Subjects -> TRANSPORTATION (Total: 214 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (26 journals)
    - RAILROADS (10 journals)
    - ROADS AND TRAFFIC (9 journals)
    - SHIPS AND SHIPPING (43 journals)
    - TRANSPORTATION (117 journals)

TRANSPORTATION (117 journals)                     

Showing 1 - 53 of 53 Journals sorted by number of followers
Journal of Navigation     Hybrid Journal   (Followers: 203)
Accident Analysis & Prevention     Hybrid Journal   (Followers: 111)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 38)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 38)
Urban, Planning and Transport Research     Open Access   (Followers: 33)
Transportation     Hybrid Journal   (Followers: 32)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 29)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 29)
Journal of Transport and Land Use     Open Access   (Followers: 28)
Transportation Science     Full-text available via subscription   (Followers: 26)
Journal of Transport Geography     Hybrid Journal   (Followers: 22)
European Transport Research Review     Open Access   (Followers: 22)
Public Transport     Hybrid Journal   (Followers: 18)
Nonlinear Dynamics     Hybrid Journal   (Followers: 18)
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 18)
Cities in the 21st Century     Open Access   (Followers: 17)
Economics of Transportation     Partially Free   (Followers: 16)
Open Journal of Safety Science and Technology     Open Access   (Followers: 16)
Transportation Journal     Full-text available via subscription   (Followers: 16)
Transport     Open Access   (Followers: 16)
Journal of Transportation Technologies     Open Access   (Followers: 13)
IET Electrical Systems in Transportation     Open Access   (Followers: 13)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 13)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 13)
Journal of Supply Chain Management Science (JSCMS)     Open Access   (Followers: 13)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 12)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 12)
Journal of Transport & Health     Hybrid Journal   (Followers: 12)
European Journal of Transport and Infrastructure Research (EJTIR)     Open Access   (Followers: 12)
Journal of Transport History     Hybrid Journal   (Followers: 12)
EURO Journal of Transportation and Logistics     Open Access   (Followers: 12)
Sport, Education and Society     Hybrid Journal   (Followers: 12)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 11)
IET Intelligent Transport Systems     Open Access   (Followers: 11)
Modern Transportation     Open Access   (Followers: 11)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 11)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 11)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 10)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 10)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 9)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 9)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 9)
International Journal of Transportation Science and Technology     Open Access   (Followers: 9)
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 8)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 8)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 8)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 7)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 7)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 7)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 7)
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
Mobility in History     Full-text available via subscription   (Followers: 7)
Transportation Research Procedia     Open Access   (Followers: 6)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Applied Mobilities     Hybrid Journal   (Followers: 5)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 5)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 5)
Logistics & Sustainable Transport     Open Access   (Followers: 4)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 4)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 4)
Transport and Telecommunication     Open Access   (Followers: 4)
Vehicular Communications     Full-text available via subscription   (Followers: 4)
IEEE Open Journal of Intelligent Transportation Systems     Open Access   (Followers: 4)
Research in Transportation Business and Management     Partially Free   (Followers: 4)
Transport Problems     Open Access   (Followers: 4)
Transactions on Transport Sciences     Open Access   (Followers: 4)
World Electric Vehicle Journal     Open Access   (Followers: 3)
Journal of Transportation and Logistics     Open Access   (Followers: 3)
Journal of Public Transportation     Open Access   (Followers: 3)
TRANSPORTES     Open Access   (Followers: 3)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 2)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 2)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 2)
Journal of Big Data Analytics in Transportation     Hybrid Journal   (Followers: 2)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
International Journal of Transportation Engineering     Open Access   (Followers: 2)
Transportation Research Interdisciplinary Perspectives     Open Access   (Followers: 2)
Journal of Intelligent and Connected Vehicles     Open Access   (Followers: 1)
Open Transportation Journal     Open Access   (Followers: 1)
eTransportation     Open Access   (Followers: 1)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Transportation Safety and Environment     Open Access   (Followers: 1)
Danish Journal of Transportation Research / Dansk Tidsskrift for Transportforskning     Open Access   (Followers: 1)
Asian Transport Studies     Open Access   (Followers: 1)
Transportation Engineering     Open Access   (Followers: 1)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 1)
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 1)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
International Journal of Services Technology and Management     Hybrid Journal   (Followers: 1)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 1)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Emission Control Science and Technology     Hybrid Journal   (Followers: 1)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Maritime Transport Research     Open Access  
Communications in Transportation Research     Open Access  
IET Smart Cities     Open Access  
Journal on Vehicle Routing Algorithms     Hybrid Journal  
Transportation in Developing Economies     Hybrid Journal  
Vehicles     Open Access  
Periodica Polytechnica Transportation Engineering     Open Access  
Transportation Systems and Technology     Open Access  
LOGI ? Scientific Journal on Transport and Logistics     Open Access  
Promet : Traffic &Transportation     Open Access  
IFAC-PapersOnLine     Open Access  
Revista Transporte y Territorio     Open Access  
Транспортні системи та технології перевезень     Open Access  
Geosystem Engineering     Hybrid Journal  
Logistique & Management     Hybrid Journal  
IATSS Research     Open Access  
Transport in Porous Media     Hybrid Journal  

