis of Injury Severity and Non-Truck
           
    • Authors: Zhenyu Wang, Abhijit Vasili, Runan Yang, Pei-Sung Lin
      Abstract: Transportation Research Record, Ahead of Print.
      This study investigated the hierarchical connection among injury severity, non-truck improper actions, and contributing factors in large-truck-involved crashes. Data for 4 years (2011–2014) of crashes that involved a large truck (≥ 10,000 lb) and a non-truck vehicle were collected from suburban roads in Florida, U.S. A recursive bivariate probit model was fitted with collected data to identify the cause-effect chain, including contributing factors influenced by improper actions, the effects of improper actions on injury severity, and contributing factors indirectly affecting injury severity in large-truck-related crashes. Study results indicate that non-truck vehicle improper actions, such as excessive speed, careless driving, failure to yield right-of-way, and others, significantly increase the likelihood of fatal and severe injury in large-truck crashes, and factors such as crash month, darkness, intersection-related, surface and shoulder width, truck parking, truck driver age, non-truck driver age, and non-truck alcohol/drug impaired indirectly influence injury severity through their impacts on non-truck improper actions. Two factors—truck right-turn and non-truck driver physical defects—affect injury severity and non-truck improper actions simultaneously. Other factors, including crash year, annual average daily traffic, speed limit, crash type, truck type, truck speed, truck alcohol/drug-impaired, and motorcycle involvement, directly contribute to injury severity in large-truck crashes and have no influence on non-truck improper actions.
      Citation: Transportation Research Record
      PubDate: 2021-03-02T06:28:38Z
      DOI: 10.1177/0361198121997146
       
  • Establishing and Satisfying Thermal Requirements for Drilled Shaft
           Concrete Based on Durability Considerations
    • Authors: Andrew Z. Boeckmann, Zakaria El-tayash, J. Erik Loehr
      Abstract: Transportation Research Record, Ahead of Print.
      Some U.S. transportation agencies have recently applied mass concrete provisions to drilled shafts, imposing limits on maximum temperatures and maximum temperature differentials. On one hand, temperatures commonly observed in large-diameter drilled shafts have been observed to cause delayed ettringite formation (DEF) and thermal cracking in above-ground concrete elements. On the other, the reinforcement and confinement unique to drilled shafts should provide resistance to thermal cracking, and the provisions that have been applied are based on dated practices for above-ground concrete. This paper establishes a rational procedure for design of drilled shafts for durability requirements in response to hydration temperatures, which addresses both DEF and thermal cracking. DEF is addressed through maximum temperature differential limitations that are based on concrete mix design parameters. Thermal cracking is addressed through calculations that explicitly consider the thermo-mechanical response of concrete for predicted temperatures. Results from application of the procedure indicate consideration of DEF and thermal cracking potential for drilled shafts is prudent, but provisions that have been applied to date are overly restrictive in many circumstances, particularly the commonly adopted 35°F maximum temperature differential provision.
      Citation: Transportation Research Record
      PubDate: 2021-03-02T06:27:18Z
      DOI: 10.1177/0361198121996357
       
  • Advantages of Geophysics to Improve Site Characterization and Reliability
           for Transportation Projects
    • Authors: Salman Rahimi, Clinton M. Wood, Panagiota (Yota) Kokkali, Benjamin Rivers
      Abstract: Transportation Research Record, Ahead of Print.
      Under the Federal Highway Administration’s innovation development program “Every Day Counts” (EDC-5), the initiative on Advanced Geotechnical Methods in Exploration (A-GaME) aims to improve the knowledge in U.S. practice on existing but underutilized subsurface exploration methods. The A-GaME suite of technologies is a group of proven and effective exploration technologies and practices that, in conjunction with limited conventional exploration methods, mitigate the risks of geotechnical uncertainties and optimize subsurface exploration programs for improved site characterization and reliability over a wider coverage area and maximum return-on-investment. Transportation agencies are becoming more eager to employ alternative exploration methods to supplement their investigations and limit uncertainty emanating from geotechnical subsurface conditions. In this context, Arkansas Department of Transportation, in collaboration with the University of Arkansas, has implemented geophysical methods in subsurface investigation to acquire adequate information in relation to bedrock depth and rippability for new construction and to address slope stability issues along roadways. Different geophysical methods have been employed, including multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and microtremor horizontal to vertical spectral ratio (MHVSR). Two case studies are presented here, one for a proposed and one for an existing transportation project. According to the results of these case histories, the joint application of MASW and MHVSR was determined to be valuable for rock rippability estimates for roadway projects, whereas the combined use of MASW, MHVSR, and ERT produced significant additional subsurface information for landslide assessments and remediation efforts.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T06:05:33Z
      DOI: 10.1177/0361198121996362
       
  • Development of North Carolina Department of Transportation’s CLEAR
           Program for Enhanced Project Performance
    • Authors: Clare E. Fullerton, Alyson W. Tamer, Siddharth Banerjee, Abdullah F. Alsharef, Edward J. Jaselskis
      Abstract: Transportation Research Record, Ahead of Print.
      Valuable lessons learned and best practices gleaned from construction projects often do not transfer to future generations because of the lack of a formalized process. This ongoing issue gives rise to the need to impart fresh training to new North Carolina Department of Transportation (NCDOT) employees once the aging workforce retires or in the event of turnover. In addition, a platform for personnel to record pertinent project information about successes and failures in projects is needed. Such information can help solve problems and avoid repeated mistakes. The aim of this research project is to create a new program called Communicate Lessons, Exchange Advice, Record (CLEAR) to reposit knowledge gained by personnel. Integral to this program is an internal-only web-based database on NCDOT’s Connect SharePoint portal with MS Access as its backend. The North Carolina State University researchers used a Design for Six Sigma approach to identify, define, develop, optimize, and verify lessons learned/best practices to create the CLEAR database. The database fields were selected based on end-user input as well as a review of existing data, such as claims and supplemental agreements, within NCDOT data repositories. Training materials, including videos and standard operating procedures, were created to disseminate information about this new program. The CLEAR program will help the NCDOT to institutionalize knowledge and is expected to improve project cost variability and scheduling.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T06:03:31Z
      DOI: 10.1177/0361198121995195
       
  • Geofencing to Enable Differentiated Road User Charging
    • Authors: Petter Arnesen, Hanne Seter, Ørjan Tveit, Mats Myhrvold Bjerke
      Abstract: Transportation Research Record, Ahead of Print.
      Tolling normally has a dual purpose in Norway. Its first goal is to finance a project or an improvment in the transport services offered in an area, for instance extend public transport services. The second goal is to change travel behavior, encouraging drivers of private cars to use other more environmentally friendly modes. Today, this tolling system is based on fixed points on the road network which are not necessarily able to record all road usage evenly. Within the GeoSUM (Geofencing for Smart Urban Mobility) research project, a distance and fuel differentiated road user charging scheme has been piloted. Instead of fixed point tolling, this system enables the driver to perceive that the cost is directly related to how much gasoline or electricity is used on the road network. The key technology for this system is geofencing, and the pilot results show that the proposed system did indeed increase the amount electricity used for driving inside the geofence zones, reducing in turn the amount of fossil-based fuel used.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:46:51Z
      DOI: 10.1177/0361198121995510
       
  • Neighborhood Effects of Safe Routes to School Programs on the Likelihood
           of Active Travel to School
    • Authors: Carole T. Voulgaris, Reyhane Hosseinzade, Anurag Pande, Serena E. Alexander
      Abstract: Transportation Research Record, Ahead of Print.
      Safe routes to school (SRTS) programs aim to increase the share of students commuting to school by active modes (e.g., walking and cycling). This study measures the relationship between the presence of SRTS programs in a neighborhood and children’s journey-to-school mode choice. Children were identified from households in the 2012 California Household Travel Survey and they were classified based on whether they commuted to school by active modes. Next, census tracts with SRTS programs were identified based on the presence of data in the National Center for Safe Routes to School (NCSRTS) data collection system. Based on these two datasets, a logistic regression model estimated the likelihood that a child commuted to school by active modes, based on the presence of a SRTS program and controlling for individual, household, and tract characteristics. This analysis was supplemented with stakeholder interviews about the nature of SRTS programs within the study area and how they are perceived. Findings indicate that longer trip distance and race (relative to white students) are associated with reduced rates of active travel to school, but that these differences are mitigated by the presence of SRTS programs. Interviews suggest SRTS programs in the study area primarily emphasize education and encouragement rather than engineering interventions. It was concluded that the effect of such SRTS programming might best be described as reducing barriers to active school travel rather than simply increasing the likelihood of using active modes.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:43:28Z
      DOI: 10.1177/0361198121995490
       
  • Development and Evaluation of Cooperative Intersection Management
           Algorithm under Connected and Automated Vehicles Environment
    • Authors: Slobodan Gutesa, Joyoung Lee, Dejan Besenski
      Abstract: Transportation Research Record, Ahead of Print.
      Recent technological advancements in the automotive and transportation industry established a firm foundation for development and implementation of various connected and automated vehicle solutions around the globe. Wireless communication technologies such as the dedicated short-range communication protocol are enabling information exchange between vehicles and infrastructure. This research paper introduces an intersection management strategy for a corridor with automated vehicles utilizing vehicular trajectory-driven optimization method. Trajectory-Driven Optimization for Automated Driving provides an optimal trajectory for automated vehicles based on current vehicle position, prevailing traffic, and signal status on the corridor. All inputs are used by the control algorithm to provide optimal trajectories for automated vehicles, resulting in the reduction of vehicle delay along the signalized corridor with fixed-time signal control. The concept evaluation through microsimulation reveals that, even with low market penetration (i.e., less than 10%), the technology reduces overall travel time of the corridor by 2%. Further increase in market penetration produces travel time and fuel consumption reductions of up to 19.5% and 22.5%, respectively.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:41:31Z
      DOI: 10.1177/0361198121994580
       
  • Retrospective Longitudinal Study of the Impact of Truck Weight Regulatory
           Changes on Operating Gross Vehicle Weights
    • Authors: Amanda Pushka, Jonathan D. Regehr
      Abstract: Transportation Research Record, Ahead of Print.
      Three primary policy changes on truck size and weight occurred in Canada over the past five decades: the 1974 Western Canadian Highway Strengthening Program, the 1988 Roads and Transportation Association of Canada Memorandum of Understanding on Heavy Vehicle Weights and Dimensions, and ongoing special permitting of longer combination vehicles. These regulatory changes influenced the gross vehicle weight (GVW) of the predominant truck configurations operating on principal Canadian highways. Using a unique time-series of truck weight data, this retrospective longitudinal study contributes insights about the magnitude and timing of the impacts of truck weight regulatory changes on operating GVWs that address current knowledge gaps and persistent uncertainties in models used to predict and evaluate truck weight regulatory changes. The analysis reveals that carriers hauling heavy (i.e., weigh-out) commodities adapt immediately to increases in GVW limits if there is no need to purchase new vehicles. When a regulatory change coincides with the introduction of a new, more productive vehicle configuration, the uptake of the new vehicle lags behind the regulatory change by a few years. Finally, configurations exhibit different GVW distributions and responses to increased GVW limits depending on whether the configurations are well suited for hauling weigh-out or cube-out commodities. This differential response demonstrates how regulations facilitate fleet diversity within the trucking industry’s approach to the road freight transport task.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:39:31Z
      DOI: 10.1177/0361198121995502
       
  • Mining Vehicle Trajectories to Discover Individual Significant Places:
           Case Study using Floating Car Data in the Paris Region
    • Authors: Danyang Sun, Fabien Leurent, Xiaoyan Xie
      Abstract: Transportation Research Record, Ahead of Print.
      In this study we discovered significant places in individual mobility by exploring vehicle trajectories from floating car data. The objective was to detect the geo-locations of significant places and further identify their functional types. Vehicle trajectories were first segmented into meaningful trips to recover corresponding stay points. A customized density-based clustering approach was implemented to cluster stay points into places and determine the significant ones for each individual vehicle. Next, a two-level hierarchy method was developed to identify the place types, which firstly identified the activity types by mixture model clustering on stay characteristics, and secondly discovered the place types by assessing their profiles of activity composition and frequentation. An applicational case study was conducted in the Paris region. As a result, five types of significant places were identified, including home place, work place, and three other types of secondary places. The results of the proposed method were compared with those from a commonly used rule-based identification, and showed a highly consistent matching on place recognition for the same vehicles. Overall, this study provides a large-scale instance of the study of human mobility anchors by mining passive trajectory data without prior knowledge. Such mined information can further help to understand human mobility regularities and facilitate city planning.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:37:31Z
      DOI: 10.1177/0361198121995500
       
  • Toward A Framework for Assessing the Fair Distribution of Space in Urban
           Streets
    • Authors: Gabriel Lefebvre-Ropars, Catherine Morency, Paula Negron-Poblete
      Abstract: Transportation Research Record, Ahead of Print.
      The increasing popularity of street redesigns highlights the intense competition for street space between their different users. More and more cities around the world mention in their planning documents their intention to rebalance streets in favor of active transportation, transit, and green infrastructure. However, few efforts have managed to formalize quantifiable measurements of the balance between the different users and usages of the street. This paper proposes a method to assess the balance between the three fundamental dimensions of the street—the link, the place, and the environment—as well as a method to assess the adequation between supply and demand for the link dimension at the corridor level. A series of open and government georeferenced datasets were integrated to determine the detailed allocation of street space for 11 boroughs of the city of Montréal, Canada. Travel survey data from the 2013 Origine-Destination survey was used to model different demand profiles on these streets. The three dimensions of the street were found to be most unbalanced in the central boroughs of the city, which are also the most dense and touristic neighborhoods. A discrepancy between supply and demand for transit users and cyclists was also observed across the study area. This highlights the potential of using a distributive justice framework to approach the question of the fair distribution of street space in an urban context.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:35:31Z
      DOI: 10.1177/0361198121995196
       
  • Autonomous Vehicles’ Car-Following Drivability Evaluation Based on
           Driving Behavior Spectrum Reference Model
    • Authors: Xiao Qi, Ying Ni, Yiming Xu, Ye Tian, Junhua Wang, Jian Sun
      Abstract: Transportation Research Record, Ahead of Print.
      A large portion of the accidents involving autonomous vehicles (AVs) are not caused by the functionality of AV, but rather because of human intervention, since AVs’ driving behavior was not properly understood by human drivers. Such misunderstanding leads to dangerous situations during interaction between AV and human-driven vehicle (HV). However, few researches considered HV-AV interaction safety in AV safety evaluation processes. One of the solutions is to let AV mimic a normal HV’s driving behavior so as to avoid misunderstanding to the most extent. Therefore, to evaluate the differences of driving behaviors between existing AV and HV is necessary. DRIVABILITY is defined in this study to characterize the similarity between AV’s driving behaviors and expected behaviors by human drivers. A driving behavior spectrum reference model built based on human drivers’ behaviors is proposed to evaluate AVs’ car-following drivability. The indicator of the desired reaction time (DRT) is proposed to characterize the car-following drivability. Relative entropy between the DRT distribution of AV and that of the entire human driver population are used to quantify the differences between driving behaviors. A human driver behavior spectrum was configured based on naturalistic driving data by human drivers collected in Shanghai, China. It is observed in the numerical test that amongst all three types of preset AVs in the well-received simulation package VTD, the brisk AV emulates a normal human driver to the most extent (ranking at 55th percentile), while the default AV and the comfortable AV rank at 35th and 8th percentile, respectively.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:23:10Z
      DOI: 10.1177/0361198121994857
       
  • Longitudinal Analysis of Transit-Integrated Ridesourcing Users and Their
           Trips
    • Authors: Emma Swarney, Jacob Terry, Devin Feng, Chris Bachmann
      Abstract: Transportation Research Record, Ahead of Print.
      Several municipal transit agencies have partnered with transportation network companies to provide a range of services, but data restrictions have limited research on trip-level observations of transit-integrated ridesourcing users. The goal of this study was to understand how users’ trip-making behaviors adapted to a transit-integrated ridesourcing pilot in Waterloo, Ontario. This research conducted a longitudinal analysis of 178 unique users and temporal analyses of their 4,536 ridesourcing trips (rides) taken throughout the pilot from November 2018 to December 2019. Trip type and frequency changes over time were measured for frequent, average, and infrequent users. Transit, walking, and cycling alternatives to the pilot rides were generated and characterized based on their complementarity with transit. The number of unique users and daily ridership increased over time, as new users made their first trips and existing users made trips more frequently. Frequent users shifted toward less transit-competitive trip types whereas average and infrequent users had a sporadic but larger share of more transit-competitive trip types. The pilot was mostly used during off-peak service periods, when transit was less frequent, which suggests these systems are valuable for nonwork trips. Transit trip alternatives were not temporally competitive with rides. Cycling was competitive with 5% to 10% of rides and was consistently faster than walking and transit alternatives. Walking was not a practical alternative to rides in most cases. This analysis may inform other agencies of performance evaluation techniques for their transit-integrated ridesourcing pilots and the unique characteristics of trips taken by users of this mode.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:21:10Z
      DOI: 10.1177/0361198121995832
       
  • Laboratory Evaluation of Electrically Conductive Asphalt Mixtures for Snow
           and Ice Removal Applications
    • Authors: Rahaf Hasan, Ayman Ali, Christopher Decarlo, Mohamed Elshaer, Yusuf Mehta
      Abstract: Transportation Research Record, Ahead of Print.
      The study evaluates the electrical conductivity and mechanical performance of graphite modified asphalt mixtures. The effects of air voids, carbon fiber, and binder performance grade (PG) on the electrical resistivity of graphite modified asphalt mixtures are also assessed. Three graphite grades, two asphalt binders (polymer-modified PG 76-22 and neat PG 64-22), one aggregate type, and one carbon fiber were used to produce graphite modified asphalt mixtures. The mixtures were produced without graphite (control mix, PG 76-22), with only graphite (three grades and PG 76-22), with both graphite and 1% carbon fiber (three grades and PG 76-22), and with graphite (all three grades) and PG 64-22. The electrical conductivity, resistance to rutting, resistance to cracking, and durability of these mixes were evaluated using electrical resistivity (using a multi-meter), asphalt pavement analyzer, Hamburg wheel tracking device, semi-circular bend, indirect tension cracking, and Cantabro loss tests. Test results showed that graphite improves the electrical conductivity of asphalt mixtures when added at dosages of 10% to 15% or higher by volume of binder. Graphite grades with larger particle sizes helped improve the conductivity of asphalt mixtures better than graphite grades with smaller particle sizes. Air voids (higher air voids increased resistivity), carbon fiber dosage (decreased resistivity), and binder performance grade (neat binders had lower resistivity) affected the electrical resistivity of graphite modified asphalt mixtures. Furthermore, graphite modified mixes had better rutting resistance but higher susceptibility to breakdown and cracking when compared with unmodified mixtures.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:19:28Z
      DOI: 10.1177/0361198121995826
       
  • Automatic Generation of Customized Checklists for Digital Construction
           Inspection
    • Authors: Xin Xu, JungHo Jeon, Yuxi Zhang, Liu Yang, Hubo Cai
      Abstract: Transportation Research Record, Ahead of Print.
      Construction inspection plays a critical role to ensure the quality and long-term performance of infrastructure. The current construction inspection practice at state transportation agencies (STAs) in the United States, which requires inspectors to manually gather and personally interpret the construction requirements from standard specifications, is subjective, error-prone, and time-consuming. This paper presents an intelligent database approach to automatically generate customized checklists of construction requirements at the pay item level. The proposed approach consists of three components: (1) identification of the functional requirements by consulting with the end users, (2) development of a construction inspection knowledge model via ontology to guide the database design, and (3) devising mechanisms to automate the generation of customized construction checklists for the work under inspection with all the necessary details in relation to what, when, and how to check, as well as the risks and actions when noncompliance is encountered. Specifically, the following functions now can be performed within the new system: (1) automatic generation of a customized checklist at the pay item level; (2) access to a checklist display that aligns with the repetitive/cyclical nature of construction workflows; (3) navigation between cross-referenced check items; (4) subgroupings based on responsibility, risk level, and inspection frequency; and (5) real-time links to training materials such as photos, videos, textual documents, and websites. This newly developed tool is currently being implemented and is expected to greatly reduce the workload for inspectors and enhance the effectiveness of the construction inspection process.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:17:27Z
      DOI: 10.1177/0361198121995825
       
  • Evaluation of a Transportation Incentive Program for Affordable Housing
           Residents
    • Authors: Huijun Tan, Nathan McNeil, John MacArthur, Kelly Rodgers
      Abstract: Transportation Research Record, Ahead of Print.
      This study looks at initial results from the Transportation Wallet for Residents of Affordable Housing pilot program launched by the City of Portland’s Bureau of Transportation. The program provides a set of transportation incentives for low-income participants, including a US$308 prepaid Visa card that could be applied to public transit or other transportation services, a free bike share membership, and access to discounted rates on several services. A survey was conducted with the program’s participants (278 total responses) to understand how they used the Transportation Wallet and how the program helped them use different transport modes to get around. The main findings include: (1) The financial support of this program encouraged some participants to use new mobility services (including Uber/Lyft, bike share, and e-scooter) that they had never used before; (2) the program increased access for participants, helping them make more trips and, for some, get to places they otherwise could not have gone; and (3) transportation fairs, where participants could learn about services and talk to providers, promoted both mode sign-up and mode usage, particularly for new mobility services and a reduced fare transit program. The survey results also point to some opportunities to improve the program. Participant feedback suggests that transportation agencies do more to streamline and educate participants on how to use new mobility services and coordinate different service providers to optimize seamless services for participants. The paper provides insights into the implementation and effectiveness of a transportation financial incentive program for low-income populations.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:14:46Z
      DOI: 10.1177/0361198121997431
       
  • Use of Blended Binder Tests to Estimate Performance of Mixtures with High
           Reclaimed Asphalt Pavement/Recycled Asphalt Shingles Content
    • Authors: Yuan Zhang, Daniel Swiertz, Hussain U. Bahia
      Abstract: Transportation Research Record, Ahead of Print.
      The purpose of this study is to assess the use of blended binder tests to estimate mixture performance properties of high reclaimed asphalt pavement (RAP)/recycled asphalt shingles (RAS) mixtures utilizing recycling agents as a means to evaluate different recycling agents and estimate their doses for a given mixture. Blended binder properties are measured by using standard performance grading (PG) and PG+ test methods and correlating the results with corresponding performance properties of mixtures. Blended binders consisting of virgin and recovered binders and recycling agents were prepared and tested for PG grading properties, multiple stress creep recovery grades, and linear amplitude sweep fatigue life after the rolling thin-film oven and pressure aging vessel aging. Mixtures were tested for rutting resistance and cracking resistance at intermediate temperature and at low temperatures after being subjected to short-term oven aging and long-term oven aging. The correlation between the blended binder properties and mixture performance properties is used to identify the binder test parameters that can be used to predict the long-term performance of high RAP/RAS mixtures and the effects of various recycling agents. Results generally indicate that use of direct testing of recovered binders with recycling agents is an effective means to estimate required initial dose for recycling agent, and testing actual blended binders can be used to predict mixture performance-related properties for the testing conditions used in this study.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:05:21Z
      DOI: 10.1177/0361198121997423
       
  • Using OpenStreetMap as a Data Source for Attractiveness in Travel Demand
           Models
    • Authors: Christian Klinkhardt, Tim Woerle, Lars Briem, Michael Heilig, Martin Kagerbauer, Peter Vortisch
      Abstract: Transportation Research Record, Ahead of Print.
      We present a methodology to extract points of interest (POIs) data from OpenStreetMap (OSM) for application in travel demand models. We use custom taglists to identify and assign POI elements to typical activities used in travel demand models. We then compare the extracted OSM data with official sources and point out that the OSM data quality depends on the type of POI and that it generally matches the quality of official sources. It can therefore be used in travel demand models. However, we recommend that plausibility checks should be done to ensure a certain quality. Further, we present a methodology for calculating attractiveness measures for typical activities from single POIs and national trip generation guidelines. We show that the quality of these calculated measures is good enough for them to be used in travel demand models. Using our approach, therefore, allows the quick, automated, and flexible generation of attractiveness measures for travel demand models.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:03:29Z
      DOI: 10.1177/0361198121997415
       
  • Effect of Taper on Shear Stiffness of Steel-Reinforced Neoprene Bearing
           Pads
    • Authors: Satyajeet R. Patil, Gary R. Consolazio, H. R. Hamilton
      Abstract: Transportation Research Record, Ahead of Print.
      Steel-reinforced elastomeric bearing pads are widely used in bridge construction to vertically support girders on piers while also accommodating translational and rotational girder deformations caused by live loads and temperature changes. To support sloped girders, flat bearing pads of uniform thicknesses are typically used with either tapered steel shim plates or an inclined concrete bearing seat. The use of tapered pads has the potential to reduce both construction time and cost by eliminating the need for tapered plates or seats to match the girder slope. However, limited research has been performed to investigate the effect of introducing taper on relevant design properties of bearing pads. In this paper, results are presented from experimental testing that was performed to quantify the effect of taper on shear stiffnesses of pads having varied geometric characteristics (plan view dimensions, elastomer thicknesses, and slope angles). An experimental bearing pad test device was designed and utilized to impose shear loads in accordance with ASTM standards, while simultaneously maintaining a constant axial load. Bearing pads chosen for testing were tapered variations of standard flat bridge bearing pads used in the state of Florida, U.S. Results obtained from the study revealed that shear stiffness was not significantly influenced by the introduction of taper angle, the direction of shear along the length of pads, or axial load level. The shear stiffness of tapered pads remained within approximately 10% of the shear stiffness of corresponding flat pads.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T05:01:09Z
      DOI: 10.1177/0361198121996709
       
  • Determination of Dynamic Modulus Master Curve of Damaged Asphalt Pavements
           for Mechanistic–Empirical Pavement Rehabilitation Design
    • Authors: Zhe “Alan” Zeng, Kangjin “Caleb” Lee, Youngsoo Richard Kim
      Abstract: Transportation Research Record, Ahead of Print.
      For pavement rehabilitation design, the current mechanistic–empirical (ME) pavement design guide provides three levels of analysis methodology to determine dynamic modulus master curves for existing asphalt pavements. First, the ME pavement design guide recommends that Witczak’s predictive equation is employed to obtain the “undamaged” modulus master curve. Depending on the chosen level of analysis, either a falling weight deflectometer test (Level 1) or a condition survey (Levels 2 and 3) is conducted to determine the damage factor(s). The damage factor is used to shift the undamaged master curve downward to match the field conditions and obtain the “damaged” master curve. In this study, two pavement structures in North Carolina Highway 96 were selected to evaluate the accuracy of the ME pavement design guide using its three levels of analysis. Because this roadway is a multilayer full-depth pavement, the extracted field cores were divided into a top layer, bottom layer, and total core for investigative and comparative purposes. Accordingly, both laboratory measurements and pavement ME predictions of the dynamic modulus values were conducted separately. Results show that the predicted undamaged master curves are always higher than the measured master curves and Levels 1, 2, and 3 can each lead to significantly different damaged master curves. Considering both efficiency and accuracy for transportation agency practice, the Level 1 method is recommended, and if the existing pavement is a multilayered asphalt pavement, a total core extracted from all the layers is recommended to generate the input properties for Witczak’s predictive equation.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T04:57:48Z
      DOI: 10.1177/0361198121996708
       
  • Jointed Plain Concrete (JPC) Pavement Variability and Method to Complement
           JPC Design with 3D Pavement Data
    • Authors: Georgene Malone Geary, Yichang (James) Tsai
      Abstract: Transportation Research Record, Ahead of Print.
      3D pavement data are increasing in use and availability and open up new opportunities to evaluate variability in pavements. The majority of information we currently have on existing pavements is the result of the Long Term Pavement Performance Program (LTPP). While the program is comprehensive and the data are immense, the study sections are typically only 500 ft in length, which limits the ability to accurately gauge the variability of the distresses in a pavement over a longer length, especially cracking in Jointed Plain Concrete (JPC) slabs. 3D pavement data already collected by transportation agencies have the opportunity to complement LTPP data to analyze variability and improve the use of LTPP data. This paper presents a unique method to complement LTPP data using 3D pavement data, consisting of four steps: (1) crack detection using 3D pavement data; (2) categorize detected cracks by orientation and extent by slab using 3D slab-based methodology; (3) convert categorized slab level cracking into mechanistic-empirical pavement design guide cracking; and (4) perform local calibration with the 3D converted input values. The method uses 3D pavement data to provide a non-discrete value for percent cracking in GPS-3 LTPP sections for the purposes of local calibration. The proposed method is shown to be feasible using 3D pavement data and two JPC LTPP sections in Georgia. The method could be extended to any of the state Departments of Transportation that have active LTPP sections and are now or will shortly be collecting 3D pavement data.
      Citation: Transportation Research Record
      PubDate: 2021-03-01T04:47:09Z
      DOI: 10.1177/0361198121997820
       
  • Acoustic Modeling of Meteorological Effects on Roadway Noise
    • Authors: Roger L. Wayson, Kenneth Kaliski
      Abstract: Transportation Research Record, Ahead of Print.
      Modeling road traffic noise levels without including the effects of meteorology may lead to substantial errors. In the United States, the required model is the Traffic Noise Model which does not include meteorology effects caused by refraction. In response, the Transportation Research Board sponsored NCHRP 25-52, Meteorological Effects on Roadway Noise, to collect highway noise data under different meteorological conditions, document the meteorological effects on roadway noise propagation under different atmospheric conditions, develop best practices, and provide guidance on how to: (a) quantify meteorological effects on roadway noise propagation; and (b) explain those effects to the public. The completed project at 16 barrier and no-barrier measurement positions adjacent to Interstate 17 (I-17) in Phoenix, Arizona provided the database which has enabled substantial developments in modeling. This report provides more recent information on the model development that can be directly applied by the noise analyst to include meteorological effects from simple look-up tables to more precise use of statistical equations.
      Citation: Transportation Research Record
      PubDate: 2021-02-25T10:20:39Z
      DOI: 10.1177/0361198121994584
       
  • Detailing an Improved Heat Transfer Model for Pavements
    • Authors: James Bryce, Arka Chattopadhyay, Mehdi Esmaeilpour, Zack E. Ihnat
      Abstract: Transportation Research Record, Ahead of Print.
      Temperature profiles are a fundamental input into mechanistic-empirical pavement analysis and design, and the enhanced integrated climatic model (EICM) is the state-of-the-practice for calculating those profiles. The EICM has also been used in other applications, such as analysis to evaluate the effects of climate change on pavements and to estimate the effects of pavements on urban heat islands. The calculations in the EICM for pavement temperatures can be viewed as having two primary components that together act as a system: the thermal model describing conductance of temperatures throughout the pavement, and the boundary conditions that include the convective terms at the pavement surface, an energy balance model to predict the solar radiation at the surface of the pavement and a specified lower boundary condition (generally constant temperature at defined depth). As is shown in this paper, the current EICM models overpredict temperatures during hot times and in no-wind conditions, while also underpredicting (albeit to a lesser magnitude) during cold conditions. This result implies that the increases in pavement temperatures predicted to occur with climate change are likewise overestimated. Conversely, because the convection coefficient is incorrect, the predicted amount of energy contributing to urban heat islands will also not be correctly predicted using the current EICM models. Although improvements to the solar model are noted, this paper focuses on improvements to the thermal model and convective boundary condition using modern heat transfer principles and data from the Long-Term Pavement Performance database.
      Citation: Transportation Research Record
      PubDate: 2021-02-25T09:42:57Z
      DOI: 10.1177/0361198121994847
       
  • Understanding the Role of Online Media Platforms in Airport Capital
           Projects and Community Outreach
    • Authors: Max Z. Li, Megan S. Ryerson
      Abstract: Transportation Research Record, Ahead of Print.
      Community outreach and engagement efforts are critical to an airport’s role as an ever-evolving transportation infrastructure and regional economic driver. As online social media platforms continue to grow in both popularity and influence, a new engagement channel between airports and the public is emerging. However, the motivations behind and effectiveness of these social media channels remain unclear. In this work, we address this knowledge gap by better understanding the advantages, impact, and best practices of this newly emerging engagement channel available to airports. Focusing specifically on airport YouTube channels, we first document quantitative viewership metrics, and examine common content characteristics within airport YouTube videos. We then conduct interviews and site visits with relevant airport stakeholders to identify the motivations and workflow behind these videos. Finally, we facilitate sample focus groups designed to survey public perceptions of the effectiveness and value of these videos. From our four project phases, to maximize content effectiveness and community engagement potential, we synthesize the following framework of action items, recommendations, and best practices: (C) Consistency and community; (O) Organizational structure; (M) Momentum; (B) Branding and buy-in; (A) Activity; (T) Two-way engagement; (E) Enthusiasm; and (D) Depth, or as a convenient initialism, our COMBATED framework.
      Citation: Transportation Research Record
      PubDate: 2021-02-23T04:55:08Z
      DOI: 10.1177/0361198121993474
       
  • Design and Implementation of Zone-to-Zone Demand Responsive Transportation
           Systems
    • Authors: Shiyu Shen, Yanfeng Ouyang, Shuai Ren, Mengke Chen, Luyun Zhao
      Abstract: Transportation Research Record, Ahead of Print.
      Conventional fixed-structure transit service is unable to satisfy the increasingly personalized passenger demand. Shared mobility companies enable the transformation of conventional transit with advanced technology. This paper proposes a framework to design an application-based demand responsive transit (DRT) system to serve zone-to-zone passenger requests. The proposed DRT service operates between zone pairs to satisfy “door-to-door” and “reservation-based” requests. A two-phase problem is formulated, including (i) conceptual planning phase and (ii) discrete route design phase. In the conceptual planning phase, a continuous approximation model is proposed to optimize operational efficiency by deciding the resource requirements and operational features with given service area and demand density. In the route design phase, a customized bus routing model is established to generate profitable routes, by adopting a combined solution approach with adapted savings and simulated annealing (SA) method. The theoretical framework is applied in a pilot area at Huangdao College Town in Qingdao, China. An implementable design including the layout plan, candidate stops, and operation headways is developed from the conceptual plan model. Groups of sample data sets are used to demonstrate the applicability of the proposed design framework. Results show that the proposed DRT system is promising in relation to providing better service than the previous first-come-first-serve bus pooling service.
      Citation: Transportation Research Record
      PubDate: 2021-02-23T04:51:07Z
      DOI: 10.1177/0361198121995493
       
  • Classifying Car Owners in Latent Psychographic Profiles
    • Authors: Sascha von Behren, Lisa Bönisch, Jan Vallée, Peter Vortisch
      Abstract: Transportation Research Record, Ahead of Print.
      Policy makers in urban areas are subjected to increasing pressure to find sustainable solutions to congestion and transportation. A detailed understanding of the motivations of car owners is required to enable the development of policies that are both socially fair and take effective measures. The objective of this study is to provide a more granular differentiation of car owners using psychographic profiles in three basic dimensions (privacy, autonomy, and car excitement). These profiles are also examined in relation to general travel behavior in everyday and long-distance travel. Data was collected in Munich and Berlin (Germany) and a latent class analysis was applied to segment respondents into latent profile classes. On this basis, six different profile classes were identified. In addition to the Car Independents profile class which does not have strong orientations toward the car, several profile classes were also identified with high concerns about “privacy” in relation to social distances in public transit. The information and analysis presented enables a deeper understanding of the motivations of the different target profile classes and discusses the need for tailored, socially fair measures to reduce car ownership and use within these groups.
      Citation: Transportation Research Record
      PubDate: 2021-02-23T04:48:06Z
      DOI: 10.1177/0361198121994839
       
  • Exploring the Factors that Affect the Frequency of Use of Ridehailing and
           the Adoption of Shared Ridehailing in California
    • Authors: Jai Malik, Farzad Alemi, Giovanni Circella
      Abstract: Transportation Research Record, Ahead of Print.
      This study explores the factors that affect the use of ridehailing services (Uber, Lyft) as well as the adoption of shared (pooled) ridehailing (UberPool, Lyft Share) using data collected in California in fall 2018 using a cross-sectional travel survey. A semi-ordered bivariate probit model is estimated using this dataset. Among other findings, the model results show that better-educated, younger individuals who currently work or work and study are more likely to use shared ridehailing services than other individuals, and in particular members of older cohorts. Being white and living in a higher-income household is associated with a higher likelihood of being a frequent user of regular ridehailing but does not have statistically significant effects on the likelihood of adopting shared ridehailing. With respect to the factors limiting the use of shared ridehailing services, it was found that the increased travel time and lack of privacy discourage the adoption of shared ridehailing. Evidence is also found that some land-use features affect the likelihood of using both types of services. While the likelihood of using both ridehailing and shared ridehailing is higher in urban areas, residents of neighborhoods with higher intersection density are found to be more likely to adopt shared ridehailing only. However, some of the land-use variables become insignificant after introducing individuals’ attitudes related to land use into the model. This is an indication of residential self-selection, and the potential risk of attributing impacts to land-use features if individual attitudes are not explicitly controlled for.
      Citation: Transportation Research Record
      PubDate: 2021-02-23T04:44:57Z
      DOI: 10.1177/0361198120985151
       
  • Use of Resampling Method to Construct Variance Index and Repeatability
           Limit of Damage Characteristic Curve
    • Authors: Jing Ding, Kangjin Caleb Lee, Cassie Castorena, Youngsoo Richard Kim, B. Shane Underwood
      Abstract: Transportation Research Record, Ahead of Print.
      The simplified viscoelastic continuum damage model has been widely accepted as a tool to predict fatigue performance of asphalt concrete. One key component in the model is the damage characteristic curve that results from a cyclic fatigue test. This curve characterizes the relationship between material integrity (stiffness) and the level of damage in the material. As with any experimental measurement, it is important to know and quantify the variability of the damage curve, but traditional statistical methods are ill-suited for experiments that yield functional data as opposed to univariate data. In this study, a variance index of the damage characteristic curve is first proposed and compared with the expert judgment of the variance of a set of nine different asphalt mixtures. Then, an example analysis for establishing the repeatability limit of a specific mixture as the application of the variance index is presented using the resampling method and hypothesis test. The major findings are as follows: 1) the proposed variance index can match the expert judgment of variability; 2) the shape of the damage characteristic curve can affect the performance of the variance index; 3) the resampling method and hypothesis test can be applied to flag inconsistent data in multi-user or multi-laboratory results; and 4) the resampling method can also be used to construct the repeatability limit of the variance index.
      Citation: Transportation Research Record
      PubDate: 2021-02-22T11:51:56Z
      DOI: 10.1177/0361198121994850
       
  • Arterial-Friendly Local Ramp Metering Control Strategy
    • Authors: Yao Cheng, Gang-Len Chang
      Abstract: Transportation Research Record, Ahead of Print.
      To prevent local streets being blocked by overflowing on-ramp queues, a standard practice of ramp metering control is to restrain its function when a series of preset conditions are identified by on-ramp queue detectors. Such a trade-off between potential ramp queue spillback and the restraint resulting from the operation of metering control may often fail to either effectively mitigate bottlenecks caused by on-ramp waving or convince arterial users and local traffic agencies of the need for ramp metering operations. This study, therefore, presents an arterial-friendly local ramp metering system (named AF-ramp) that can achieve the target metering rate to produce optimal freeway conditions without ramp queues spilling back onto local streets. This is achieved by concurrently optimizing the signal plans for those intersections that send turning flows to the ramp. At this stage, this system has been developed for time-of-day control. It could also serve as the base module for extending to real-time control, or multi-ramp coordinated operations. The AF-ramp model, with its ability to optimize the arterial signals concurrently with the ramp metering rate, can ensure the best use of the capacity of local intersections and prevent any gridlock caused by overflows from on-ramp queue spillback or arterial turning traffic. With extensive simulation experiments, the evaluation results confirmed the AF-ramp model’s effectiveness in improving traffic conditions on both the freeway and its neighboring arterial links at the same time. This study has also introduced the real-time extension of the proposed model and a framework of a transition from the time-of-day control to fully responsive real-time operations.
      Citation: Transportation Research Record
      PubDate: 2021-02-20T11:52:18Z
      DOI: 10.1177/0361198121994581
       
  • Long Short-Term Memory-Based Human-Driven Vehicle Longitudinal Trajectory
           Prediction in a Connected and Autonomous Vehicle Environment
    • Authors: Lei Lin, Siyuan Gong, Srinivas Peeta, Xia Wu
      Abstract: Transportation Research Record, Ahead of Print.
      The advent of connected and autonomous vehicles (CAVs) will change driving behavior and travel environment, and provide opportunities for safer, smoother, and smarter road transportation. During the transition from the current human-driven vehicles (HDVs) to a fully CAV traffic environment, the road traffic will consist of a “mixed” traffic flow of HDVs and CAVs. Equipped with multiple sensors and vehicle-to-vehicle communications, a CAV can track surrounding HDVs and receive trajectory data of other CAVs in communication range. These trajectory data can be leveraged with recent advances in deep learning methods to potentially predict the trajectories of a target HDV. Based on these predictions, CAVs can react to circumvent or mitigate traffic flow oscillations and accidents. This study develops attention-based long short-term memory (LSTM) models for HDV longitudinal trajectory prediction in a mixed flow environment. The model and a few other LSTM variants are tested on the Next Generation Simulation US 101 dataset with different CAV market penetration rates (MPRs). Results illustrate that LSTM models that utilize historical trajectories from surrounding CAVs perform much better than those that ignore information even when the MPR is as low as 0.2. The attention-based LSTM models can provide more accurate multi-step longitudinal trajectory predictions. Further, grid-level average attention weight analysis is conducted and the CAVs with higher impact on the target HDV’s future trajectories are identified.
      Citation: Transportation Research Record
      PubDate: 2021-02-19T10:36:34Z
      DOI: 10.1177/0361198121993471
       