           

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: 29  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 0361-1981 - ISSN (Online) 2169-4052
Published by Sage Publications Homepage  [1174 journals]
  • Accelerating Mixture Design for Cement Treated Base Material

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      Authors: Stephen Sebesta, Jinho Kim, Younho Rew, Ross Taylor, Peter Townsend
      Abstract: Transportation Research Record, Ahead of Print.
      The stabilization of roadway and stockpile materials enhances the strength and stiffness properties of pavement base layers, allowing those layers to meet structural requirements in a cost-effective and sustainable manner. Historically, mixture stabilization design criteria have relied on unconfined compressive strength (UCS) results and, depending on the treatment type and test methods, they can take nearly a month to complete. Additionally, different treatment types currently require different preparation, curing time, and acceptance criteria. This research develops a harmonized and accelerated design procedure for cement-treated base materials with the objective of producing acceptable mixture design recommendations. This work focuses on a rapid test turnaround time, the inclusion of moisture conditioning in the mix design, and performance-related design criteria by relating an accelerated-cure indirect tensile test (IDT) to UCS and modulus of rupture (MoR). The resulting strength relationship model for the MoR, UCS, and IDT was found to show promise for estimating UCS based on an accelerated-cure IDT, and potentially estimating MoR from that same IDT. The newly formulated IDT test method illustrates the possibility of accelerating the mixture design procedure for cement-treated bases and harmonizing with mix design procedures used for emulsion and foamed asphalt-treated base materials.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:32:10Z
      DOI: 10.1177/03611981221115077
       
  • Enabling Rapid Large-Scale Seismic Bridge Vulnerability Assessment Through
           Artificial Intelligence

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      Authors: Xin Zhang, Corey Beck, Ali Lenjani, Leslie Bonthron, Alana Lund, Xiaoyu Liu, Shirley J. Dyke, Julio Ramirez, Prince Baah, Jeremy Hunter
      Abstract: Transportation Research Record, Ahead of Print.
      Departments of transportation (DOTs) throughout the United States maintain vast bridge databases that house information such as bridge services, dimensions, materials, inspection reports, and photographs. These databases are expensive to maintain and have evolved quite gradually over the years. They are meant to be substantial enough, at a bare minimum, to support typical asset management activities and to prioritize maintenance tasks. There is great potential to make use of them to support other decisions. However, these databases often lack certain detailed information related to substructure elements, which is necessary for seismic vulnerability assessment, for example, and would be time-consuming to gather for thousands of bridges in a given region or state. In this study, a technique was demonstrated and validated that reduces the time needed to collect this information, by leveraging artificial intelligence to automate the identification of substructure types using images. We defined categories appropriate for vulnerability assessment task, classifiers were trained to identify visual content, and their performance evaluated. In this paper we illustrate a method to determine whether to use artificial intelligence, human visual confirmation, or a combination of the two, to identify bridge substructure types based on accuracy, cost, and risk tolerance. The technical approach was validated using images from Indiana. This leveraging of artificial intelligence for automated identification of critical bridge characteristics from readily available images could empower asset owners, such as DOTs, to assess their inventory more frequently and with confidence.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:30:29Z
      DOI: 10.1177/03611981221112950
       