  • Bayesian Nonparametric Approach to Average Annual Daily Traffic Estimation
           for Bridges
    • Authors: Grace Ashley, Nii Attoh-Okine
      Abstract: Transportation Research Record, Ahead of Print.
      Every year, the U.S. government provides several billions of dollars in the form of federal funding for transportation services in the U.S.A. Decision making with regard to the use of these funds largely depends on performance indicators like average annual daily traffic (AADT). In this paper, Bayesian nonparametric models are developed through machine learning for the estimation of AADT on bridges. The effect of hyperparameter choice on the accuracy of estimations produced by Bayesian nonparametric models is also assessed. The predictions produced using the Bayesian nonparametric approach are then compared with predictions from a popular Frequentist approach for the selected bridges. Evaluation metrics like the mean absolute percentage error are subsequently employed in model evaluation. Based on the results, the best methods for AADT forecasting for the selected bridges are recommended.
      Citation: Transportation Research Record
      PubDate: 2021-02-19T10:36:12Z
      DOI: 10.1177/0361198121994591
       
  • Performance Evaluation of Basic Turbo Roundabouts as an Alternative to
           Conventional Double-Lane Roundabouts
    • Authors: Zuhair Elhassy, Hatem Abou-Senna, Essam Radwan
      Abstract: Transportation Research Record, Ahead of Print.
      Since their introduction in the late 1990s, basic turbo roundabouts have made a great success in several European countries. Researchers, however, have been unable to reach a general consensus on the operational performance advantages and benefits derived from such a novel design of multi-lane roundabouts, as compared with conventional double-lane roundabouts. Those contradictory results could be mostly attributed to wide variations in driver behavior among different traffic environments. This study aims to analyze and evaluate the operational performance of an existing, congested double-lane roundabout in the State of Florida and a proposed, simulated basic turbo roundabout. Local field data was used to accurately calibrate and validate the microsimulation models and to precisely capture local driving behavior. Three scenarios were created for evaluation. Results indicated that basic turbo roundabouts with regulatory entry speed as per Dutch standards, that is, 25 mph, were the most suitable alternative to reduce average delay and provide comparable capacity to double-lane conventional roundabouts for traffic flow ranging between 4,350 and 6,050 vehicles per hour. However, double-lane conventional roundabouts, including their major and minor approaches, always managed to process significantly more vehicles.
      Citation: Transportation Research Record
      PubDate: 2021-02-19T10:35:52Z
      DOI: 10.1177/0361198121994838
       
  • State of the Practice for High Polymer-Modified Asphalt Binders and
           Mixtures
    • Authors: Jhony Habbouche, Ilker Boz, Brian K. Diefenderfer, Bryan C. Smith, Sayed Hamidullah Adel
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this paper was to provide information on the state of the practice for using high polymer-modified (HP) asphalt concrete (AC) mixtures in the United States (U.S.) and Canada. This information was collected through a survey of U.S. and Canadian provincial agencies combined with a search of HP-related specifications, special provisions, and field trials or pilot projects previously constructed. Moreover, the Virginia Department of Transportation’s (VDOT) current state of the practice with regard to using HP paving material was determined. This was achieved through a navigation of VDOT databases to report tonnage and types of produced HP AC mixtures, and experience, lessons learned, and best practices on behalf of multiple asphalt contractors in the area. The majority of the agencies that currently use or have constructed field trials and pilot projects using HP AC mixtures are located in the eastern part of the U.S. In general, HP AC mixtures have been used in a wide range of applications ranging from full-depth AC to thin AC overlays under heavy traffic on interstates and slow-braking loads at intersections. No major field-related construction issues in relation to mixing temperatures and in-place compaction of HP AC mixtures were reported, and standard construction practices and equipment were used. Finally, good communication between the polymer/binder supplier and the contractor, and solid planning before conducting the work were important lessons learned with regard to paving with HP AC mixtures.
      Citation: Transportation Research Record
      PubDate: 2021-02-19T10:35:32Z
      DOI: 10.1177/0361198121995190
       
  • State-of-the-Practice Review on the Use of Flocculants for Construction
           Stormwater Management in the United States
    • Authors: Billur Kazaz, Michael A. Perez, Wesley N. Donald
      Abstract: Transportation Research Record, Ahead of Print.
      Construction stormwater practices have a vital role in protecting downstream water bodies from runoff that is typically characterized with large amounts of sediment and suspended solids. Most sediment control practices lack the capability to capture fine-sized soil particles that are responsible for causing elevated turbidity. Flocculation is a form of chemical treatment that uses flocculant particles as a binding bridge to form larger particles to enhance the gravitational settling process. The use of flocculants provides promising results for removing fine particles and treating construction stormwater. This study provides a comprehensive review of flocculants and their applications in construction stormwater treatment in the U.S. The study presents a literature review and results of a state-of-the-practice survey distributed to state departments of transportation. Results from 37 participating state agencies and data from specifications and design manuals for non-participating agencies were compiled to develop a comprehensive understanding of current uses and perceptions. Results indicated that 39% of state agencies currently use flocculants on construction sites. Within that, 54% of the state agencies rely on manufacturer guidance for dosage and application rates and only 23% require monitoring residual flocculant in downstream receiving waters. The potential risk of polluting downstream water bodies because of overdosage of flocculants related to inadequate application rates and techniques is the main concern of the state departments of transportation on flocculant usage. Understanding the perspective of the state agencies on flocculants will provide an insight into future research agendas for extending the use of flocculants in construction stormwater management.
      Citation: Transportation Research Record
      PubDate: 2021-02-19T10:35:13Z
      DOI: 10.1177/0361198121995192
       
  • Autonomous Vehicle Safe Operating Speeds on the Automated Skyway Express
           in Jacksonville, Florida
    • Authors: Andrew E. Loken, Joshua S. Steelman, Scott K. Rosenbaugh, Ronald K. Faller
      Abstract: Transportation Research Record, Ahead of Print.
      Autonomous vehicles (AV) differ significantly from traditional passenger vehicles in both their behavior and physical characteristics. As such, the validity of the guidance provided in the Manual for Assessing Safety Hardware, Second Edition (MASH 2016) is questionable in AV applications. Impact angles, speeds, and vehicle weights specified in MASH 2016 are inextricably linked to the traditional vehicles underlying the estimates. For AV applications, these parameters must be estimated from the ground up, stepping outside the guidance of MASH 2016. In this paper, a conservative method for evaluating existing infrastructure to support AV traffic is proposed. The method integrates traditional structural analyses with unconventional methods of estimating impact conditions. This methodology was developed for the Jacksonville Transportation Authority, who, when faced with unique challenges in maintaining and expanding their Automated Skyway Express, opted to convert the system from monorail to AV traffic. Leading AV developers were surveyed to develop a portfolio of potential candidates for the conversion. Estimated impact conditions were then compared against the capacity of the system’s existing concrete parapets. Ultimately, safe operating speeds for each AV candidate were recommended on the bases of structural capacity and vehicle stability. All but one AV candidate were deemed capable of safely operating at the desired speed of 25 mph without any modifications to the barrier. Although the methodology was developed for a particular case, it is applicable to future implementations of AVs on existing infrastructure, provided the roadway is confined similarly to the Skyway deck.
      Citation: Transportation Research Record
      PubDate: 2021-02-18T06:19:37Z
      DOI: 10.1177/0361198121991834
       
  • Simple Methodology for the Development and Analysis of Local Driving
           Cycles Applied in the Study of Cars and Motorcycles in Recife, Brazil
    • Authors: Guilherme Medeiros Soares de Andrade, Fernando Wesley Cavalcanti de Araújo, Maurício Pereira Magalhães de Novaes Santos, Silvio Jacks dos Anjos Garnés, Fábio Santana Magnani
      Abstract: Transportation Research Record, Ahead of Print.
      Standard driving cycles are usually used to compare vehicles from distinct regions, and local driving cycles reproduce more realistic conditions in specific regions. In this article, we employed a simple methodology for developing local driving cycles and subsequently performed a kinematic and energy analysis. As an application, we employed the methodology for cars and motorcycles in Recife, Brazil. The speed profile was collected using a smartphone (1 Hz) validated against a high precision global positioning system (10 Hz), presenting a mean absolute error of 3 km/h. The driving cycles were thus developed using the micro-trip method. The kinematic analysis indicated that motorcycles had a higher average speed and acceleration (32.5 km/h, 0.84 m/s2) than cars (22.6 km/h, 0.55 m/s2). As a result of the energy analysis, it was found that inertia is responsible for most of the fuel consumption for both cars (59%) and motorcycles (41%), but for motorcycles the aerodynamic drag is also relevant (36%). With regards to fuel consumption, it was found that the standard driving cycle used in Brazil (FTP-75; 2.47 MJ/km for cars and 0.84 MJ/km for motorcycles) adequately represents the driving profile for cars (2.46 MJ/km), and to a lesser extent motorcycles (0.91 MJ/km) in off-peak conditions. Finally, we evaluated the influence of the vehicle category on energy consumption, obtaining a maximum difference of 38% between a 2.0 L sports utility vehicle and a 1.0 L hatchback.
      Citation: Transportation Research Record
      PubDate: 2021-02-18T06:19:28Z
      DOI: 10.1177/0361198121991850
       
  • Characteristics of Non-Punitive Employee Safety Reporting Systems for
           Public Transportation as Abridged from TCRP Report 218
    • Authors: Lisa Staes, Jodi Godfrey
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this research is to produce a compilation of best practices used in non-punitive employee safety reporting (ESR) systems at transit agencies, including examples of how ESR systems benefit transit agencies and their employees. This report will support the public transportation industry’s efforts to institute non-punitive ESR as a critical element in safety management systems implementation. The literature review and background research framed the subsequent narrative and findings from interviews with public transportation agencies. For the purposes of this report, the agency that implemented the ESR system determined successful elements. The researchers did not perform a statistical modeling or evaluation method to determine elemental success; rather, success determination stemmed from the implementing agencies. This report also identifies challenges faced through the implementation phases of ESR system deployment, as presented through the literature review and transit agency case studies. Report findings identify benefits associated with wide dissemination of commonly reported hazards and methods to address them, such as the Aviation Safety Reporting System, or the Confidential Close Call Reporting System. There are also recognized benefits in third-party administration and management of ESR systems through reduced likelihoods of associated punitive or retaliatory consequences. Therefore, researchers determined the public transportation industry could benefit from central repository reporting options for hazards and near-miss information aggregation to further support data-driven decision-making. Additionally, industry evidentiary protections would ensure greater reporting. Finally, the public transportation industry would benefit from a non-punitive ESR toolkit or online resource repository that includes samples for agency customization.
      Citation: Transportation Research Record
      PubDate: 2021-02-18T06:19:27Z
      DOI: 10.1177/0361198121992075
       
  • Development and Validation of a Seven-County Regional Pedestrian Volume
           Model
    • Authors: Robert J. Schneider, Andrew Schmitz, Xiao Qin
      Abstract: Transportation Research Record, Ahead of Print.
      This study describes the development and validation of pedestrian intersection crossing volume models for the seven-county Milwaukee metropolitan region. The set of three models, among the first developed at a multi-county scale, can be used to estimate the total number of pedestrian crossings per year at four-leg intersections along state highways and other major thoroughfares. Outputs are appropriate for annual volumes ranging from 1,000 to 650,000. We used negative binomial regression to relate annual pedestrian volumes at 260 intersections to roadway and surrounding neighborhood socioeconomic and land-use variables. The three models include seven variables that have significant positive associations with annual pedestrian volume: population density within 400 m of the intersection; employment density within 400 m; number of bus stops within 100 m; number of retail businesses within 100 m; number of restaurant and bar businesses within 100 m; presence of a school within 400 m; and proportion of households without a motor vehicle within 400 m. Results suggest that square root or cube root transformations of continuous explanatory variables could potentially improve model fit. The models have fair accuracy, with each of the three model formulations predicting 60% or more of validation intersection counts to within half or double the observed value. Future research could address overprediction by creating new variables to better represent the number of lanes on each intersection leg and low socioeconomic status of adjacent neighborhoods.
      Citation: Transportation Research Record
      PubDate: 2021-02-18T06:19:07Z
      DOI: 10.1177/0361198121992360
       
  • Using Real-Time Data to Detect Delays and Improve Customer Communications
           at New York City Transit
    • Authors: Adam Caspari, Daniel Wood, Angel Campbell, Darian Jefferson, Tuan Huynh, Alla Reddy
      Abstract: Transportation Research Record, Ahead of Print.
      New York City Transit operates one of the world’s largest transit systems, and it can be difficult for the agency’s communications team to keep track of the numerous service disruptions that need to be communicated to customers. This paper introduces the Transit Visualization tool, which processes real-time train location data to automatically identify areas of the system where service may not be living up to customers’ expectations. Specifically, the Transit Visualization is set up to identify areas of the system where trains are operating at lower-than-normal speeds and areas of the system where there are atypically long gaps between trains. Any occurrence of slow speeds or long gaps is assigned a severity level (Moderate, Severe, or Very Severe) to indicate the magnitude of the problem. An overview of any problems the application identifies is shown on an interactive web map, as well as on several easy-to-digest summary tables. The map also displays real-time locations of trains and buses throughout the transit system. The Transit Visualization has been successfully rolled out to the subways communications team and has become a mission-critical tool for communicating delays to customers, especially during the course of the COVID-19 pandemic.
      Citation: Transportation Research Record
      PubDate: 2021-02-18T06:18:36Z
      DOI: 10.1177/0361198121994115
       
  • Performance Evaluation of Studded Tire Ruts for Asphalt Mix Designs in a
           Cold Region Environment
    • Authors: Osama A. Abaza, Daniel Dahms
      Abstract: Transportation Research Record, Ahead of Print.
      Studded tire wear is one of the most important contributing factors that govern pavement life on high traffic volume roads in south-central Alaska. It has been estimated that the annual cost to repair damage caused by studded tires in Alaska is approximately $13.7 million. Polymer modified asphalt binders and hard aggregate are commonly used in mix designs in the State of Alaska Department of Transportation and Public Facilities projects in an attempt to resist studded tire wear. This research provides a field performance-based analysis of the use of hard aggregate and polymer modified binders related to the reduction of the impact of studded tire wear. To analyze the performance of modification in asphalt mix designs, roadway data was gathered from the Alaska Department of Transportation Pavement Management System Database and roads were grouped into deterioration families based on mix design properties. Relationships of each deterioration are presented to show cumulative average annual daily traffic versus total rut depth, comparing mix designs with and without hard aggregate and polymer modification. Findings indicated that both polymer modification and hard aggregate can be used to reduce the impact of studded tire wear. The benefits of polymer modification and hard aggregate proved more significant as cumulative traffic volumes increase. Recommendations from the performance analysis included continuing the use of hard aggregate and polymer modified binders on Alaskan roadways with continuous research on the use of more highly modified asphalt binders to further reduce the impact of studded tire wear.
      Citation: Transportation Research Record
      PubDate: 2021-02-18T06:18:27Z
      DOI: 10.1177/0361198121994120
       
  • Study on Risks and Countermeasures of Shallow Biogas during Construction
           of Metro Tunnels by Shield Boring Machine
    • Authors: Xi Jiang, Yuxin Zhang, Zhuanzhuan Zhang, Yun Bai
      Abstract: Transportation Research Record, Ahead of Print.
      With the intensive development of cities, the utilization of underground space has attracted more and more attention from industry and academia. Underground rail (metro) in cities has become an imperative mode for people in their daily lives. Meanwhile, the safety of rail tunnel construction has constantly been a challenging issue because of the presence of complex strata containing shallow biogas. Accidents in tunnel construction because of shallow biogas which resulted in massive casualties and property loss have been reported in some recent literature. The excavation of formations containing shallow biogas not only poses a threat to the safety of the earlier stage of tunnel construction but also affects the later operation of metro lines. Therefore, the safety problem caused by shallow biogas should be taken into consideration seriously and avoided in the pre-construction stage. A typical underwater metro tunnel, Hangzhou Metro Line 6, is introduced in this study to suggest the proper approach to deal with the biogas problem during the construction process. The generation mechanism of shallow biogas is clarified and the process of identifying biogas risk during strata exploration is also discussed. A risk identification and control system for shield tunneling through biogas strata is proposed to mitigate the potential dangers of shallow biogas during the construction process. This study provides actual construction experience and countermeasures for other similar metro tunnel projects that encounter biogas strata to diminish the potential risks and avoid severe accidents.
      Citation: Transportation Research Record
      PubDate: 2021-02-18T06:18:07Z
      DOI: 10.1177/0361198121994594
       
  • Robust Hazardous Materials Closed-Loop Supply Chain Network Design with
           Emergency Response Teams Location
    • Authors: Nasrin Mohabbati-Kalejahi, Alexander Vinel
      Abstract: Transportation Research Record, Ahead of Print.
      Hazardous materials (hazmat) storage and transportation pose threats to people’s safety and the environment, which creates a need for governments and local authorities to regulate such shipments. This paper proposes a novel mathematical model for what is termed the hazmat closed-loop supply chain network design problem. The model, which can be viewed as a way to combine several directions previously considered in the literature, includes two echelons in the forward direction (production and distribution centers), three echelons in the backward direction (collection, recovery, and disposal centers), and emergency response team positioning. The two objectives of minimizing the strategic, tactical, and operational costs as well as the risk exposure on road networks are considered in this model. Since the forward flow of hazmat is directly related to the reverse flow, and since hazmat accidents can occur at all stages of the lifecycle (storage, shipment, loading, and unloading, etc.), it is argued that such a unified framework is essential. A robust framework is also presented to hedge the optimization model in case of demand and return uncertainty. The performance of both models is evaluated based on a standard dataset from Albany, NY. Considering the trade-offs between cost and risk, the results demonstrate the design of efficient hazmat closed-loop supply chain networks where the risk exposure can be reduced significantly by employing the proposed models.
      Citation: Transportation Research Record
      PubDate: 2021-02-12T10:53:43Z
      DOI: 10.1177/0361198121992071
       
  • Who’s on Board' Examining the Changing Characteristics of Transit
           Riders using Latent Profile Analysis
    • Authors: Andrew Schouten, Brian D. Taylor, Evelyn Blumenberg
      Abstract: Transportation Research Record, Ahead of Print.
      Subsidies of public transit have more than doubled since the late 1980s, with a disproportionate share of funds going to rail services. These investments have important implications, including how they affect both the composition of transit users and their travel behavior. To investigate how transit users and use are changing, we use Latent Profile Analysis and data from the 2009 and 2017 National Household Travel Surveys to examine changes in transit users in the U.S. and in five major metropolitan areas. Nationwide, we find that the share of Transit Dependents grew by 17% to account for two-thirds of all transit users in 2017. These least advantaged riders were more likely over time to reside in very poor households and to be carless. There was a corresponding decline in Occasional Transit Users, for whom transit is part of a multi-modal travel profile. Higher-income, mostly car-owning Choice Transit Riders increased slightly over time but accounted for less than one in ten transit riders in 2017. Their growth was concentrated in a few large metropolitan areas where densities and land use are most transit-supportive. While increased rail transit service has shifted riders away from buses, transit’s role as a redistributive social service that provides mobility to disadvantaged travelers has grown over time. Efforts to draw more multi-modal and car-owning travelers onto transit have been less successful. As transit systems struggle to recover riders following the pandemic, transit’s waxing role of providing mobility for those without will likely become even more prominent.
      Citation: Transportation Research Record
      PubDate: 2021-02-12T10:50:41Z
      DOI: 10.1177/0361198120987225
       
  • Assessment of Discretionary Lane-Changing Decisions using a Random
           Parameters Approach with Heterogeneity in Means and Variances
    • Authors: Qianwen Li, Xiaopeng Li, Fred Mannering
      Abstract: Transportation Research Record, Ahead of Print.
      Lane-changing maneuvers on highways may cause capacity drops, create shock waves, and potentially increase collision risks. Properly managing lane-changing behavior to reduce these adverse impacts requires an understanding of their determinants. This paper investigates the determinants of lane changing in congested traffic using a next generation simulation dataset. A random parameters binary logit model with heterogeneity in means and variances was estimated to account for unobserved heterogeneity in lane-changing behavior across vehicles. Estimation results show that average headway, the original lane of the vehicle, driver acceleration/deceleration behavior, and vehicle size all significantly influence lane-changing probabilities. It was further found that the effect of vehicle size varied significantly across observations, that the mean of this variation decreased with increasing average headway, and the variance increased with increasing driver acceleration/deceleration. These empirical findings provide interesting new evidence on the determinants of lane changing, which can be used in traffic flow models to better replicate and predict traffic flow.
      Citation: Transportation Research Record
      PubDate: 2021-02-12T10:48:41Z
      DOI: 10.1177/0361198121992364
       
  • Introducing a New Apparatus for Designating Two-Lane Highway Passing and
           No-Passing Zones
    • Authors: Ahmed Farid, Zephaniah Connell, James Mock, Suresh Muknahallipatna, Khaled Ksaibati
      Abstract: Transportation Research Record, Ahead of Print.
      Two-lane highways constitute a large proportion of the U.S. highways. An essential component needed in the design of safe two-lane highways is the passing sight distance (PSD). Otherwise, insufficient PSDs lead to passing-related crashes and, therefore, no-passing zones ought to be marked. This research involves the development of a new apparatus of the two-vehicle method, which is used for measuring the PSD in the field. That is to replace the defunct apparatus used by the Wyoming Department of Transportation (WYDOT). To the best of the authors’ knowledge, the introduced apparatus is the most up-to-date system and addresses shortcomings of previous research. The two-vehicle method involves two successive vehicles spaced at a gap, equivalent to PSD, and both vehicles travel at the speed limit. The driver of the rear vehicle operates a switch when the lead vehicle becomes invisible because of sight obstructions, such as vegetation, signaling the beginning point of the no-passing zone. Similarly, the switch is operated when the lead vehicle returns to view to designate the endpoint of the no-passing zone. The apparatus is composed of vehicle-to-vehicle radio communication devices, global positioning system devices, the switch and computers with graphical user interfaces to record and display the data. Testing was conducted on two two-lane highway segments. As per the results, overall discrepancies between WYDOT’s no-passing zone markings and those designated by the apparatus, developed, ranged from 1% to 7%. This research lays the foundation for a future study involving the development of a cutting-edge prototype.
      Citation: Transportation Research Record
      PubDate: 2021-02-12T10:46:21Z
      DOI: 10.1177/0361198121994112
       
  • Experimental Study on the Design and Behavior of Concrete Pavement Joint
           Sealants
    • Authors: Jinho Kim, Dan Zollinger, Seunghyun Lee
      Abstract: Transportation Research Record, Ahead of Print.
      Joints in concrete pavement are intended to provide freedom of movement in a concrete slab relative to the volumetric effects. Changes such as this can occur owing to drying shrinkage, temperature changes, and moisture differences that develop within the slab. A key reason to seal the rigid pavement joints is to prevent, or at least reduce, the amount of water from rainfall events infiltrating the pavement structure, which can ultimately contribute to subbase erosion, loss of support, and the build-up of a fine, incompressible material on the face of the joint. The strength of the joint sealant bond and stress of the interface between the sealant and the face of the joint reservoir play important roles in joint sealant failure. Thus, in this research, experimental coupling tests were conducted to investigate the geometric characteristics of the sealant/joint reservoir design. The stress–strain relationship on the interface was investigated according to its geometry, both with regard to the shape factor (SF) and the degree of curvature (DoC). The SF and DoC were evaluated through a tensile test of the joint sealant based on these geometric characteristics. Also discussed are the shape factors (SFs) of the joint sealant currently being recommended, the SF most appropriate for a narrow-width joint, and the surface finish of the joint sealant. Based on this study, the effects of sealant geometries (i.e., SF and DoC) should be considered during design and installation. Also, further research into more realistic SFs for narrow-width joints and self-leveling sealants is recommended.
      Citation: Transportation Research Record
      PubDate: 2021-02-12T10:44:17Z
      DOI: 10.1177/0361198121993472
       
  • Gravity Model of Passenger and Mobility Fleet Origin–Destination
           Patterns with Partially Observed Service Data
    • Authors: Brian Yueshuai He, Joseph Y. J. Chow
      Abstract: Transportation Research Record, Ahead of Print.
      Mobility-as-a-service systems are becoming increasingly important in the context of smart cities, with challenges arising for public agencies to obtain data from private operators. Only limited mobility data are typically provided to city agencies, which are not enough to support their decision-making. This study proposed an entropy-maximizing gravity model to predict origin–destination patterns of both passenger and mobility fleets with only partial operator data. An iterative balancing algorithm was proposed to efficiently reach the entropy maximization state. With different trip length distributions data available, two calibration applications were discussed and validated with a small-scale numerical example. Tests were also conducted to verify the applicability of the proposed model and algorithm to large-scale real data from Chicago transportation network companies. Both shared-ride and single-ride trips were forecast based on the calibrated model, and the prediction of single-ride has a higher level of accuracy. The proposed solution and calibration algorithms are also efficient to handle large scenarios. Additional analyses were conducted for north and south sub-areas of Chicago and revealed different travel patterns in these two sub-areas.
      Citation: Transportation Research Record
      PubDate: 2021-02-11T06:42:00Z
      DOI: 10.1177/0361198121992074
       
  • COVID-19 Impact on Transport: A Paper from the Railways’ Systems
           Research Perspective
    • Authors: Alessio Tardivo, Armando Carrillo Zanuy, Celestino Sánchez Martín
      Abstract: Transportation Research Record, Ahead of Print.
      This paper analyzes the possible impacts of the 2019 coronavirus disease (COVID-19) on the transport sector and specifically on the railways. It aims at investigating how the sector should approach the “new normal.” The pandemic had repercussions not only on the interaction between producers and consumers but also on the environment, therefore changing the supply chain. The health crisis halted passengers’ mobility and limited air and sea freight capacity significantly, consequently producing a positive impact on the environment. However, the low production trend of greenhouse gas (GHG) emission is expected to reverse once containment measures are lifted. Transport will have an important role in the predicted rebound effect of GHG emissions; thus, the development of green new mobility is essential. In light of these aspects, this study argues that a new resilient paradigm of mobility must be developed for future health emergencies which meets environmental demands. This paper introduces the five “R”s—resilience, return, reimagination, reform, and research—as the necessary steps the rail sector will need to address to better continue to provide services throughout future crises. In particular, the paper highlights new avenues for research which can play an essential role in enhancing rail competitiveness and resilience within future crises. In conclusion, this paper reminds that the pandemic might be considered as a testing ground for upcoming crises and an opportunity to introduce the discussion about a new green and public paradigm of mobility.
      Citation: Transportation Research Record
      PubDate: 2021-02-11T06:38:20Z
      DOI: 10.1177/0361198121990674
       
  • Assessing the Effects of Limited Curbside Pickup Capacity in Meal Delivery
           Operations for Increased Safety during a Pandemic
    • Authors: Hossein Fotouhi, Nicholas Mori, Elise Miller-Hooks, Vadim Sokolov, Sagar Sahasrabudhe
      Abstract: Transportation Research Record, Ahead of Print.
      Meal delivery has become increasingly popular in past years and of great importance in past months during the COVID-19 pandemic. Sustaining such services depends on maintaining provider profitability and reduced cost to consumers while continuing to support autonomy and independence for customers, restaurants, and delivery drivers (here crowdsourced drivers). This paper investigates the possible enactment of curbside regulations in the U.S. that limit the number of drivers simultaneously waiting at restaurants to pick up meals for delivery on both public safety and delivery efficiency. Curbside regulations would aim to increase safety by enabling social distancing between delivery personnel at pickup locations and have a secondary benefit of improving local traffic flows, which are sometimes impeded in busier, urban locations. Curbside space limits are studied in relation to their impacts on consumer-related performance measures: freshness of the food on delivery and click-to-door time. This investigation is enabled through a proposed hybrid discrete-event and time-advanced simulation platform that replicates meal delivery service calls and pickup and delivery operations across a region built on data from a leading meal delivery company. Embedded within the simulation is an integer program that optimally assigns orders to drivers in a dynamically changing environment. Order assignments are constrained by imposed curbside capacity limits at the restaurants, and potential efficiencies and curbside violation reductions from bundling orders are assessed. Results of analyses from numerical experiments provide insights to state and local communities in designing curbside restrictions that reduce curbside crowding yet enable delivery companies to retain their profitability.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:33:58Z
      DOI: 10.1177/0361198121991840
       
  • Spatio-Temporal Crash Prediction: Effects of Negative Sampling on
           Understanding Network-Level Crash Occurrence
    • Authors: Peter Way, Jeremiah Roland, Mina Sartipi, Osama Osman
      Abstract: Transportation Research Record, Ahead of Print.
      In projects centered around rare event case data, the challenge of data comprehension is greatly increased because of insufficient data for deriving insight and analysis. This is particularly the case with traffic crash occurrence, where positive events (crashes) are rare and, in most cases, no data set exists for negative events (non-crashes). One method to increase available data is negative sampling, which is the process of creating a negative event based on the absence of a positive event. In this work, four negative sampling techniques are presented with varying ratios of negative to positive data. These types of techniques are based on spatial data, temporal data, and a mixture of the two, with the data ratios acting as class balancing tools. The best performing model found was with a negative sampling technique that shifted temporal information and had an even 50/50 data split, with an F-1 score, a formulaic combination of precision and recall, of 93.68. These results are promising for Inteligent Transportation Systems (ITS) applications to inform of potential crash locations in an entire area for proactive measures to be put in place.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:31:35Z
      DOI: 10.1177/0361198121991836
       
  • Sidewalk Static Obstructions and Their Impact on Clear Width
    • Authors: Nicholas A. Coppola, Wesley E. Marshall
      Abstract: Transportation Research Record, Ahead of Print.
      Data on sidewalks have long been deficient. But advances in remote sensing are beginning to increase data prevalence and accuracy. These sidewalk datasets rarely, if ever, account for static obstructions in the sidewalk such as signs, street furniture, or trees. This paper seeks to determine how much of a difference accounting for static obstructions will make when measuring the clear width of sidewalks. We extracted the minimum width of sidewalk surfaces—both with and without accounting for static obstructions—for the entirety of Cambridge, MA, using new GIS methods described in this paper. We then compared these results against Americans with Disabilities Act (ADA) standards for clear width as well as national and federal sidewalk guidelines. The results suggest a significant decrease in the average clear width of sidewalks when accounting for static obstructions. More specifically, the clear width of the average sidewalk drops from 4.5 ft (1.4 m) to 3.5 ft (1.1 m). The percentage of sidewalk segments meeting the 3-ft ADA standard drops from 78% to 51% when accounting for static obstructions. For the proposed 4-ft (1.2-m) ADA standard, it plunges from 59% of sidewalk segments meeting the width threshold to 31%. These results demonstrate that not accounting for static obstructions could lead to a gross overestimation of seemingly adequate sidewalks and an unrealistic assessment of sidewalk infrastructure and pedestrian accessibility.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:28:55Z
      DOI: 10.1177/0361198121991833
       
  • Field Evaluation of Wattle and Silt Fence Ditch Checks
    • Authors: Jaime C. Schussler, Billur Kazaz, Michael A. Perez, J. Blake Whitman, Bora Cetin
      Abstract: Transportation Research Record, Ahead of Print.
      Erosion and sediment control practices are implemented during construction activities to mitigate downstream effects, but limited field-performance data exists. Field assessments were conducted to evaluate ditch check installations during highway construction in Tama County, Iowa. Data collection included daily rainfall, topographical surveys of sediment deposition, pre- and post-rain event images, and visual observations. Variations to the standard Iowa Department of Transportation silt fence ditch check installation evaluated as part of this study include: (a) upgrading non-reinforced geotextile to a multi-belted, reinforced geotextile (i.e., SF-M1); (b) installing V-shape, as opposed to linear, while incorporating wire reinforcement to support hydrostatic loads placed on the geotextile, inclusion of a weir to facilitate controlled flow discharge, and offsetting the geotextile entrenchment location to improve ground securement (i.e., SF-M2); and (c) installing the dich check as described for SF-M2 substituting slicing for trenching (i.e., SF-M3). The modified wattle installation (i.e., W-M) incorporated a teepee staking configuration to facilitate ground contact, and an excelsior underlay, secured by sod staples, to minimize wattle undercutting. Results from field experiments indicated that sediment retention rates significantly improved for installations of SF-M2 and SF-M3 when compared with the standard installation and SF-M1 at the 85% confidence level, and served as viable control measures in concentrated flow applications. The W-M installation exhibited a statistically significant improvement in sediment retention over the W-S installation at the 95% confidence level. These findings suggest that ditch check performance is a function of specified practice and of installation methods described within regulatory agency specifications and design guidelines.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:27:15Z
      DOI: 10.1177/0361198121992073
       
  • Do Larger Sample Sizes Increase the Reliability of Traffic Incident
           Duration Models' A Case Study of East Tennessee Incidents
    • Authors: Zihe Zhang, Jun Liu, Xiaobing Li, Asad J. Khattak
      Abstract: Transportation Research Record, Ahead of Print.
      Incident duration models are often developed to assist incident management and traveler information dissemination. With recent advances in data collection and management, enormous achieved incident data are now available for incident model development. However, a large volume of data may present challenges to practitioners, such as data processing and computation. Besides, data that span multiple years may have inconsistency issues because of the data collection environments and procedures. A practical question may arise in the incident modeling community—Is that much data really necessary (“all-in”) to build models' If not, then how many data are necessary' To answer these questions, this study aims to investigate the relationship between the data sample sizes and the reliability of incident duration analysis models. This study proposed and demonstrated a sample size determination framework through a case study using data of over 47,000 incidents. This study estimated handfuls of hazard-based duration models with varying sample sizes. The relationships between sample size and model performance, along with estimate outcomes (i.e., coefficients and significance levels), were examined and visualized. The results showed that the variation of estimated coefficients decreases as the sample size increases, and becomes stabilized when the sample size reaches a critical threshold value. This critical threshold value may be the recommended sample size. The case study suggested a sample size of 6,500 to be enough for a reliable incident duration model. The critical value may vary significantly with different data and model specifications. More implications are discussed in the paper.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:25:14Z
      DOI: 10.1177/0361198121992063
       
  • Approach for Predicting Cracking Deterioration in Sprayed Seals from
           Subjective Condition Ratings
    • Authors: Khulood Hwayyis, Rayya Hassan, Michael T. Fahey
      Abstract: Transportation Research Record, Ahead of Print.
      Cracking is the most influential distress on the performance of bituminous surfaces of granular pavements and ultimately that of underlying layers. The purpose of the study reported here is to describe the modeling approach adopted in developing cracking deterioration models of bituminous sprayed seals from historical time series subjective condition ratings. In this approach, a multilevel analysis has been applied to capture the variations between observations, segments, and highways. Further, it involved considering all possible contributing factors that affect cracking deterioration of in-service sprayed seals. Factors considered here include surface age, temperature, traffic volume, rainfall, shoulder seal width, and subgrade soil reactivity. The modeling approach has been applied to condition data from five rural highway networks separately then collectively. In the latter, only significant contributing factors from the individual networks’ models are considered. These networks have spray sealed granular pavements with different operating and environmental conditions. Predictions of the overall model have been compared with the currently used model. The latter has been developed for the same networks from two years of subjective condition data, using Markov chains (MC) and surface age as the only predictor. The overall model developed here using multilevel analysis and incorporating the significantly contributing factors predicts earlier deterioration than the MC model currently used. The latter predicts 70% of segments to be in good condition at the age of 5 years, whereas the first predicts only 49%.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:21:53Z
      DOI: 10.1177/0361198121991504
       
  • Evaluating the Interoperability of Urban Air Mobility Systems and Airports
    • Authors: Parker D. Vascik, R. John Hansman
      Abstract: Transportation Research Record, Ahead of Print.
      This paper investigates how existing arrival and departure procedures can be directly used or adapted to enable high-volume instrument and visual urban air mobility (UAM) flight operations at major airports in the United States. Viable procedures are restricted to those that enable simultaneous and non-interfering UAM flights with conventional aircraft operations. Air traffic controller workload is proposed as the critical integration barrier to scale UAM operations in visual conditions whereas separation minima, especially for approach procedures, is proposed as the critical barrier in instrument conditions. A systems approach is taken to evaluate potential integration strategies for UAM in which the location of UAM runways or vertipads and flight procedures are presented in a topological framework. The benefits, challenges, and notional application of five integration schemes are discussed. Four promising procedures for UAM are introduced through case studies at three airports. Findings indicate that multiple procedures exist to support high-volume UAM integration at major airports under current regulations with additional controller staffing, especially if UAM aircraft exhibit helicopter-like performance.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:19:33Z
      DOI: 10.1177/0361198121991501
       
  • Real-Time Vehicle Trajectory Estimation Based on Lane Change Detection
           using Smartphone Sensors
    • Authors: Zubayer Islam, Mohamed Abdel-Aty
      Abstract: Transportation Research Record, Ahead of Print.
      As technology is moving rapidly toward automation and connectivity, it is of paramount importance to predict vehicle trajectories ahead of time. This not only enhances safety but also ensures mobility in a connected and automated environment. Previous studies have shown that, given the previous trajectory, the future trajectory can be estimated. But this method suffers from considerable drawbacks in the case of intersections as it cannot predict turning movements. It also requires advanced sensors that are not readily available in most vehicles. A smartphone device can also be used in such scenarios, bringing partial automation to vehicles without these sensors. This paper presents an integrated method of estimating vehicle trajectories for both general roadway segments and intersections by using a smartphone. A lane change detection system is taken as an indicator of intersection turning movement estimation and corresponding vehicle trajectories are estimated accordingly. The system can achieve high penetration rates and can be used to replicate onboard units. Sensor readings are taken periodically which are first filtered with a low-pass filter to zero out any high-frequency noise and then fed into a machine learning model to detect lane changes. The model can successfully capture lane changes with smartphone data with high accuracy (95%). Finally, vehicle trajectory is estimated using Chebyshev’s polynomial. This type of estimation system can find applications in collision prediction at intersections between a turning vehicle and a pedestrian on a crosswalk.
      Citation: Transportation Research Record
      PubDate: 2021-02-09T11:11:50Z
      DOI: 10.1177/0361198121990681
       
  • Investigating the Role of Transportation Barriers in Cancer Patients’
           Decision Making Regarding the Treatment Process
    • Authors: Roya Etminani-Ghasrodashti, Chen Kan, Ladan Mozaffarian
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation barriers to healthcare access may lead to rescheduled or missed appointments, thereby influencing patients’ treatment outcomes. However, the impact of transportation barriers on stopping cancer treatments remains unknown in the literature. This study aims to investigate the association between cancer patients’ travel behavior and their decisions about stopping or continuing treatments. In this study, an online survey was designed and conducted for cancer patients who received radiotherapy and chemotherapy. Comprehensive questions were asked to reveal personal- and treatment-related factors that affect participants’ decisions, including their travel behavior, travel burden, treatment characteristics, and side effects. With data collected from the survey, machine learning models were further employed to quantitatively assess the factors contributing to patients’ decision making. Results suggest that lack of access to transportation has a significant impact on cancer patients’ decisions with respect to stopping or continuing treatments. Limited access to private vehicles will likely lead to the stopping of radiotherapy. In addition, trip frequency and trip length to caregivers influence the patients’ continuing or quitting chemotherapy. Insights generated in this study have great potential to help policy makers and planners make informed decisions to enhance cancer patients’ access to treatments and improve their health outcomes.
      Citation: Transportation Research Record
      PubDate: 2021-02-06T10:32:52Z
      DOI: 10.1177/0361198121991497
       
  • Pricing of Connected and Autonomous Vehicles in Mixed-Traffic Networks
    • Authors: Paolo Delle Site
      Abstract: Transportation Research Record, Ahead of Print.
      For networks with human-driven vehicles (HDVs) only, pricing with arc-specific tolls has been proposed to achieve minimization of travel times in a decentralized way. However, the policy is hardly feasible from a technical viewpoint without connectivity. Therefore, for networks with mixed traffic of HDVs and connected and autonomous vehicles (CAVs), this paper considers pricing in a scenario where only CAVs are charged. In contrast to HDVs, CAVs can be managed as individual vehicles or as a fleet. In the latter case, CAVs can be routed to minimize the travel time of the fleet of CAVs or that of the entire fleet of HDVs and CAVs. We have a selfish user behavior in the first case, a private monopolist behavior in the second, a social planner behavior in the third. Pricing achieves in a decentralized way the social planner optimum. Tolls are not unique and can take both positive and negative values. Marginal cost pricing is one solution. The valid toll set is provided, and tolls are then computed according to two schemes: one with positive tolls only and minimum toll expenditure, and one with both tolls and subsidies and zero net expenditure. Convergent algorithms are used for the mixed-behavior equilibrium (simplicial decomposition algorithm) and toll determination (cutting plane algorithm). The computational experience with three networks: a two-arc network representative of the classic town bypass case, the Nguyen-Dupuis network, and the Anaheim network, provides useful policy insight.
      Citation: Transportation Research Record
      PubDate: 2021-02-06T10:02:25Z
      DOI: 10.1177/0361198120985850
       