  • Short-Term Passenger Flow Prediction Using a Bus Network Graph
           Convolutional Long Short-Term Memory Neural Network Model

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      Authors: Asiye Baghbani, Nizar Bouguila, Zachary Patterson
      Abstract: Transportation Research Record, Ahead of Print.
      Short-term passenger flow prediction is critical to managing real-time bus networks, responding to emergencies quickly, making crowdedness-aware route recommendations, and adjusting service schedules over time. Some recent studies have attempted to predict passenger flow using deep learning models. The complexity of transportation networks, coupled with emerging real-time data collection and information dissemination systems, has increased the popularity of these approaches. There has also been a growing interest in using a new deep learning approach, the graph neural network that captures graph dependence by passing messages between its nodes. Researchers in various transportation domains have used such tools for modeling and predicting transportation networks, as many of these networks consist of nodes and links and can be naturally categorized as graphs. This paper develops a bus network graph convolutional long short-term memory (BNG-ConvLSTM) neural network model to forecast short-term passenger flows in bus networks. Validating the proposed model is done using real-world data collected from the Laval bus network in Canada. Based on a set of comparisons between the proposed model and some other popular deep learning approaches, it clearly indicates that the BNG-ConvLSTM model is more scalable and robust than other baselines in making network-wide predictions for short-term passenger flows.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:27:29Z
      DOI: 10.1177/03611981221112673
       
  • Investigating the Safety Impact of Segment- and Intersection-Level Bicycle
           Treatments on Bicycle–Motorized Vehicle Crashes

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      Authors: Aikaterini Deliali, Nicholas Fournier, Eleni Christofa, Michael Knodler
      Abstract: Transportation Research Record, Ahead of Print.
      Bicycle treatments are installed to elevate motorists’ awareness of the presence of bicyclists and to enhance bicycle safety and mobility. To date, no studies have compared the safety benefits of sharrows and protected- and conventional bike lanes, or intersection-level treatments like bike boxes and intersection-crossing pavement markings. One factor that limits bicycle safety research is the lack of adequate bicycle exposure data. For this study, a crowdsource app was used for estimating networkwide bicycle demand data for Portland, OR. Crash prediction models were developed for road segments and signalized intersections to associate bicycle treatment presence and type with crash frequency. Compared with the “no treatment” case, protected bike lanes (odds ratio [OR] = 0.032), sharrows (OR = 0.211), and conventional bike lanes (OR = 0.552) were safer for road segments. Signalized intersections where segment-level bicycle treatments exist at more than one of the intersecting roads were associated with higher crash frequency. Specifically, for signalized intersections with one conventional bike lane, with two conventional bike lanes, or with a conventional- and a protected bike lane, the respective CMFs were 1.94, 2.07, and 3.38. Signalized intersections with at least one bike box or intersection-crossing pavement markings experienced higher crash frequency than intersections with no treatments, however not necessarily in the approach where the treatment was located. The respective Crash Modification Factors (CMFs) were 1.39 and 1.76. The findings could guide practitioners in selecting bicycle treatments for segments, whereas the models for signalized intersections could identify intersections with high crash frequency that need safety improvements.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:25:26Z
      DOI: 10.1177/03611981221112670
       
  • A New Method for the Quality of Service Assessment of Highly Frequented
           Bicycle Facilities in Germany