  • Estimating the Rebound Effect of the U.S. Road Freight Transport
    • Authors: A. Latif Patwary, T. Edward Yu, Burton C. English, David W. Hughes, Seong-Hoon Cho
      Abstract: Transportation Research Record, Ahead of Print.
      The United States (U.S.) road freight sector has continued to grow over recent decades. Growth in road freight could result in more fuel consumption and hence increased greenhouse gas emissions. Policymakers have attempted to manage the growth of energy usage through improved fuel economy based on technological advances. However, such improvements may not lead to anticipated goals because of the rebound effect, where improvements in energy efficiency trigger more travel and energy consumption that offsets energy savings. Thus, this study aims to determine the potential rebound effect from improved energy efficiency in the U.S. road freight sector. Eight fuel cost models are applied and asymmetric price response is incorporated in estimating the U.S. road freight sector’s rebound effect from 1980 to 2016. In addition, a recently developed data envelopment analysis is applied to determine the annual rebound effect in the road freight sector. The results suggest that, after accounting for the asymmetric price response, the average rebound effect of the U.S. road freight sector ranges from 6.9% to 8.8%, a level considerably less than that found for several industrialized countries and emerging economies. However, a considerable increase in the rebound effect has been seen in more recent years. The findings suggest that overlooking the rebound effect in environmental policies could impede the goal of reducing total energy consumption and accompanying emissions. Policymakers should incorporate the rebound effect from efficiency enhancement in policy development and utilize some potential programs to reduce the adverse influence of rebound effect in related policies.
      Citation: Transportation Research Record
      PubDate: 2021-02-04T09:36:51Z
      DOI: 10.1177/0361198121991494
       
  • Middle-Up Cracking Potential in Flexible Pavements with Stabilized
           Foundations
    • Authors: Mostafa Nakhaei, David H. Timm
      Abstract: Transportation Research Record, Ahead of Print.
      This investigation presents a new perspective on the structural behavior of stabilized foundation pavements through full-scale testing and simulation where the historical premise of bottom-up fatigue cracking has been challenged. Two full-scale pavement sections were constructed at the National Center for Asphalt Technology Test Track in 2018. One section featured a stabilized foundation under the asphalt layers while the other was a thick-lift asphalt section on conventional base and subgrade materials. Both sections were embedded with pavement response instrumentation and their behavior was observed over time under accelerated truck trafficking. In addition, computational simulations were executed to explain the observed behavior. The strain measurement at the bottom of the asphalt concrete (AC) for the thick-lift section showed a familiar trend in which the tensile strain at the bottom of the AC increased exponentially with temperature. In contrast, the strain at the bottom of the AC in the stabilized foundation pavement was predominantly in compression at elevated temperatures. Further analysis revealed that compressive strain at the bottom of the AC increased exponentially with temperature similar to conventional flexible pavements but with a reversed sign. The results were confirmed by falling weight deflectometer testing that was conducted directly above the embedded pavement sensors. Computational simulations confirmed the behavior and suggested that the maximum tensile strain could occur at shallower depths, possibly mid-depth of the AC, in stabilized foundation pavements. This indicates stabilized foundation pavements could be prone to middle-up cracking and subsequent precautions should be taken to avoid middle-up fatigue cracking.
      Citation: Transportation Research Record
      PubDate: 2021-02-03T10:46:27Z
      DOI: 10.1177/0361198121990691
       
  • Exploring the Interactions between Online Shopping, In-Store Shopping, and
           Weekly Travel Behavior using a 7-Day Shopping Survey in Lisbon, Portugal
    • Authors: Rui Colaço, João de Abreu e Silva
      Abstract: Transportation Research Record, Ahead of Print.
      The steady growth of online shopping in the last decades has led to an impact on personal travel and on freight transport that is yet to be fully grasped. Previous research on the subject offers mixed findings, with several studies pointing to complementarity between online and in-store shopping, while others suggest substitution, modification, or neutrality. Using data from a 7-day shopping survey in Lisbon, Portugal, which involved 400 respondents, this paper applies structural equation modeling to explore the relationships among online shopping and in-store shopping preferences, while also considering the period of the week in which the purchases took place, since it is expected that the interaction between shopping and other personal travel behavior varies between weekdays and weekends. The result shows that online shopping preference leads to more online purchases, while in-store shopping preference leads to more in-store purchases. Furthermore, online shopping on weekdays has a positive association with both online and in-store shopping on weekends, which supports a complementarity effect. This effect is linked to a younger population, which commutes by car, and lives in less central areas. Since deliveries are becoming increasingly faster, while living centrally is becoming progressively more difficult, complementarity might give way to substitution, with the foreseeable challenges to maintaining street vitality, if this issue is not addressed timely by policymakers.
      Citation: Transportation Research Record
      PubDate: 2021-02-03T10:40:20Z
      DOI: 10.1177/0361198121990672
       
  • Neural Network Optimal Model for Classification of Unclassified Vehicles
           in Weigh-in-Motion Traffic Data
    • Authors: Cheng Peng, Yi Jiang, Shuo Li, Tommy Nantung
      Abstract: Transportation Research Record, Ahead of Print.
      A weigh-in-motion (WIM) system has the capability to perform on-site vehicle classifications based on the FHWA schema. However, WIM datasets often contain a significant portion of vehicles that could not be classified into any of the 13 vehicle classes by WIM devices. Possible reasons for the WIM classifier failing to classify these vehicles are tailgating, lane changing, traffic congestion, and equipment malfunction. Analysis of unclassified vehicles was performed with WIM-recorded data. A neural network model was established to determine the appropriate allocations of unclassified vehicles to vehicle classes. Since the number of unclassified vehicles is often fairly high, the allocations will help to improve the accuracy of truck traffic data and thus improve pavement design. Video records of traffic streams on an interstate section and traffic data from a nearby WIM station were used to identify causes for vehicle misclassifications. The optimal model was developed through model algorithm design, data processing, model training, validation, robustness analysis, and verification of video records. It was found that the optimal model was effective in allocating unclassified vehicles to appropriate vehicle classes. The optimal model was able to reclassify the unclassified vehicles that had non-zero attributes with high accuracy. The optimal model provides a useful tool for properly allocating the unclassified vehicles to the FHWA specified vehicle classes. The developed allocations can be applied to allocate unclassified vehicles appropriately to vehicle classes for pavement design and would potentially increase benefit and reduce cost with reliable and realistic pavement designs.
      Citation: Transportation Research Record
      PubDate: 2021-02-03T10:38:40Z
      DOI: 10.1177/0361198121990670
       
  • Exploring Preferences for Transportation Modes in the City of Munich after
           the Recent Incorporation of Ride-Hailing Companies
    • Authors: Maged Shoman, Ana Tsui Moreno
      Abstract: Transportation Research Record, Ahead of Print.
      The growth of ride-hailing (RH) companies over the past few years has affected urban mobility in numerous ways. Despite widespread claims about the benefits of such services, limited research has been conducted on the topic. This paper assesses the willingness of Munich transportation users to pay for RH services. Realizing the difficulty of obtaining data directly from RH companies, a stated preference survey was designed. The dataset includes responses from 500 commuters. Sociodemographic attributes, current travel behavior and transportation mode preference in an 8 km trip scenario using RH service and its similar modes (auto and transit), were collected. A multinomial logit model was used to estimate the time and cost coefficients for using RH services across income groups, which was then used to estimate the value of time (VOT) for RH. The model results indicate RH services’ popularity among those aged 18–39, larger households and households with fewer autos. Higher income groups are also willing to pay more for using RH services. To examine the impact of RH services on modal split in the city of Munich, we incorporated RH as a new mode into an existing nested logit mode choice model using an incremental logit. Travel time, travel cost and VOT were used as measures for the choice commuters make when choosing between RH and its closest mode, metro. A total of 20 scenarios were evaluated at four different congestion levels and four price levels to reflect the demand in response to acceptable costs and time tradeoffs.
      Citation: Transportation Research Record
      PubDate: 2021-02-03T10:37:00Z
      DOI: 10.1177/0361198121989726
       
  • Multiscale Modeling of Asphalt Concrete and Validation through
           Instrumented Pavement Section
    • Authors: Zafrul H. Khan, Rafiqul A. Tarefder, Hasan M. Faisal
      Abstract: Transportation Research Record, Ahead of Print.
      In this study, macroscale responses of asphalt concrete (AC) are predicted from the responses of its corresponding microscale representative volume element (RVE) within a finite element framework using quasi-static and dynamic analyses. Nanoindentation test was performed on the mastic and aggregate phase of an AC sample to determine the viscoelastic and elastic properties of RVE elements. Aggregate-mastic proportions in the RVE were obtained from the morphological image analysis. Macroscale model responses were compared with the AC pavement responses obtained from an instrumented pavement section subjected to falling weight deflectometer loading and a class 9 vehicle. Model responses are very close to the actual responses. The multiscale analyses show that tensile strain in microscale RVE is 5–10 times higher than that in a macroscale element. Furthermore, multiscale analyses also show that variations in the microscale RVE, such as the reduction in the aggregate-mastic ratio or increment in the voids, can increase the maximum tensile strain at the bottom of the AC in macroscale model by around 25%.
      Citation: Transportation Research Record
      PubDate: 2021-02-01T10:07:42Z
      DOI: 10.1177/0361198121989723
       
  • Estimation and Mitigation of Epidemic Risk on a Public Transit Route using
           Automatic Passenger Count Data
    • Authors: Pramesh Kumar, Alireza Khani, Eric Lind, John Levin
      Abstract: Transportation Research Record, Ahead of Print.
      This paper studies the potential spread of infectious disease through passenger encounters in a public transit system using automatic passenger count (APC) data. An algorithmic procedure is proposed to evaluate three different measures to quantify these encounters. The first two measures quantify the increased possibility of disease spread from passenger interaction when traveling between different origin–destination pairs. The third measure evaluates an aggregate measure quantifying the relative risk of boarding at a particular stop of the transit route. For calculating these measures, compressed sensing is employed to estimate a sparse passenger flow matrix planted in the underdetermined system of equations obtained from the APC data. Using the APC data of Route 5 in Minneapolis/St. Paul region during the COVID-19 pandemic, it was found that all three measures grow abruptly with the number of passengers on board. The passenger contact network is densely connected, which further increases the potential risk of disease transmission. To reduce the relative risk, it is proposed to restrict the number of passengers on-board and analyze the effect of this using a simulation framework. It was found that a considerable reduction in the relative risk can be achieved when the maximum number of passengers on-board is restricted below 15. To account for the reduced capacity and still maintain reasonable passenger wait times, it would then be necessary to increase the frequency of the route.
      Citation: Transportation Research Record
      PubDate: 2021-02-01T10:05:04Z
      DOI: 10.1177/0361198120985133
       
  • Risky Driving Behaviors of Drivers Who Use Alcohol and Cannabis
    • Authors: Tara Kelley-Baker, Leon Villavicencio, Lindsay S. Arnold, Aaron J. Benson, Victoria Anorve, Brian C. Tefft
      Abstract: Transportation Research Record, Ahead of Print.
      Many drivers in the United States use alcohol or cannabis, including some who co-use both substances. Using data from a nationally representative survey, self-reported engagement in various risky driving behaviors is examined among drivers who co-use alcohol and cannabis, those who use alcohol but not cannabis, those who use cannabis but not alcohol, and those who use neither. Results were adjusted for age, gender, education, and race. Co-users, compared with those who use only alcohol, were more likely to engage in nearly all of the risky behaviors measured in the survey, including driving under the influence of alcohol. Compared with those who neither drink nor use cannabis, those who use only cannabis were more likely to drive under the influence of prescription drugs, engage in aggressive driving, and ride with an intoxicated driver. Results of this and future related research will assist with understanding the differences in driving behavior among users of alcohol, cannabis, or both, so more effective interventions can be developed to improve traffic safety.
      Citation: Transportation Research Record
      PubDate: 2021-01-29T10:12:54Z
      DOI: 10.1177/0361198121989727
       
  • Predictive Analytics of Streetcar Bunching Occurrence Time for Real-Time
           Applications
    • Authors: Aya Aboudina, Ehab Diab, Amer Shalaby
      Abstract: Transportation Research Record, Ahead of Print.
      Bunching occurs when transit vehicles are unable to maintain their scheduled headways, resulting in two or more vehicles arriving at a stop in close succession and following each other too closely thereafter. Very few studies have explored the prediction of bunching in real-time, particularly for streetcar services. Predicting the time to bunching in real-time allows transit agencies to take more preventive actions to avoid the occurrence of bunching or to minimize its effects. In this study, we present a comprehensive literature review of the recent research conducted in bunching and real-time prediction models. Based on the findings from the literature review, we propose a model for real-time prediction of streetcar bunching. The Kalman filtering model predicts the travel time to bunching incidents and is tested and analyzed using an automatic vehicle location data feed for one streetcar route (Route 506 Carlton), obtained from the Toronto Transit Commission’s next bus system. The results show that: (1) the model provides good predication quality given that it relies only on the real-time GPS feed of streetcars, which makes it practical for use in real-time prediction applications; (2) the model prediction accuracy improves as the transit vehicle travels away from the terminal; and (3) increasing the number of past days involved in the calculations beyond 6 days or increasing the number of leading trips considered in the same day beyond 7 or 10 trips might increase the prediction error.
      Citation: Transportation Research Record
      PubDate: 2021-01-29T10:11:13Z
      DOI: 10.1177/0361198121990698
       
  • Development of High Friction Surface Treatment Prescreening Protocols and
           an Alternative Friction Application
    • Authors: Thomas Bennert, Robert Blight, Vahid Ganji, Drew Tulanowski, Susan Gresavage
      Abstract: Transportation Research Record, Ahead of Print.
      The use of high friction surface treatments (HFST) has become increasingly popular to help improve roadway friction properties and reduce the number of lane-departure and breaking-related accidents. Conventional HFST installation consists of applying an epoxy-resin material to an existing roadway surface and “gluing” a hard, highly angular fine aggregate to the roadway surface. When constructed correctly, skid resistance values (SN40) are often measured in the upper 60s and 70s. However, this functional overlay does not come without potential issues. Performance and service life is strongly dependent on the quality of the construction process, as well the quality of the substrate, which is often difficult to assess in situ. The paper summarizes the forensic testing of three HFST installations in New Jersey—one performing well and two showing premature failure. Testing procedures and preliminary criteria for existing asphalt pavement surfaces were developed to address whether or not epoxy-resin HFST is a viable option. Additionally, the paper summarizes the development and forensic testing of a potential alternative to the epoxy-resin based HFST application. This alternative surface, called a high friction chip seal (HFCS), incorporates the same hard, highly angular fine aggregate but using asphalt binder as the “gluing” medium within the chip seal application process. Three different aggregate sources were evaluated using the HFCS application on Rt 68 in New Jersey. Laboratory testing of the aggregates, as well as field measurements of the test sections, were conducted. It was found that HFCS could be a potential alternative for areas where premature HFST failure is a concern.
      Citation: Transportation Research Record
      PubDate: 2021-01-29T10:07:54Z
      DOI: 10.1177/0361198121990027
       
  • Measuring Benefits of Rural and Small Urban Transit in Greater Minnesota
    • Authors: Jeremy Mattson, Del Peterson
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this research was to measure the benefits of rural and small urban transit services in Minnesota. The study accomplished this by first identifying, describing, and classifying the potential benefits of transit. Second, a method was developed to measure these benefits. Where possible, benefits were quantified in dollar values. Other benefits that could not be quantified in monetary terms were either quantified in another way or described qualitatively. The study included an analysis of societal benefits and economic impacts within local communities. Third, the developed method was applied to a series of six case studies across Greater Minnesota. Data were collected through onboard rider surveys for each of the six transit agencies. Total benefits and benefit-cost ratios were estimated for the six transit agencies—all showed benefits that exceeded costs—and results were generalized to Greater Minnesota. Economic impacts were also estimated showing the effect on jobs, labor income, and value added. This research provides information to assess the benefits of public spending on transit, which gives decision makers the data needed to inform investment decisions.
      Citation: Transportation Research Record
      PubDate: 2021-01-29T10:05:34Z
      DOI: 10.1177/0361198121990014
       
  • Life-Extending Benefit of Chip Sealing for Pavement Preservation
    • Authors: Farhang Jalali, Adriana Vargas-Nordcbeck
      Abstract: Transportation Research Record, Ahead of Print.
      Chip seals are effective pavement preservation treatments that are usually applied to address non-fatigue cracking, weathering, and raveling, to seal the surface, to delay oxidation, and, finally, to improve skid resistance. This study used field performance data of test sections from the Pavement Preservation Group Study being conducted by the National Center for Asphalt Technology and the Minnesota DOT’s Road Research Facility. Data from test sections located in a low-traffic-volume road with a hot, wet, no-freeze climate collected over a period of 7 years were used to evaluate the effect of several chip seal treatments. Treatments range from single layer to multilayer systems, and include different construction techniques such as rejuvenating scrub seal and fiber membrane. Also, a section was crack sealed before the application of a single layer chip seal to assess the benefits. A semi-parametric survival analysis was performed to determine the differences in median time to failure (MTTF) for different chip seal sections versus a controlled section—representing a “do-nothing” scenario. The results showed that the MTTF for a single layer chip seal ranges from 6.8 to 9.1 years depending on the pretreatment condition. Crack sealing before chip seal could extend the MTTF by an additional 1–3 years, depending on initial conditions. Double and triple layer chip seals extend the MTTF beyond 10 years. Finally, the scrub seal provided the highest benefits, with survival rates close to 100% after 10 years of performance.
      Citation: Transportation Research Record
      PubDate: 2021-01-29T09:43:57Z
      DOI: 10.1177/0361198121989721
       
  • Transit Accessibility Measurement Considering Behavioral Adaptations to
           Reliability
    • Authors: Tierra S. Bills, Andre L. Carrel
      Abstract: Transportation Research Record, Ahead of Print.
      Accessibility measures are necessary for evaluating the benefits of proposed transportation improvements. However, they often do not account for travel time unreliability, but instead incorporate deterministic and time-invariant travel times. This approach risks mischaracterizing the accessibility experienced by travelers. In this paper, we review recent literature on accessibility and travel time reliability with a focus on transit and introduce an approach to joint accessibility-reliability measurement that relies on a behavioral perspective. Using this behavioral perspective, we propose that existing accessibility measures be implemented using travelers’ total travel time budget as a measure of travel time, and that varying departure time strategies depending on service characteristics be considered. The total travel time budget can reasonably be quantified with a high percentile of the total travel time distribution. However, we note that different percentiles may be more appropriate for different traveler types, as these percentiles correspond to varying tolerances for late arrivals. This behavioral perspective can be operationalized with commonly used accessibility measures, such as the cumulative opportunity measure, and with real-time vehicle location data. We include a demonstration of the potential changes in accessibility estimates when accounting for travel time unreliability, with a simplified case study of a transit route in San Francisco. The results show a considerable reduction of the number of opportunities available to travelers when the calculation is based on the latter—between 5.9% and 37.9% less, depending on various factors. Such differences have the potential to significantly affect the accessibility benefits of transit capital investments.
      Citation: Transportation Research Record
      PubDate: 2021-01-29T09:41:21Z
      DOI: 10.1177/0361198120986567
       
  • Exploring Travel Behavior of Households with Pre-School Aged Children
    • Authors: Muhammad Ahsanul Habib, Md Asif Hasan Anik, Caroline Robertson
      Abstract: Transportation Research Record, Ahead of Print.
      Child-care centers are major trip generators for households with pre-school aged children (
      Citation: Transportation Research Record
      PubDate: 2021-01-25T05:53:59Z
      DOI: 10.1177/0361198120988006
       
  • Understanding Google Location History as a Tool for Travel Diary Data
           Acquisition
    • Authors: Dillan Cools, Scott Christian McCallum, Daniel Rainham, Nathan Taylor, Zachary Patterson
      Abstract: Transportation Research Record, Ahead of Print.
      Understanding human mobility within urban settings is fundamental for urban and transport planning. Travel demand modeling and planning typically rely on data that are collected from large-scale household travel surveys (i.e., origin–destination surveys) and compiled into single- or multiple-day travel diaries. The laborious task of collecting these data has left traditional methods with numerous limitations, resulting in significant trade-offs in regard to accuracy, sample size, and study duration, while also being vulnerable to reporting and transcription error. Rising mobile phone ownership has provided opportunities to acquire expansive cellular network data from service providers and location-based service data through smartphone applications. At the same time, the Google Maps smartphone application provides built-in infrastructure that can passively collect detailed location information from user smartphone devices. The resulting data are known as Google location history (GLH). To better understand the potential of these data offerings in transportation modeling and planning, GLH data passively collected from five different smartphones following prescribed itineraries over 12 days was evaluated. As 51% of 934 locations and 32% of 888 trips were matched to the pre-determined travel diary data, it was determined that GLH data does not currently appear to be an adequate tool for travel diary data collection. On average, locations that were missed by GLH were shorter (mean of 355 s), whereas locations that were identified were longer (mean of 762 s).
      Citation: Transportation Research Record
      PubDate: 2021-01-23T11:12:25Z
      DOI: 10.1177/0361198120986169
       
  • Performance of Machine Learning Algorithms in Predicting the Pavement
           International Roughness Index
    • Authors: Mohammad Z. Bashar, Cristina Torres-Machi
      Abstract: Transportation Research Record, Ahead of Print.
      Significant research efforts have documented the capabilities of machine learning (ML) algorithms to model pavement performance. Several challenges, however, limit the implementation of ML by practitioners and transportation agencies. One of these challenges is related to the high variability in the performance of ML models as reported by different studies and the lack of quantitative evidence supporting the true effectiveness of these techniques. The objective of this paper is twofold: to assess the overall performance of traditional and ML techniques used to predict pavement condition, and to provide guidance on the optimal architecture and minimum sample size required to develop these models. This paper analyzes three ML algorithms commonly used to predict International Roughness Index (IRI)—Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM)—and compares their performance to traditional techniques. An inverse variance heterogeneity based meta-analysis is performed on 20 studies conducted between 2001 and 2020. The results indicate that ML algorithms capture on average 15.6% more variability than traditional techniques. RF is the most accurate technique with an overall performance value of 0.995. ANN is also identified as a highly effective technique that has been widely used and provides accurate predictions with both small and large sample sizes. For ANN algorithms, a single hidden layer with nodes equal to 0.3–2 times the number of input features is found to be sufficient in predicting pavement deterioration. A minimum sample size equal to 50 times the number of input variables is recommend to model pavement deterioration using ML.
      Citation: Transportation Research Record
      PubDate: 2021-01-19T12:18:37Z
      DOI: 10.1177/0361198120986171
       
  • Analytical Elastic Modeling of Rail and Fastener Longitudinal Response
    • Authors: Matheus Trizotto, Marcus S. Dersch, J. Riley Edwards, Arthur Lima
      Abstract: Transportation Research Record, Ahead of Print.
      The rail fastening system plays a critical role in maintaining proper railroad track geometry by transferring vertical, lateral, and longitudinal forces from the rails to crossties. Broken spikes in elastic fastening systems have been linked to inadequate transfer of longitudinal loads, posing a safety risk for timber crosstie ballasted track. Longitudinal track demand caused by passing trains has been investigated in previous research, but the magnitude and distribution of longitudinal fastener loads is not well understood or documented. To address these track component failures and improve fastener design, this paper presents a validated analytical model that estimates longitudinal rail seat loads, advancing current formulations to focus specifically on the rail seat. The validated method was used to quantify the distribution and magnitude of longitudinal loads in both the rail and fastening system caused by passing trains. Further, this paper quantifies the effect of track stiffness, number of powered locomotives, and wheel spacing on these distributions and magnitudes. This information provides valuable insight into the specific type of spike failures that have led to at least ten derailments and the requirement of manual walking inspections on multiple North American heavy axle load railroads as detailed in this paper. Further, this method can be used to quantify the longitudinal fastener loads for different track conditions to advance the mechanistic-empirical track design philosophy for elastic fastening systems.
      Citation: Transportation Research Record
      PubDate: 2021-01-16T09:14:36Z
      DOI: 10.1177/0361198120985848
       
  • Exploratory Analysis of Unmanned Aircraft Sightings using Text Mining
    • Authors: Subasish Das
      Abstract: Transportation Research Record, Ahead of Print.
      Because of recent technological advancements, a growing number of unmanned aircraft systems (UASs) are anticipated to occupy the U.S. National Airspace System (NAS) and operate side-by-side with human pilot controlled civil aircraft. UAS technology has transitioned to broader applications, including commercial, scientific, and expanded military use. There have been significant challenges concerning the safe and suitable integration of UASs with existing systems. The interaction between humans and increasingly automated systems is of concern to researchers. Additionally, the number of UAS sightings has increased significantly during the last few years. In this study, the research team compiled 7,400 reports of UAS sightings (2015–2018). The Latent Dirichlet Allocation (LDA) method was then applied to develop topics relevant to UAS sighting incidents. This study also developed an online interactive tool to show keywords associated with different topics. These interactive topic models can help policymakers establish new policies and regulations to address specific safety concerns.
      Citation: Transportation Research Record
      PubDate: 2021-01-16T05:52:06Z
      DOI: 10.1177/0361198120987230
       
  • Statewide Application of Wrong-Way Driving Crash Risk Modeling and
           Countermeasures Optimization Algorithm to Identify Optimal Locations for
           Countermeasure Deployment on Florida Limited Access Facilities
    • Authors: Adrian Sandt, Haitham Al-Deek, Patrick Blue, John McCombs
      Abstract: Transportation Research Record, Ahead of Print.
      Wrong-way driving (WWD) crashes can have significant impacts on freeway safety and operations. Deploying intelligent transportation systems (ITS) WWD countermeasures at freeway exit ramps can effectively reduce WWD crash risk (WWCR), but these countermeasures are expensive. In this paper, a WWCR segment model and WWD countermeasures optimization algorithm are developed for all Florida limited access facilities (56 roadways with 1,375 exits) to identify the optimal locations for ITS countermeasure deployment. These were previously developed for specific toll-road networks within Florida, but never for a statewide network. Multiple WWCR models were investigated, with the final Poisson model using four-exit segments and 5 years of WWD event data. This model showed that more WWD events and higher crossing road traffic volumes increased WWCR, while certain interchange designs increased or decreased WWCR. Sixty-three segments containing 169 exit ramps without ITS WWD countermeasures were identified as WWD hotspots; these ramps were compared with the 169 ramps with the highest WWCR selected by the optimization algorithm. The algorithm selected 96 ramps not in the hotspots (improved resource utilization of 56.8%) and provided a 38.6% increase in WWCR reduction. Comparing WWD detection and turnaround data from 31 sites with rectangular flashing beacon ITS countermeasures to the optimization indicated a significant positive association between WWCR and turnaround percentage (higher WWCR at sites with lower turnaround percentage), verifying the accuracy of the optimization. By showing the transferability, scalability, accuracy, and benefits of this approach, this paper can help agencies reduce WWD and improve freeway safety and operations.
      Citation: Transportation Research Record
      PubDate: 2021-01-16T05:49:28Z
      DOI: 10.1177/0361198120986562
       
  • Review of Tunnel Fire Damage Assessment Methods and Techniques
    • Authors: Nan Hua, Negar Elhami-Khorasani, Anthony Tessari
      Abstract: Transportation Research Record, Ahead of Print.
      Major tunnel fires can have catastrophic consequences, including loss of life, property damage, and long-term service disruptions. The rapid rise of gas temperature in excess of 1,000°C (1,832°F) inside a confined tunnel space as well as long fire duration because of limited emergency responder access necessitate special design considerations when evaluating the structural response to fire. Although tunnel stability is not challenged in most cases, severe damage to the concrete lining is observed after major fire events. This paper provides a detailed review of assessment methodologies and techniques of fire damage in concrete tunnel linings, including guidance on the determination of fire scenarios, concrete spalling, and tunnel safety from existing codes and guidelines, experiments, and numerical models. Based on the review, the need to develop relevant guidelines is emphasized, the knowledge gaps in the existing research are identified, and future research directions are proposed.
      Citation: Transportation Research Record
      PubDate: 2021-01-15T08:47:57Z
      DOI: 10.1177/0361198120987228
       
  • Sensitivity Analysis of the Transit Signal Priority Requesting Threshold
           and the Impact on Bus Performance and General Traffic
    • Authors: Michael H. Sheffield, Grant G. Schultz, David Bassett, Dennis L. Eggett
      Abstract: Transportation Research Record, Ahead of Print.
      An analysis was performed to evaluate the impact of changing the transit signal priority (TSP) requesting threshold on bus performance and general traffic, using field-generated data exclusively. Route 217, a conventional bus route that uses a dedicated short-range communication (DSRC)-based TSP system as part of its normal day-to-day operations, was analyzed over a three-month period from May 2019 through August 2019. The requesting thresholds evaluated for Route 217 were 3, 2, and 0 min, which stipulate how far behind schedule the bus must be to request TSP. For each requesting threshold, bus performance was evaluated through on-time performance (OTP), schedule deviation, travel time, and dwell time, while the traffic analysis was performed by evaluating split failure, change in green time, and the frequency at which TSP was served. A combination of observational and statistical analyses concluded with convincing evidence that OTP, schedule deviation, and travel time improve as the requesting threshold approaches zero with negligible impacts on general traffic. As the requesting threshold changed from 3, to 2, to 0 min, OTP increased 2.0% and 2.5%, respectively; mean schedule deviation improved by 15.9 s and 20.9 s, respectively; and travel time decreased at 75% of timepoints. Meanwhile, negative impacts to traffic occurred if an increase in split failure was measured after TSP was served, a phenomenon observed a maximum of once every 43 min. Thus, it is concluded that bus performance improves as the requesting threshold approaches zero with inconsequential impacts on general traffic.
      Citation: Transportation Research Record
      PubDate: 2021-01-15T08:46:57Z
      DOI: 10.1177/0361198120985853
       
  • Explorative Visualization for Traffic Safety using Adaptive Study Areas
    • Authors: Anne S. Berres, Haowen Xu, Sarah A Tennille, Joseph Severino, Srinath Ravulaparthy, Jibonananda Sanyal
      Abstract: Transportation Research Record, Ahead of Print.
      The pressing need to improve traffic safety has become a societal concern in many cities around the world. Many traffic accidents are not occurring as stand-alone events but as consequences of other road incidents and hazards. To capture the traffic safety indications from a holistic aspect, this paper presents a suite of visualization techniques to explore large traffic safety datasets collected from different sources using adaptive study areas which include the whole region (Hamilton County, Ohio, U.S.) as well as smaller sub-areas. In the present study, these data source include (1) Hamilton County’s 911 emergency response data, which includes traffic incidents as well as other types of incidents throughout the county, and (2) Tennessee crash data, which contains only vehicle crashes with more detail on the circumstances of each crash. Both abstract and spatial visualization techniques are used to derive a better understanding of traffic safety patterns for different traffic participants in various urban environments. In addition to the entire region of Hamilton County, safety is examined on the highways, in the downtown area, and in a shopping district east of the city center. It is possible to characterize incidents in the different areas, gain a better understanding of common incident patterns, and identify outliers in the data. Finally, a textured tile calendar is presented to compare spatiotemporal patterns.
      Citation: Transportation Research Record
      PubDate: 2021-01-15T08:45:13Z
      DOI: 10.1177/0361198120981065
       
  • Evaluation of Network-Level Data Collection Variability and its Influence
           on Pavement Evaluation Utilizing Random Forest Method
    • Authors: Xiaoyang Jia, Mark Woods, Hongren Gong, Di Zhu, Wei Hu, Baoshan Huang
      Abstract: Transportation Research Record, Ahead of Print.
      The use of pavement condition data to support maintenance and resurfacing strategies and justify budget needs becomes more crucial as more data-driven approaches are being used by the state highway agencies (SHAs). Therefore, it is important to understand and thus evaluate the influence of data variability on pavement management activities. However, owing to a huge amount of data collected annually, it is a challenge for SHAs to evaluate the influence of data collection variability on network-level pavement evaluation. In this paper, network-level parallel tests were employed to evaluate data collection variability. Based on the data sets from the parallel tests, classification models were constructed to identify the segments that were subject to inconsistent rating resulting from data collection variability. These models were then used to evaluate the influence of data variability on pavement evaluation. The results indicated that the variability of longitudinal cracks was influenced by longitudinal lane joints, lateral wandering, and lane measurement zones. The influence of data variability on condition evaluation for state routes was more significant than that for interstates. However, high variability of individual metrics may not necessarily lead to high variability of combined metrics.
      Citation: Transportation Research Record
      PubDate: 2021-01-15T08:41:19Z
      DOI: 10.1177/0361198120980435
       
  • Estimating Fatality and Injury Savings Because of Deployment of Advanced
           Wrong-Way Driving Countermeasures on a Toll Road Network
    • Authors: Adrian Sandt, Haitham Al-Deek
      Abstract: Transportation Research Record, Ahead of Print.
      Limited access facility wrong-way driving (WWD) crashes are typically more severe than other crashes. Deploying advanced WWD countermeasures, such as rectangular flashing beacon (RFB) and light-emitting diode (LED) technologies, at exit ramps can reduce WWD crashes, injuries, and fatalities. No previous research has developed a methodology to quantify the potential fatality and injury savings because of future countermeasure deployments. This paper developed such a methodology and applied it to Florida’s Turnpike Enterprise (FTE) toll road network. From 2011–2016, there were 53 FTE WWD crashes, resulting in 16 fatalities and annual injury costs of $37 million. The proportion of these crashes occurring during night-time was 87%. RFB and LED life-cycle injury savings and costs were determined for all 216 FTE exits. The total savings were $424 million for RFBs (benefit–cost [B/C] ratio of 23.20) and $144 million for LEDs (B/C ratio of 13.13). Deploying countermeasures at the 103 exits with the highest B/C ratios would provide 70% of the total possible savings by equipping 40% of the ramps. For the same capital investment, RFBs provide more savings than LEDs. Spending $1 million to deploy RFBs will provide similar savings as spending $3.4 million to deploy LEDs. Evaluating the existing FTE RFB and LED ramps shows that RFBs are more effective at night-time and can provide three times the savings of LEDs. The results of this paper show the improved performance of RFBs over LEDs and provide an example that other agencies could follow to identify savings and cost-effectively deploy advanced WWD countermeasures.
      Citation: Transportation Research Record
      PubDate: 2021-01-12T05:34:14Z
      DOI: 10.1177/0361198120986573
       
  • Evaluating the Role and Evolution of Factors Influencing Rapid Transit
           Planning in Ecuador
    • Authors: Juan F. Arias, Chris Bachmann
      Abstract: Transportation Research Record, Ahead of Print.
      In practice, the process of transportation planning is shaped by more than technical factors. This paper analyzes how different factors (demand, local conditions, financial, social, and political) have influenced all of the rapid transit projects in Ecuador over the past three decades by evaluating their relative significance on each system component (alignment, size, and technology). This research uses a multiple-case methodology including in-depth interviews with the senior members of the technical teams, as well as a survey component based on the analytic hierarchy process for quantification of the relative significance of the factors. The comparative analysis of projects shows five key results: (1) Each project was unique and external factors introduced a varying degree of complexity into each planning process; (2) The systems’ alignments and sizes were mostly driven by demand and local conditions (rational planning process); (3) The main factor driving technology selection has evolved over time from system demand to political (political bargaining approach); (4) Negative economic conditions had a large influence on the factors of all project components; (5) There is a lack of rational alternative evaluation and an absence of corresponding tools/guidelines in Ecuador. Nonetheless, several processes included practices that contributed to a more rational planning process: lifecycle cost analysis for the various technology alternatives, explicit decision-maker guidelines, transferring the demand risk to the private sector, and the use of multicriteria decision analysis. Implications for future planning efforts are discussed.
      Citation: Transportation Research Record
      PubDate: 2021-01-12T05:24:12Z
      DOI: 10.1177/0361198120986170
       
  • Incorporating Speed in a Traffic Conflict Severity Index to Estimate Left
           Turn Opposed Crashes at Signalized Intersections
    • Authors: Alireza Jafari Anarkooli, Bhagwant Persaud, Craig Milligan, Joel Penner, Taha Saleem
      Abstract: Transportation Research Record, Ahead of Print.
      Rigorous evaluation of implemented safety treatments, especially for innovative treatments and those targeted at rare crash types, is challenging to accomplish with conventional crash-based analyses. This paper aims to address this challenge for treatments at urban signalized intersections by providing a methodology that uses surrogate measures of safety obtained from video analytics to predict changes in crashes. To develop this approach, left turn opposed traffic conflicts based on post-encroachment times, along with corresponding conflicting vehicle speeds, are first measured from video observations at signalized intersections. The conflicts are then classified into three severity levels using a risk score function defined by these measures. Multiple linear regression models are developed to relate left turn opposed crashes at the same intersections in the period 2009–2014 to the correspondingly classified conflicts. The results show strong relationships between the classified conflicts and crashes (adjusted [math] of 85% and 94% for total and fatal/injury crashes, respectively). The results also reveal that the contribution of conflicts to the risk of crashes varies based on speed dimension of their severity, suggesting that neglecting speed as a factor in conflict severity levels may be at the expense of losing meaningful information. The models can be applied to estimate the change in crashes following a safety treatment by observing, through video analytics, the change in conflicts and speeds and using the crash-conflict-speed model. The methodological approach is viable for quickly evaluating all treatments and, in particular, innovative ones for which knowledge on safety effects is sparse or non-existent.
      Citation: Transportation Research Record
      PubDate: 2021-01-12T05:23:12Z
      DOI: 10.1177/0361198120986167
       
  • Survey of Practices on Performance Measurement of U.S. Inland Waterway
           Freight Transportation
    • Authors: Nahid Parvez Farazi, Bo Zou, P.S. Sriraj
      Abstract: Transportation Research Record, Ahead of Print.
      The inland waterway freight transportation system plays a vital role in the trade and commerce of the U.S.A. To ensure that the system performs at an acceptable level, routine monitoring and performance evaluation of the system is critical. Individual states are responsible for developing and implementing suitable performance measurement systems for their respective inland waterways. This paper focuses on surveying, reviewing, and synthesizing current performance measurement practices adopted by different states in the U.S.A. It finds that, among the 38 states with inland navigability, only 12 states have established performance measures to monitor the performance of their inland water transportation systems. To aid the states in developing and enhancing inland waterway performance measurement programs, the paper further outlines the current state of research on inland waterways, recommendations from various federal and maritime organizations, and also current practice outside of the U.S.A. Based on a scan of the publicly available data sources, the paper proposes a two-dimensional performance measurement practice from the perspectives of performance areas and infrastructure types. Such an approach will help state Departments of Transportation to identify system needs and deficiencies while offering a comprehensive picture of performance of an inland water freight transportation system.
      Citation: Transportation Research Record
      PubDate: 2021-01-12T05:15:38Z
      DOI: 10.1177/0361198120985220
       
  • Development and Testing of Structurally Independent Foundations for
           High-Speed Containment Concrete Barrier
    • Authors: James Kovar, Nauman Sheikh, Roger Bligh, Sofokli Cakalli, Taya Retterer, Jon Ries
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents the development and testing of single slope barriers with independent foundations that can be installed at a wide range of site conditions. The researchers developed designs of barriers with foundation systems by conducting a series of finite element simulations and performing full-scale vehicle impact tests under the American Association of State Highway and Transportation Officials’ (AASHTO) Manual for Assessing Safety Hardware (MASH) Test Level 5 (TL-5) and Test Level 4 (TL-4) conditions. In this process, foundation designs were developed for site conditions that may require shallow foundations, or foundations that have a smaller footprint. Depending on the site conditions and the presence of underground structures, designers could select the most fitting option from these designs. Impact performance of the developed barrier and foundation systems was evaluated using full-scale finite element impact simulations under MASH TL-5 and TL-4 impact conditions. Two critical systems were selected for full-scale crash testing: a 54 in. tall single slope barrier with drilled shaft foundations, and a 36 in. tall single slope barrier with moment slab foundation. The barrier with the drilled shaft foundation system was tested to MASH Test 5-12 conditions, and the barrier with the moment slab foundation system was tested to MASH Test 4-12 conditions. Both systems performed acceptably with respect to the MASH criteria. This paper presents the various barrier and foundation designs that were developed, key results from the simulation analyses, and details of the crash testing performed on the two selected systems.
      Citation: Transportation Research Record
      PubDate: 2021-01-11T09:07:43Z
      DOI: 10.1177/0361198120980325
       