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      Authors: Alexander Brandenburg, Justin Geistefeldt, Verena Zeidler, Sebastian Buck, Peter Vortisch, Michael M. Baier
      Abstract: Transportation Research Record, Ahead of Print.
      Owing to increasing bicycle traffic volumes in Germany, more and more bicycle facilities are being designed with widths beyond the standard values given in the existing design guidelines. However, the level of service assessment method for bicycle facilities in the current edition of the German Highway Capacity Manual, HBS, is based on empirical data from facilities with mostly low traffic demand and small widths. Therefore, a new quality of service assessment method for highly frequented bicycle facilities was developed. For this, the cycling behavior of cyclists at high traffic volumes was analyzed, considering different bicycle types. Bicycle traffic flow quality, which is mainly characterized by the ability for cyclists to pass, was examined on segments of bicycle facilities with different geometric parameters, including facility type, gradient, and width. The speed and lateral distance behavior of cyclists were analyzed by using radar and video measurements. It was found that a large variance in the bicycle speed distribution mainly resulted from an inhomogeneous composition of bicycle types. The bicycle facilities were modeled with the microscopic traffic simulation tool PTV Vissim and calibrated using the empirical data. The models were used to analyze the impact of different geometric parameters and high proportions of specific bicycle types. As expected, the simulations revealed that the quality of service was mainly influenced by the lane width. Based on the results, a method to assess the quality of service of bicycle facilities, in which traffic density is used as the measure of effectiveness, was developed.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:20:25Z
      DOI: 10.1177/03611981221112669
       
  • Distribution of Highway Infrastructure Cost Responsibility and Revenue
           Contribution Shares Among Highway Users in North Carolina: Present
           Conditions and Future Alternatives

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      Authors: Md Mehedi Hasnat, Eleni Bardaka
      Abstract: Transportation Research Record, Ahead of Print.
      As the proportion of fuel-efficient and electric vehicles is rapidly increasing, US states are challenged to meet the greater needs of the aging transportation infrastructure with less funds. The purpose of this study is to support state authorities in understanding the equity implications, feasibility, and effectiveness of many of the currently available transportation funding mechanisms. To fulfill this objective, the study analyzes data from North Carolina (NC) between 2014 and 2017. As a first step, we estimate and compare the transportation infrastructure cost responsibility and revenue contribution of NC highway users. Results indicate that lightweight vehicles contribute substantially more to the revenue compared with their share of cost responsibilities. Single-unit trucks with four or more axles and multi-unit trucks are found to underpay their cost responsibilities by 37% to 92%. We use these results in combination with previous research to assess different scenarios for funding transportation infrastructure in the future. Each alternative is evaluated for its revenue generation potential, equity-related improvements, applicability, and public acceptance. Findings suggest that a moderate increase in traditional taxes such as motor fuels tax, vehicle sales tax, or the state sales tax are practical and reasonable approaches for generating significant additional revenue in the short run without strong opposition from the public. However, all the scenarios analyzed by this study, which are based on tax and fee structures planned or implemented in the USA, are found to have minor impacts in improving equity between the cost responsibility and revenue contribution across vehicle classes.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:17:02Z
      DOI: 10.1177/03611981221112403
       
  • Simulation of Urban Crash Occurrence Based on Real-World Crash Data

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      Authors: Marcel Langer, Ronald Kates, Klaus Bogenberger
      Abstract: Transportation Research Record, Ahead of Print.
      The intelligent application of simulation is of central importance for the successful development and testing of automated driving functions. Realistic virtual environments are required to assess and optimize both the efficiency and safety of automated driving functions in real-world traffic situations. While existing traffic flow simulation frameworks excel at evaluating traffic efficiency, the implementation of human failure models and traffic safety aspects is a current field of research. In this publication, the occurrence of human failures is inferred from real-world crash statistics and introduced into traffic simulation. A realistic traffic simulation setup of the city of Ingolstadt, Germany, is used as a basis for this simulation of crash occurrence. Focusing on intersections as the most important urban crash hot spots, the relation between human failures and the occurrence of collisions is estimated for each conflict point in the simulation network. From crash statistics, the distributions of crash quantities and types across the intersections in the simulation network are calculated. An Iterative Proportional Fitting algorithm is used to project crash counts available at the intersection level onto the “conflict level,” determined by intersecting traffic streams within intersections. Human failures are generated and applied to traffic participants in the simulation using a Monte Carlo selection. The results demonstrate the functionality of the method for calibrating models for realistic crash occurrence in traffic simulation. This methodology provides a basis for simultaneous evaluation of both traffic efficiency and traffic safety impacts of future developments in urban traffic networks.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:14:02Z
      DOI: 10.1177/03611981221112400
       
  • Understanding Airline Passengers during Covid-19 Outbreak to Improve
           Service Quality: Topic Modeling Approach to Complaints with Latent
           Dirichlet Allocation Algorithm

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      Authors: Levent Çallı, Fatih Çallı
      Abstract: Transportation Research Record, Ahead of Print.
      The COVID-19 pandemic has deeply affected the airline industry, as it has many sectors, and has created tremendous financial pressure on companies. Flight bans, new regulations, and restrictions increase consumer complaints and are emerging as a big problem for airline companies. Understanding the main reasons triggering complaints and eliminating service failures in the airline industry will be a vital strategic priority for businesses, while reviewing the dimensions of service quality during the COVID-19 pandemic provides an excellent opportunity for academic literature. In this study, 10,594 complaints against two major airlines that offer full-service and low-cost options were analyzed with the Latent Dirichlet Allocation algorithm to categorize them by essential topics. Results provide valuable information for both. Furthermore, this study fills the gap in the existing literature by proposing a decision support system to identify significant service failures through passenger complaints in the airline industry utilizing e-complaints during an unusual situation such as the COVID-19 pandemic.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:07:18Z
      DOI: 10.1177/03611981221112096
       
  • On-Site Experiment and Characteristics Analysis of Ground Vibrations
           Induced by Vehicle Loads Moving on an Urban Trunk Road

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      Authors: Yanmei Cao, Zhe Li, Chao Yang
      Abstract: Transportation Research Record, Ahead of Print.
      In urban areas, the ground vibrations induced by vehicle loads are becoming an increasingly serious environmental issue, especially in the planning and design of high-tech workshops. In this paper, traffic flow and ground vibrations are simultaneously measured from the vehicles moving on a trunk road in Beijing from 9:30 a.m. to 9:30 p.m. The correlation between traffic volume and ground vibration is calculated to analyze the contribution of different vehicle types and density. The characteristics of ground vibration are revealed by analyzing the experimental data from the testing points of time history and frequency variety. Moreover, the attenuation law of ground vibration is summarized and well fitted by the Bornitz model. Finally, according to existing assessment standards, the vibration levels are effectively assessed. The results indicate that the concentration of multi-peak ground vibrations in a short time period can be attributed to the combination of vibration waves induced by vehicles close to each other. Two vibration peaks were observed in the frequency range of 10 Hz to 12.5 Hz and 2.5 to 4 Hz, close to the resonant frequencies of vehicle parts. The environmental vibrations induced by road traffic may exceed the allowable values stipulated in the relevant standards, and undoubtedly influence the normal operation of precise instruments, even at a distance beyond 100 m from the source.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:04:58Z
      DOI: 10.1177/03611981221112092
       
  • Method for Estimating the Monetary Benefit of Improving Annual Average
           Daily Traffic Accuracy in the Context of Road Safety Network Screening

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      Authors: Mohammad Zarei, Bruce Hellinga
      Abstract: Transportation Research Record, Ahead of Print.
      Conventional road safety network screening (NS) relies on measures of historical crash data and annual average daily traffic (AADT) as a measure of exposure to develop safety performance functions. AADT is typically estimated from short-term counts and contains error which can negatively affect NS outcomes and result in the inefficient allocation of safety improvement resources. In this paper, we propose a simulation-based method for quantifying the monetary benefit of improving AADT accuracy. The results of applying the method under various conditions show that crash data sets with higher sample mean and dispersion parameter values are more sensitive to AADT error and consequently benefit more from improving AADT accuracy. The use of the proposed method is illustrated through the application to a real-world example.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:03:18Z
      DOI: 10.1177/03611981221115720
       
  • Privacy-Preserving Adaptive Trajectory Storage on Blockchain for COVID-19
           Contact Tracing