  • Evaluation Methodology of Leader-Follower Autonomous Vehicle System for
           Work Zone Maintenance
    • Authors: Qing Tang, Yanqiu Cheng, Xianbiao Hu, Chenxi Chen, Yang Song, Ruwen Qin
      Abstract: Transportation Research Record, Ahead of Print.
      Mobile and slow-moving operations, such as striping, sweeping, bridge flushing, and pothole patching, are critical for efficient and safe operation of a highway transportation system. However, reducing hazards for roadway workers and achieving a safer environment for both roadway maintenance operators and the public is a challenging problem. In 2017 alone, a total of 158,000 vehicle crashes occurred in work zones in the U.S.A., accounting for 61,000 injuries. The autonomous truck-mounted attenuator (ATMA) vehicle, sometimes referred to as an autonomous impact protection vehicle (AIPV), offers a promising solution to eliminate injuries to roadway maintenance workers and the public. This paper presents the evaluation methodology for the ATMA system, as well as the outcomes of field testing in Sedalia, Missouri. To the best of the authors’ knowledge, this is the first academic research to focus on ATMA. The ATMA system is first reviewed, followed by an introduction to the field testing procedures that includes descriptions of test cases and data collected, and their format. An analysis methodology is then proposed to quantitatively evaluate the system’s performance, and statistical models and hypothesis testing procedures are developed and presented. The numerical analysis results from real-world field testing under a controlled environment are presented, and the ATMA system’s performance is summarized. This paper can serve as a reference for transportation agencies that are interested in deploying similar technologies or for academic researchers to assess characteristics of autonomous vehicles and to apply knowledge gained in transportation modeling and simulation practices.
      Citation: Transportation Research Record
      PubDate: 2021-01-08T05:53:31Z
      DOI: 10.1177/0361198120985233
       
  • Risk Mitigation Planning for Revenue Service Testing of Bus Automated
           Emergency Braking
    • Authors: Heidi H. Soule, Adam Davis, Andrew Krum, Yinhai Wang, Ruimin Ke, Dave Valadez, Dan Sellers, Steve Roberts, Luke Fischer, Jerome M. Lutin
      Abstract: Transportation Research Record, Ahead of Print.
      In 2017, the Federal Transit Administration awarded Pierce Transit of Lakewood, WA, a $1.66 m grant for a bus collision avoidance and mitigation safety research and demonstration project. The project scope includes installation of an advanced technology package, the Pedestrian Avoidance Safety System (PASS) that uses light detection and ranging (LiDAR) sensors to trigger automated deceleration and braking. Thirty transit buses are being equipped with PASS and will be monitored using telematics to transmit and collect critical test data. The test plan includes collecting data while operating the buses in “stealth mode” with PASS detecting and logging events, but not activating brakes automatically or warning the drivers. At the conclusion of “stealth mode” operation, Pierce Transit will make a go/no-go decision on whether to activate PASS’s automatic deceleration and braking functionality for revenue service with passengers. This paper describes the risk mitigation process developed to determine if the system is safe enough to allow operation in revenue service. The process includes: broad stakeholder engagement, constituting an ad-hoc working group within Pierce Transit to advise executive management, development of decision-making criteria, consultation with state and federal officials on regulatory requirements and compliance, review of applicable standards and engineering test protocols, engineering consultations with the bus original equipment manufacturer, and road testing to simulate revenue service, collect data, and obtain feedback from drivers and maintainers.
      Citation: Transportation Research Record
      PubDate: 2021-01-06T10:45:18Z
      DOI: 10.1177/0361198120985857
       
  • Warning Light Flash Frequency as a Method for Visual Communication to
           Drivers
    • Authors: Nicholas P. Skinner, Timothy T. LaPlumm, John D. Bullough
      Abstract: Transportation Research Record, Ahead of Print.
      Service vehicles use flashing warning lights to indicate their presence to approaching drivers. Present standards offer ranges of flash frequencies to enhance conspicuity and avoid potential risks of photosensitive epilepsy or other issues. But, in practice, the flash frequency is not varied in specific situations. Previous studies have indicated that people interpret faster flash frequencies as more “urgent” than slower flash frequencies. Building on these findings, a laboratory study was conducted to identify whether drivers might be able to use cues from the frequency of flashing warning lights to anticipate how a service vehicle might behave in a work zone or other incident scene. The results suggest that even if they are not taught about the interpretation of different flash frequencies, drivers can differentiate between 1 Hz and 4 Hz flashing lights and learn to make accurate predictions about their meaning. The results also indicate that there are no reliable differences between 1 Hz and 4 Hz flashing in relation to a driver’s ability to detect when a service vehicle has begun to move. Based on the results, a preliminary suggestion is made to use lights flashing at 1 Hz when a service vehicle is moving forward, and 4 Hz when it is traveling in reverse.
      Citation: Transportation Research Record
      PubDate: 2021-01-06T09:55:14Z
      DOI: 10.1177/0361198120983325
       
  • Automatic Communication Error Detection Using Speech Recognition and
           Linguistic Analysis for Proactive Control of Loss of Separation
    • Authors: Zhe Sun, Pingbo Tang
      Abstract: Transportation Research Record, Ahead of Print.
      Losses of separation (LoS) are breaches of regulations that specify the minimum distance between aircraft in controlled airspace. Erroneous communications between air traffic controllers (ATCs) and pilots are leading contributors to LoS that result in elevated risk of fatal accidents. An air traffic control system that could identify communication errors promptly would, therefore, be advantageous. Establishing such a system requires a systematic characterization of communication errors to reveal how various communication arrangements and errors influence the development of LoS. Such know-how could guide the ATCs and pilots in identifying the parts of their communication processes and content that most influence the occurrence of LoS. Existing studies of LoS focus on simulation of aircraft operation processes with little quantitative analysis about how communication issues arise and result in elevated risks of LoS. This paper presents a method for supporting automatic communication error detection through integrated use of speech recognition, text analysis, and formal modeling of airport operational processes. The proposed method focuses on: identifying communication features to guide the detection of vulnerable communications; characterizing communication errors; and Bayesian Network modeling for predicting communication errors and LoS using the features derived from ATC–pilot communications. Major findings show that incorrect read-backs by pilots are highly correlated with a majority of LoS. Results indicate the proposed method could form a basis for automating communication error detection and preventing LoS. The integrated Automatic Speech Recognition and Natural Language Processing functions may be incorporated into existing aviation applications for real-time ATC–pilot communication monitoring and preventive LoS control.
      Citation: Transportation Research Record
      PubDate: 2021-01-06T09:48:54Z
      DOI: 10.1177/0361198120983004
       
  • Electric Vehicle Charger Placement Optimization in Michigan Considering
           Monthly Traffic Demand and Battery Performance Variations
    • Authors: Fatemeh Fakhrmoosavi, MohammadReza Kavianipour, MohammadHossein (Sam) Shojaei, Ali Zockaie, Mehrnaz Ghamami, Joy Wang, Robert Jackson
      Abstract: Transportation Research Record, Ahead of Print.
      Limited charging infrastructure for electric vehicles (EVs) is one of the main barriers to adoption of these vehicles. In conjunction with limited battery range, the lack of charging infrastructure leads to range-anxiety, which may discourage many potential users. This problem is especially important for long-distance or intercity trips. Monthly traffic patterns and battery performance variations are two main contributing factors in defining the infrastructure needs of EV users, particularly in states with adverse weather conditions. Knowing this, the current study focuses on Michigan and its future needs to support the intercity trips of EVs across the state in two target years of 2020 and 2030, considering monthly traffic demand and battery performance variations. This study incorporates a recently developed modeling framework to suggest the optimal locations of fast EV chargers to be implemented in Michigan. Considering demand and battery performance variations is the major contribution of the current study to the proposed modeling framework by the same authors in the literature. Furthermore, many stakeholders in Michigan are engaged to estimate the input parameters. Therefore, the research study can be used by authorities as an applied model for optimal allocation of resources to place EV fast chargers. The results show that for charger placement, the reduced battery performance in cold weather is a more critical factor than the increased demand in warm seasons. To support foreseeable annual EV trips in Michigan in 2030, this study suggests 36 charging stations with 490 chargers and an investment cost of $23 million.
      Citation: Transportation Research Record
      PubDate: 2021-01-06T06:31:41Z
      DOI: 10.1177/0361198120981958
       
  • Extraction of Road Lane Markings from Mobile LiDAR Data
    • Authors: Mustafa Zeybek
      Abstract: Transportation Research Record, Ahead of Print.
      This study presents a method for automatic extraction of road lane markings from mobile light detection and ranging (LiDAR) data. Road lanes and traffic signs on the road surface provide safe driving for drivers and aid traffic flow movement along the highway and street. Mobile LiDAR systems acquire massive datasets very quickly in a short time. To simplify the data structure and feature extraction, it is essential for traffic management personnel to apply the right methods. Road lanes must be visible and are a major factor in road safety for drivers. In this study, a methodology is devised and implemented for the extraction of features such as dashed lines, continuous lanes, and direction arrows on the pavement from point clouds. Point cloud data was collected from the Riegl VMX-450 mobile LiDAR system. The alpha shape algorithm is implemented on a point cloud and compared with the widespread use of edge detection techniques applied for intensity-based raster images. The proposed methodology directly extracts three-dimensional and two-dimensional road features to control the quality of road markings and spatial positions with the obtained marking boundaries. State-of-the-art results are obtained and compared with manually digitized reference markings. The standard deviations were evaluated and acquired for intensity image-based and direct point cloud-based extractions, at 1.2 cm and 1.7 cm, respectively.
      Citation: Transportation Research Record
      PubDate: 2021-01-06T06:27:18Z
      DOI: 10.1177/0361198120981948
       
  • Influence of Rail Transit on Development Patterns in the Mountain
           Mega-Region with a Surprise and Implications for Rail Transit and Land-Use
           Planning
    • Authors: Arthur C. Nelson, Robert Hibberd
      Abstract: Transportation Research Record, Ahead of Print.
      Between 2020 and 2050, all states comprising the Mountain Mega-Region (MMR—Arizona, Colorado, Nevada, New Mexico, and Utah) will be among the top 10 fastest growing U.S. states. They also have among the nation’s largest shares of land area in federal, state, public, and tribal land ownership. This has led to concentrations of populations in their metropolitan areas. Indeed, in 2020, the metropolitan areas of more than one million residents—Albuquerque, Las Vegas, Phoenix, Salt Lake City, and Tucson—comprise more than 70% of their states’ populations. With rapid growth combined with land constraints, many of these metropolitan areas are using rail transit systems to help meet transportation needs while also influencing development patterns in intended ways. If they are effective, these rail transit systems will: (a) create commercial real estate rent premiums; (b) attract jobs; and (c) attract households to areas near rail stations. We report the effectiveness of MMR rail transit systems in each of these respects. We also present a surprise: Contrary to conventional wisdom, it is households with children that locate closest to rail stations than single persons and childless households. We reason that improved planning is needed to meet the market demand for development throughout the half-mile circle around transit stations in the MMR’s metropolitan areas. If this can be done, all development in these MMR metropolitan areas may occur near rail transit stations.
      Citation: Transportation Research Record
      PubDate: 2021-01-06T06:24:01Z
      DOI: 10.1177/0361198120980439
       
  • Train Scheduling Method to Reduce Substation Energy Consumption and Peak
           Power of Metro Transit Systems
    • Authors: Bo Jin, Xiaoyun Feng, Qingyuan Wang, Pengfei Sun, Qian Fang
      Abstract: Transportation Research Record, Ahead of Print.
      The rapid development of metro transit systems brings very significant energy consumption, and the high service frequency of metro trains increases the peak power requirement, which affects the operation of systems. Train scheduling optimization is an effective method to reduce energy consumption and substation peak power by adjusting timetable parameters. This paper proposes a train timetable optimization model to coordinate the operation of trains. The overlap time between accelerating and braking phases is maximized to improve the utilization of regenerative braking energy (RBE). Meanwhile, the overlap time between accelerating phases is minimized to reduce the substation peak power. In addition, the timetable optimization model is rebuilt into a mixed integer linear programming model by introducing logical and auxiliary variables, which can be solved by related solvers effectively. Case studies based on one of Guangzhou Metro Lines indicate that, for all-day operation, the utilization of RBE would likely be improved on the order of 23%, the substation energy consumption would likely be reduced on the order of 14%, and the duration of substation peak power would likely be reduced on the order of 66%.
      Citation: Transportation Research Record
      PubDate: 2021-01-06T05:17:22Z
      DOI: 10.1177/0361198120974677
       
  • Experimental Study on Mix Ratio Design and Road Performance of Medium and
           Small Deformation Seamless Expansion Joints of Bridges
    • Authors: Pengzhen Lu, Chenhao Zhou, Simin Huang, Yang Shen, Yilong Pan
      Abstract: Transportation Research Record, Ahead of Print.
      Expansion joints are a weak and fragile part of bridge superstructure. The damage or failure of the expansion joint will lead to the decline of bridge durability and endanger the bridge structure and traffic safety. To improve the service life and performance of bridge expansion joints, the ideal method is to use seamless expansion joints. In this study, starting from the commonly used asphalt mixture gradation of seamless expansion joint, and taking into account the actual situation of bridge expansion joint structure and environment in China, the gradation and asphalt-aggregate ratio are preliminarily designed. Through a Marshall test, the corresponding asphalt mixture is evaluated and analyzed according to the stability, flow value, and void ratio, and the optimal gradation and asphalt-aggregate ratio are determined. Finally, the asphalt mixture is prepared with the mixture ratio design, and the test results of an immersion Marshall test, fatigue performance test, and full-scale test verify that the asphalt mixture meets the road performance requirements of seamless expansion joints. On the basis of the experimental data, the performance of large sample asphalt mixture is continuously tested, compared, and optimized. The results show that the asphalt mixture ratio designed is true and reliable, which can provide reference for the optimal design of seamless expansion joint filler.
      Citation: Transportation Research Record
      PubDate: 2021-01-04T09:39:03Z
      DOI: 10.1177/0361198120984741
       
  • Feature Selection for Enhancing Purpose Imputation using Global
           Positioning System Data without Geographic Information System Data
    • Authors: Minh Hieu Nguyen, Jimmy Armoogum, Emeli Adell
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a method for enhancing purpose imputation from global positioning system data without using geographic information system data via relevant feature selection from six groups: (1) activity time; (2) user characteristics; (3) predicted travel modes; (4) actual travel modes; (5) estimated home location; and (6) estimated location of the most frequently visited non-home place (MFVP). Two datasets were collected in 2019 using TRavelVU, a smartphone application. The first one (the Hanoi dataset) comprised 652 days’ worth of data collected from 63 users in Hanoi, Vietnam, whereas the second one (the Donate dataset) comprised 932 days’ worth of information collected from 65 individuals in Denmark, Sweden, and Norway. The hyperparameters of the random forest models were tuned carefully in accordance with selected features, thereby facilitating a thorough evaluation of the improvement in prediction models. The findings of this study revealed that the addition of either actual or predicted modes resulted in improved imputation performance, albeit the former exhibited a stronger positive effect. This demonstrated the potential benefits of integrating mode detection and purpose identification into a continuous process. The newly adopted MFVP feature contributed to enhanced prediction results (around 2%). The proposed purpose-imputation models, which benefited from all features, demonstrated accuracies of the order of 75% and 85% for the Hanoi and Donate datasets, respectively. The imputation of home and work/education activities demonstrated high success, whereas reasonable prediction results with nearly all F-score levels ranging between 50% and 83% were observed for pick-up/drop-off, shopping/eating, visit/leisure, and business activities.
      Citation: Transportation Research Record
      PubDate: 2021-01-01T06:17:09Z
      DOI: 10.1177/0361198120983006
       
  • Evaluation of Airport Wayfinding Accessibility with the Use of a
           Wheelchair Simulator
    • Authors: Zhu Qing, Carlos Sun, Joseph Reneker
      Abstract: Transportation Research Record, Ahead of Print.
      As the number of air passengers with disabilities is expected to increase in the coming decades, the significance of airport wayfinding accessibility has been recognized by airport stakeholders. Emerging assistive technologies have been used to accommodate passengers’ wayfinding needs; however, because of non-standard practices and the complexity of terminal designs, the literature only provides general guidance on improving airport wayfinding accessibility. There is a need for detailed analysis of quantitative traveler performance measures to evaluate airport wayfinding accessibility. This research is the first use of a wheelchair simulator to compare airport wayfinding signage with a mobile wayfinding application. A virtual model of the St. Louis Lambert International Airport main terminal was replicated using as-built computer-aided-design files. A federated simulation architecture was used to integrate the wheelchair simulator with a mobile wayfinding application. Wheelchair simulator experiments were conducted by analyzing twenty-four wheelchair users’ performance measures and eye tracking data. Although the mobile wayfinding application did not significantly reduce total travel time (–23.8 s) and deviation ratio (–3%), it reduced wheelchair users’ reliance on wayfinding signs by decreasing total glance frequency (–23.3 times) and total glance duration (–26.7 s) and helped to reduce travel anxiety in wheelchair users. The potential benefits of a mobile wayfinding application include improving traveler levels of service, reducing airport operating costs, and enhancing non-airline revenue. Overall, this study showed that, with the use of a wheelchair simulator, passenger performance could be captured and analyzed for evaluating the effectiveness of airport wayfinding accessibility and emerging assistive technologies.
      Citation: Transportation Research Record
      PubDate: 2021-01-01T06:13:08Z
      DOI: 10.1177/0361198120980445
       
  • Field Determined Live Load Distribution Factors for Modular
           Press-Brake-Formed Tub Girders
    • Authors: Karl E. Barth, Gregory K. Michaelson, Adam D. Roh, Robert M. Tennant
      First page: 1
      Abstract: Transportation Research Record, Ahead of Print.
      This paper is focused on the field performance of a modular press-brake-formed tub girder (PBFTG) system in short span bridge applications. The scope of this project to conduct a live load field test on West Virginia State Project no. S322-37-3.29 00, a bridge utilizing PBFTGs located near Ranger, West Virginia. The modular PBFTG is a shallow trapezoidal box girder cold-formed using press-brakes from standard mill plate widths and thicknesses. A technical working group within the Steel Market Development Institute’s Short Span Steel Bridge Alliance, led by the current authors, was charged with the development of this concept. Research of PBFTGs has included analyzing the flexural bending capacity using experimental testing and analytical methods. This paper presents the experimental testing procedures and performance of a composite PBFTG bridge.
      Citation: Transportation Research Record
      PubDate: 2021-01-09T09:08:45Z
      DOI: 10.1177/0361198120983757
       
  • Contrasting Perspectives on the Comfort and Safety of Pedestrians
           Interacting with Other Road Users
    • Authors: Alexander Bigazzi, Gurdiljot Gill, Meghan Winters
      First page: 33
      Abstract: Transportation Research Record, Ahead of Print.
      Assessments of interactions between road users are crucial to understanding comfort and safety. However, observers may vary in their perceptions and ratings of road user interactions. The objective of this paper is to examine how perceptions of yielding, comfort, and safety for pedestrian interactions vary among observers, ranging from members of the public to road safety experts. Video clips of pedestrian interactions with motor vehicles and bicycles were collected from 11 crosswalks and shown to three groups of participants (traffic safety experts, an engaged citizen advisory group, and members of the general public) along with questions about yielding, comfort, and risk of injury. Experts had similar views of yielding and comfort to the other two groups, but a consistently lower assessment of injury risk for pedestrians in the study. Respondent socio-demographics did not relate to perceptions of yielding, comfort, or risk, but self-reported travel habits did. Respondents who reported walking more frequently rated pedestrian comfort as lower, and respondents who reported cycling more frequently rated risk as lower for pedestrian interactions with both motor vehicles and bicycles. Findings suggest small groups of engaged citizens can provide useful information about public perspectives on safety that likely diverge from expert assessments of risk, and that sample representation should be assessed in relation to travel habits rather than socio-demographics.
      Citation: Transportation Research Record
      PubDate: 2021-02-12T10:41:20Z
      DOI: 10.1177/0361198121992272
       
  • Transit Economic Equity Index: Developing a Comprehensive Measure of
           Transit Service Equity
    • Authors: Torrey Lyons, Dong-ah Choi
      First page: 288
      Abstract: Transportation Research Record, Ahead of Print.
      In this study an index is developed called the Transit Economic Equity Index, to enable quantitative assessment of transit service equity. The index measures convenience of travel for work trips for advantaged and disadvantaged populations, based on travel speed, using a multimodal network that includes transit lines, stop locations, transit schedules, and pedestrian connections via the street network. Non-peak hour service is compared with peak hour service to determine the degree to which operating resources are concentrated in times that might have greater benefits to advantaged populations. Finally, accessibility to the transit system is compared in relation to the number of transit stops in neighborhoods and employment centers, and these figures are compared between advantaged and disadvantaged locations. The scores for these three components are combined to create a single measure of transit economic equity. Disadvantage is defined using criteria established in Title VI of the Civil Rights Act of 1964. The index is constructed in a way that balances a robust and meaningful measure of transit equity that is decipherable by practitioners so that they can assess the equity of their systems as well as how potential service changes affect equity.
      Citation: Transportation Research Record
      PubDate: 2021-01-08T05:13:50Z
      DOI: 10.1177/0361198120970529
       