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      Authors: Junaid Ahmed Khan, Kavya Bangalore, Kaan Ozbay
      Abstract: Transportation Research Record, Ahead of Print.
      Privacy preservation in various contact tracing approaches for the COVID-19 or SARS-CoV-2 virus is challenging, as such applications tend to reveal users’ points of interest (POIs) and other sensitive data shared together with their location information. This paper proposes COVID-19 eavesdropping resistant tracing (COVERT)-Blockchain, a novel distributed-ledger-based platform to facilitate contact tracing without invading users’ privacy. COVERT-Blockchain enables infected users to share only their anonymized location traces on the Blockchain with a sliding window of the previous 15 days, thereby avoiding constant location information sharing with third party users. To further reduce the chances of revealing the corresponding users’ trajectories, in COVERT-Blockchain we employ an adaptive logging mechanism to store trajectory data for contact tracing only if the users stayed in a location where there is significant presence of other humans around them for a relatively long duration of time. This ensures anonymity where the trajectory is generated differently each time for each user, and such infrequent and random trajectory generation enables us to generate unidentifiable trajectories for each user and thus preserve their privacy. COVERT-Blockchain is evaluated for scalability and robustness in relation to overhead and delays in storing and retrieving data from the Blockchain. Results show it to efficiently achieve contact tracing without any breaches of privacy.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T06:01:58Z
      DOI: 10.1177/03611981221115430
       
  • Methodology for Conflating Large-Scale Roadway Networks

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      Authors: Xu Zhang, Mei Chen
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation agencies are increasingly integrating third-party traffic data into their core business function areas such as system performance monitoring, project programming, traffic incident management, and safety analysis. However, linking private-sector data with agency asset inventory data has been a major challenge because the networks typically have different referencing systems, segmentation schemes, and representations of travel directions. This paper presents an effective conflation algorithm that associates spatial features between large-scale road networks. Instead of breaking lines into smaller pieces, which is a common technique in transportation applications, we use an intersection-based approach that leverages the inherent topological similarities between networks. The underlying uncertainty and imprecision in network geometries and road names are addressed through application of a fuzzy logic inference technique. We then implement an effective mechanism to handle differences in representations of divided roadways and travel directions in the two networks. The algorithm was tested on Kentucky statewide roadway networks and achieved a matching accuracy of over 99%. This approach has been successfully applied by the Kentucky Transportation Cabinet in its project identification and prioritization process.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T05:57:29Z
      DOI: 10.1177/03611981221115085
       
  • Platooning Trajectory Optimization for Connected Automated Vehicles in
           Coordinated Arterials

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      Authors: Agustin Guerra, Lily Elefteriadou
      Abstract: Transportation Research Record, Ahead of Print.
      This paper proposes heuristic methods to optimize the trajectories of connected automated vehicles (CAVs) along an arterial assuming fully automated traffic condition. CAV trajectories are adjusted to form platoons at the saturation headway, guaranteeing the arrival of vehicles at the downstream intersection during the green interval. On the arrival of CAVs, an algorithm enables a smooth transition to the system target speed. The CAVs’ trajectories are then adjusted by an algorithm according to the vehicles’ positions (leader/follower). Simulation parameters that consider human driving are selected to avoid overestimating the benefits of the proposed strategy. A simulation algorithm is developed to evaluate the performance of the proposed heuristic. The proposed method is compared with a pre-timed coordinated signal control scheme. Seven demand scenarios corresponding to undersaturated conditions are evaluated. The proposed method reduced travel time by 7% to 16% and delay by 23% to 43%. Its computational efficiency makes the proposed method suitable for real-world tests.
      Citation: Transportation Research Record
      PubDate: 2022-08-13T05:48:33Z
      DOI: 10.1177/03611981221112099
       
  • Moving Toward Gender-Equitable Transportation in Post-COVID-19 Urban South
           Asia