  • Using Taxi GPS Trajectory Data to Optimize the Spatial Layout of Urban
           Taxi Stands
    • Authors: Xin Wang, Zhaowei Qu, Xianmin Song, Haitao Li, Zhaotian Pan
      First page: 301
      Abstract: Transportation Research Record, Ahead of Print.
      The unreasonable layout of taxi stands (TS) in urban areas not only fails to provide bidirectional guidance for drivers and passengers but also wastes spatial resources and aggravates the surrounding traffic. This paper compares the performance of three classical location models in optimizing TS spatial layout, and develops an extended model integrating the p-median and distance factor to support TS site selection in urban planning from multiple perspectives. To this end, taxi demand with spatial–temporal dynamics is extracted from taxi global positioning system (GPS) data to uncover the restrictive distribution characteristics of the setting areas and specific locations of TS with GIS platform. Taxi demand is then subdivided, and potential service points are set up on the road network. With the constraints of the supply and demand environment, we design the TS location models (TSLM) based on the set covering problem (SCP), the maximal covering location problem (MCLP), and the p-median problem (PMP), respectively. Furthermore, the TSLM based on PMP is extended to consider the maximum acceptable distance for passengers. A genetic algorithm-based procedure is introduced for solving the extended TSLM. An experiment conducted in China compares the facility coverage capacity, taxi demand allocation, and passenger access willingness of the optimal layout schemes obtained from four TSLMs. The number of parking spaces at TS is also evaluated. The result demonstrates that extended TSLM outperforms the other three models in the validity of locating TS.
      Citation: Transportation Research Record
      PubDate: 2021-01-01T06:11:50Z
      DOI: 10.1177/0361198120970537
       
  • Value-Based Approach to Assess the Impact of Lifestyles on Mode Shares
    • Authors: Veronique Van Acker, Sazkia Sandoval, Mario Cools
      First page: 313
      Abstract: Transportation Research Record, Ahead of Print.
      Travel behavior research has long been dominated by a rational perspective considering primarily objective factors such as price, travel time, and speed. Only at the end of the 1990s was attention also paid to subjective factors such as perceptions and attitudes. Since then, a growing number of studies combine objective and subjective factors in explaining travel behavior. This paper adds to this by focusing on the influence of lifestyles on mode share. To this end, an online survey was carried out in Belgium, completed successfully by 334 respondents. Lifestyles were measured based on a psychographic or value-based approach using the Portrait Values Questionnaire (PVQ) developed by Schwartz. Results of a structural equation model (SEM) indicate that using value-based lifestyles adds new insights to the analysis of mode share. Personal values have not only a direct effect on mode share but also an indirect effect because of interactions with urban residential location choices, car ownership decisions, and activity patterns. The findings suggest that public transport use could be encouraged by promoting it as an act of caring for others. At the same time, policy-makers should invest in creating positive experiences for travelers using public transport.
      Citation: Transportation Research Record
      PubDate: 2021-01-11T09:03:42Z
      DOI: 10.1177/0361198120971261
       
  • Multi-Intersection Control with Deep Reinforcement Learning and
           Ring-and-Barrier Controllers
    • Authors: Matthew Muresan, Guangyuan Pan, Liping Fu
      Abstract: Transportation Research Record, Ahead of Print.
      This paper discusses a machine-learning traffic signal control method. A full-scale corridor is analyzed and the transferability of using a model pre-trained on a single intersection is examined. Two controller designs are explored, a simple two-phase design and a full ring-and-barrier style controller. The full ring-and-barrier controller adapts many of the key features present in traditional controllers, such as protected-permissive left turns, so that they can be used in the reinforcement learning (RL) paradigm. This study is the first to propose a method that uses deep reinforcement learning (DRL) to implement a full ring-and-barrier style controller. The study also examines the feasibility of using transfer learning to pre-train a model on a single intersection and then fine-tune it for application in a complete environment. Training is done on a simple four lane intersection and the pre-trained model is then transferred for fine-tuning to six controllers operating on a corridor modeled with field data obtained for University Avenue in Waterloo, Ontario, Canada. The performance of the fully trained model is then compared with the existing signal plans in relation to the average delay and average queue length. Application of the ring-and-barrier design to this corridor was found to reduce delays by at least 5% and average queue lengths at intersections by 27%.
      Citation: Transportation Research Record
      PubDate: 2020-12-30T04:03:21Z
      DOI: 10.1177/0361198120980321
       
  • User Activity and Trip Recognition using Spatial Positioning System Data
           by Integrating the Geohash and GIS Approaches
    • Authors: Hafez Irshaid, Md Mehedi Hasan, Raed Hasan, Jun-Seok Oh
      Abstract: Transportation Research Record, Ahead of Print.
      Analyzing travel behavior in transportation networks within a city is significant to understand the user’s activity and travel pattern in relation to making improved city plans for the future. Unlike the traditional travel diary survey, GPS data have helped researchers to analyze Big Data with enriched travel information in an automated way. The focus of this research was to identify user activity and travel pattern from GPS data logs. We proposed three different approaches, including Geohash clustering, the GIS-based approach, and Combined Geohash–GIS approach, for automatic user activity and trip recognition in a continuous and aggregate manner. We developed different individual models considering different dwell times for the above three approaches. We considered three different testing scenarios based on specified tolerance levels, including simple, moderate, and critical testing to identify trip only, activity only, and sequential activity–trip analysis. In comparison with other approaches, the Combined Geohash–GIS approach considering 5 min dwell time accurately classified data with about 95% accuracy. The proposed Combined Geohash–GIS approach could significantly enhance the efficiency and accuracy of GPS travel surveys by correctly recognizing user activity and trip patterns. This proposed combined approach could serve as a foundation for a future model system of full-scale travel information identification with GPS data.
      Citation: Transportation Research Record
      PubDate: 2020-12-23T06:07:21Z
      DOI: 10.1177/0361198120980437
       
  • Multiscale and Multivariate Transportation System Visualization for
           Shopping District Traffic and Regional Traffic
    • Authors: Anne S Berres, Tim J LaClair, Chieh (Ross) Wang, Haowen Xu, Srinath Ravulaparthy, Austin Todd, Sarah A Tennille, Jibonananda Sanyal
      Abstract: Transportation Research Record, Ahead of Print.
      In this paper, we present a suite of visualization techniques for sensor-based transportation system data at different scales to facilitate the exploration of interconnected traffic dynamics at intersections and highways. These techniques are designed for analyzing multivariate traffic data from radar-based highway sensors and camera-based intersection sensors recording turn movements and vehicle speed, in the Chattanooga Metropolitan Area, with the capability of (a) revealing multiscale mobility patterns using different levels of data aggregation (e.g., individual sensor for microscale, multiple sensors along a corridor for mesoscale, and a larger number of sensors across the region for macroscale visualization) at different intervals (e.g., 5-min intervals, time of day, full day, and day-of-the-week), and (b) exploring the spatial variation of multiple traffic-related variables (e.g., volumes, speeds, turn movements, and traffic light colors) provided by the sensors. We close with a case study to demonstrate the effectiveness of our multiscale and multivariate visualization techniques. At microscale, we focused on intersection data from a shopping district around Shallowford Road in East Chattanooga. For mesoscale visualization, we studied the Shallowford Road corridor and an adjacent stretch of I-75. At macroscale, we included highway data from the Chattanooga Metropolitan Area. All visualizations were integrated into a web-based situational awareness tool to promote user access and interaction. At a minimum, each visualization provides the option for selecting dates for real-time (depending on sensor availability) and historical data, and additional information on hovering, though most provide more detailed information, including different views of the selected data, or interactive highlights.
      Citation: Transportation Research Record
      PubDate: 2020-12-21T07:33:13Z
      DOI: 10.1177/0361198120970526
       
  • Assessing Drivers’ Compliance with Restrictive Yellow Traffic Lights
           in a Developing Country
    • Authors: Abdoul-Ahad Choupani
      Abstract: Transportation Research Record, Ahead of Print.
      Driving rules adopt permissive or restrictive policies concerning yellow light running (YLR). In a restrictive policy, vehicles behind the stop line are not allowed to enter the intersection on yellow no matter how close they are to the stop line. YLR policy affects driving risks, safety, and operation. There is limited knowledge about the restrictive policy and drivers’ compliance with this rule. Previous studies on YLR are limited in scope since they tended to use binary stop/go decision models without considering red light running decisions. This potentially results in the loss of information about drivers’ conformity to red signals. This paper examines whether drivers are only non-compliant with yellow lights or whether non-conformity to any prohibitive yellow/red signal emerges as a wider behavioral issue. This study develops regression choice models to predict drivers’ illegal yellow-light passing decisions in a developing country with a poor safety record and explores reasons for drivers’ non-compliance. The results obtained show that the restrictive policy is ineffective in relation to driver compliance, especially in cases where drivers’ non-conformity to any restrictive rule emerges as a behavioral issue of concern. Drivers make their stop/go decisions according to the time needed to cross the intersection, and they consider the yellow light as an opportunity for crossing. Yellow (red) light running rates were 101 (31) per 1,000 vehicles per hour (vph) for the restrictive policy, whereas these rates for the U.S.A., with a permissive policy, were at most 29 (6) per 1,000 vph.
      Citation: Transportation Research Record
      PubDate: 2020-12-21T07:31:16Z
      DOI: 10.1177/0361198120973659
       
  • Urban Impacts of Mobile Fuel Delivery Service
    • Authors: Andrea Broaddus
      Abstract: Transportation Research Record, Ahead of Print.
      Mobile fuel delivery (MFD) uses a fueling truck to fill up personal and commercial fleet vehicles while they are parked overnight. This study used a sample data set provided by a San Francisco Bay Area company to explore the potential impacts on vehicle miles traveled (VMT), carbon dioxide (CO2) emissions, and traffic congestion. An analysis of vehicle travel associated with gas station trips was conducted to establish a basis for comparison. Future scenarios comparing the potential impacts of scaled-up MFD services in 2030 were also developed. The study concluded that MFD services compared favorably to gas stations in relation to environmental and traffic benefits in the longer term, even though personal fueling trips tended to generate low VMT. Benefits stemmed from efficiencies achieved by fueling multiple vehicles per delivery trip, replacing car share vehicle fueling trips, and removing trips from the network during peak hours. This analysis estimated that total annual CO2 emissions associated with fuel delivery operations in the Bay Area were 76 metric tons, which is less than a typical gas station with 97 metric tons. Under assumptions of declining demand for gasoline and significantly fewer gas stations, and with highly efficient optimized operations, mobile delivery could gain up to 5% market share for gas and not add additional VMT over the business as usual scenario.
      Citation: Transportation Research Record
      PubDate: 2020-12-21T07:31:07Z
      DOI: 10.1177/0361198120975413
       
  • Evaluation of the Response Analysis Approach Used in the
           Mechanistic-Empirical Pavement Design Guide
    • Authors: Guozhi Fu, Yanqing Zhao, Wanqiu Liu, Changjun Zhou
      Abstract: Transportation Research Record, Ahead of Print.
      Asphalt concrete (AC) is a typical viscoelastic material exhibiting rate-dependent behavior. The rate-dependency of AC should be properly taken into consideration in pavement response analysis to accurately evaluate pavement performance and life. In the Mechanistic-Empirical Pavement Design Guide (MEPDG), the dynamic modulus master curve is used to account for the rate-dependency of the dynamic modulus of AC. However, the rate-dependent phase angle is ignored and a constant phase angle of 0 is assumed. The partial characterization of rate-dependent properties of AC in the MEPDG may lead to inaccurate results. This study compares the pavement responses computed using the MEPDG approach and the layered viscoelastic theory (LVET) which utilizes the complex modulus master curve to fully characterize the rate-dependent properties of AC. Typical three-layer pavement structures were analyzed at three temperatures (−10°C, 20°C and 50°C) and four speeds (10, 40, 80 and 120 km/h). The results show that the horizontal tensile stresses at the bottom of cement-treated base layer obtained from the two approaches are almost the same, and for other responses analyzed, the results obtained from the MEPDG approach are larger than those from the LVET approach, especially for the responses in the AC layer. The normalized difference of the vertical compressive strain at the mid-depth of the AC layer between the two approaches can be up to 100% and that for the horizontal tensile strain at the bottom of the AC layer can be more than 50%.
      Citation: Transportation Research Record
      PubDate: 2020-12-21T07:31:04Z
      DOI: 10.1177/0361198120974010
       
  • Support Vector Machine for Short-Term Traffic Flow Prediction and
           Improvement of Its Model Training using Nearest Neighbor Approach
    • Authors: Trinh Dinh Toan, Viet-Hung Truong
      Abstract: Transportation Research Record, Ahead of Print.
      Short-term prediction of traffic flow is essential for the deployment of intelligent transportation systems. In this paper we present an efficient method for short-term traffic flow prediction using a Support Vector Machine (SVM) in comparison with baseline methods, including the historical average, the Current Time Based, and the Double Exponential Smoothing predictors. To demonstrate the efficiency and accuracy of the SVM method, we used one-month time-series traffic flow data on a segment of the Pan Island Expressway in Singapore for training and testing the model. The results show that the SVM method significantly outperforms the baseline methods for most prediction intervals, and under various traffic conditions, for the rolling horizon of 30 min. In investigating the effect of the input-data dimension on prediction accuracy, we found that the rolling horizon has a clear effect on the SVM’s prediction accuracy: for the rolling horizon of 30–60 min, the longer the rolling horizon, the more accurate the SVM prediction is. To look for a solution for improvement of the SVM’s training performance, we investigate the application of k-Nearest Neighbor method for SVM training using both actual data and simulated incident data. The results show that the k- Nearest Neighbor method facilitates a substantial reduction of SVM training size to accelerate the training without compromising predictive performance.
      Citation: Transportation Research Record
      PubDate: 2020-12-21T07:30:43Z
      DOI: 10.1177/0361198120980432
       
  • Explanatory Analysis of the Safety of Short Passing Zones on Two-Lane
           Rural Highways
    • Authors: Arastoo Karimi, Amin Mirza Boroujerdian
      Abstract: Transportation Research Record, Ahead of Print.
      Passing zones afford sufficient passing distance for passing vehicles on two-lane rural highways. This study aimed to assess the effects of geometric and traffic variables on the safety of short passing zones using the rate of passing maneuvers ending in the no-passing zone as a surrogate safety measure. A Poisson regression model was applied to aerial data collected by drone at seven passing zones. The findings showed that increase in the length of the passing zone corresponds to decrease in the rate of passing maneuvers ending in the no-passing zone. The passing rate is also affected by the lane width, the percentage of heavy vehicles in the subject direction, and the directional split in the subject direction. The rate of passing maneuvers ending in no-passing zones reaches a peak as the two-way traffic flow rate increases to 600 vehicles per hour regardless of the directional split, or as the absolute vertical grade increases to 4.8%–6% depending on the percentage of heavy vehicles. After the peak value, the rate decreases. The presented model can serve as a tool for evaluating and improving the safety of short passing zones.
      Citation: Transportation Research Record
      PubDate: 2020-12-21T07:30:19Z
      DOI: 10.1177/0361198120980436
       
  • Impact of Built Environment on Mode Choice to Major Destinations in Dhaka
    • Authors: Paromita Nakshi, Anindya Kishore Debnath
      Abstract: Transportation Research Record, Ahead of Print.
      In recent years, there has been a growing interest in investigating the impacts of built environment on mode choice decisions. There is a consensus that built environment factors influence travel behavior, although this influence is far from being homogenous. Compared with the North American and some European countries, there has been comparatively limited research in this field in the context of the Global South, especially South Asia. In this context, this paper aims to explore the extent to which built environment influences mode choice behavior to major destinations in Dhaka, the capital of Bangladesh. “Major destinations” refers to the statistically significant trip-attracting clusters in the city. Dhaka is a city with heterogeneous motorized and non-motorized modes. Investigating mode choice decisions, in such a setting, is vital for the planners and policymakers to realize the goals of sustainable development with measured insights. A multinomial logit model was used to estimate the effects of built environment factors on mode choice to work and non-work trips in Dhaka. The study results showed that inclusion of built environment variables had significantly improved the models. Several built environment variables, including dissimilarity index, distance to the nearest bus stop, road density, and so forth, were found to be strong predictors of mode choice, and their elasticities were higher than the elasticities of several personal and household characteristics. Down that line, the findings provided support in favor of considering land use policies intended to increase accessibility, mixed land use, density, and so forth.
      Citation: Transportation Research Record
      PubDate: 2020-12-15T12:21:01Z
      DOI: 10.1177/0361198120978418
       
  • Development of Maximum Weaving Length Model Based on HCM 2016
    • Authors: Ali Kashani, Behrooz Shirgir
      Abstract: Transportation Research Record, Ahead of Print.
      Weaving segments are among the most important segments in any kind of facility. One of their key features is their maximum length (Lwmax), which determines the performance of the facility as a weaving or separate merge and diverge segments. Based on an equation in the Highway Capacity Manual (HCM 2016), only two variables VR (volume ratio) and Nwl (number of weaving lanes) influence this length. However, certain cases can be found in which traffic conditions are different but Nwl and VR values are equal. In this study, three separate weaving segments in Tehran, Iran were used and their data were collected to further analyze the influence of the traffic parameters. Calibration of field data was performed using GEH values of freeways and ramps for simulation and field traffic volumes. The simulation was therefore used on the basis of different traffic and geometric parameters, and the effects of these parameters on Lwmax were carefully observed. There were 184 simulated scenarios in Aimsun using data collected from the three weaving segments in Tehran plus simulation. In these scenarios, two geometric parameters (Nwl and Lwmax) and four traffic parameters were considered variable. It was found that for Nwl = 2 the accepted regression model containing three new variables has an R2 value equal to 0.95, and for Nwl = 3 two of the three variables were used for the model produced with an R2 value equal to 0.7.
      Citation: Transportation Research Record
      PubDate: 2020-12-14T10:23:11Z
      DOI: 10.1177/0361198120973667
       
  • Railway Fastener Defects Detection under Various Illumination Conditions
           using Fuzzy C-Means Part Model
    • Authors: Biao He, Jianqiao Luo, Yang Ou, Ying Xiong, Bailin Li
      Abstract: Transportation Research Record, Ahead of Print.
      To ensure the safe operation of railways, computer vision and pattern recognition technology have been gradually applied to the routine inspection of railway track infrastructure. Rails are fixed to sleepers by railway fasteners, which are important components in railway track systems, and completely missing and partially worn railway fasteners may cause major accidents and train derailments. Because the acquisition of track images is carried out in the real world at any time of the day, the acquired track images have large illumination changes, and the fasteners in the images have slight deformations. To solve these problems, a fuzzy c-means part model (FCMPM) is proposed in this paper. The fastener part model is divided according to the fastener shape and solved by the fuzzy c-means clustering algorithm using the simplified and improved histogram of oriented gradients as the low-level feature. The part score is calculated based on the part’s deformation and then is seamlessly incorporated with cascade detection to determine whether the fastener has defects or not. The experimental results from the fastener defect detection show that the proposed FCMPM algorithm achieves good performance when analysing the collected fastener images and can meet the requirements of fastener defect detection for actual railway lines.
      Citation: Transportation Research Record
      PubDate: 2020-12-14T10:12:42Z
      DOI: 10.1177/0361198120977182
       
  • Identifying Human Mobility Patterns in the Rio de Janeiro Metropolitan
           Area using Call Detail Records
    • Authors: Matheus H. C. Barboza, Ricardo de S. Alencar, Julio C. Chaves, Moacyr A. H. B. Silva, Romulo D. Orrico, Alexandre G. Evsukoff
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents the utilization of mobile phone data for transport models, with spatial modeling of the study region in geographical units that allows the integration of aggregated call detail records (CDR) with demographic data and other sources. The algorithm used for the estimation of the origin–destination matrices obtained a distribution of the number of trips compatible with those of a household survey conducted in 2013. With the use of a one-year dataset, two mobility patterns were identified in Rio de Janeiro: home–work and weekend trips. Changes in mobility patterns because of an important road modification were also detected, demonstrating that the use of CDR for urban planning and monitoring is a robust and low-cost option.
      Citation: Transportation Research Record
      PubDate: 2020-12-14T10:12:00Z
      DOI: 10.1177/0361198120977655
       
  • Smart Method for Self-Organization in Last-Mile Parcel Delivery
    • Authors: J.H.R. v