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      Authors: Sonal Shah, Rithvika Madhummal Rajiv, Abhijit Lokre
      Abstract: Transportation Research Record, Ahead of Print.
      This research examines the impacts of COVID-19 on the mobility of resource-poor women and its linkage with livelihoods in urban South Asia, and how gender-responsive transport measures could be adopted. The study, conducted in Delhi between October 2020 and May 2021, used a mixed methods, multi-stakeholder, and reflexive approach. A literature review was conducted on the gender and mobility context in Delhi, India. Quantitative data were collected through surveys with resource-poor women, while qualitative research methods consisted of in-depth interviews with them. Different stakeholders were engaged through round tables and key informant interviews before and after data collection to share the findings and recommendations. The sample survey (n = 800) revealed that only 1.8% of working resource-poor women have access to a personal vehicle, making them dependent on public transport. While 81% of their trips are by bus, 57% of their peak hour trips are by paratransit, despite free travel on buses. Only 10% of the sample have access to a smart phone, which restricts their access to digital initiatives based on smart phone applications. The women expressed concerns such as poor bus frequencies and buses not stopping for them under the free ride scheme. These were consistent with issues faced before the COVID-19 pandemic. These findings highlight the need for targeted strategies for resource-poor women to achieve equity in gender-responsive transport. These include a multimodal subsidy, short messaging service to obtain real-time information, increased awareness on filing complaints, and an effective grievance redressal system.
      Citation: Transportation Research Record
      PubDate: 2022-08-11T11:18:57Z
      DOI: 10.1177/03611981221111369
       
  • Study of Measures to Design Asphalt Mixes Including High Percentages of
           Recycled Asphalt Pavement and Recycled Asphalt Shingles

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      Authors: Maziar Mivehchi, Haifang Wen, Yankai Wen, Lin Wang
      Abstract: Transportation Research Record, Ahead of Print.
      With the increased use of recycled materials and various additives, the performance of asphalt mixes, especially their cracking resistance, has become a primary concern. Researchers have developed performance test methods and parameters to simulate field performance in the laboratory. When these performance tests are included in specifications, contractors must adjust their mix design parameters accordingly. To aid contractors, this study evaluated rut depths obtained from Hamburg wheel-tracking tests of 261 asphalt mixes and cracking test (CT) index values from IDEAL-CT tests of 69 mixes designed by contractors and verified by the Washington State Department of Transportation. These mixes had different gradations; binder contents; air void contents; recycled asphalt pavement (RAP); recycled asphalt shingles (RAS); recycling agents; binder performance grades; and other volumetric properties. The results show that (1) rut depth is highly sensitive to binder content, performance grade, aggregate angularity, and RAP/RAS content and (2) the CT index is sensitive to binder content, air void content of the mixture, aggregate gradation, and RAP/RAS content. The low-RAP mixes also showed worse cracking performance than the mixes without RAP. Therefore, the performance grade of blended binder may need to match the target binder grade even for low-RAP mixes. It was found that the design air void of 3.5% is optimal in respect of cracking resistance. The use of softer virgin binder or rejuvenator may not be effective in completely mitigating the cracking potential of high-RAP/RAS mixes.
      Citation: Transportation Research Record
      PubDate: 2022-08-09T06:18:16Z
      DOI: 10.1177/03611981221108982
       
  • Car-Following Characteristics of Commercially Available Adaptive Cruise
           Control Systems and Comparison With Human Drivers

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      Authors: Yingjun Ye, Jie Sun, Jian Sun
      Abstract: Transportation Research Record, Ahead of Print.
      Adaptive cruise control (ACC) system, as one of the most fundamental modules of automated vehicles, is widely used in commercially available vehicles. It inevitably influences the traffic flow, from both the individual perspective, that is, its interaction with other traffic participants, and the traffic system perspective, that is, traffic string stability and road capacity. However, subject to limited data availability, no consistent conclusions on these impacts have been reached in the literature. Meanwhile, the similarities and differences between ACC vehicles and human-driven vehicles (HDV) have not been fully discussed and comparisons among different commercially available ACC systems remain to be untangled. Therefore, to fill this gap, this study investigates the car-following characteristics of various ACC systems and compares them with human drivers based on the open-access OpenACC database. We first identify the proper surrogate car-following model for denoting the driving behaviors of ACC vehicles and HDVs from five widely used car-following models, among which the best-fitted one is the intelligent driver model. Then, we implement the Gaussian mixture model and Jensen-Shannon divergence to describe the similarities between ACC systems and human drivers. Moreover, the string stability of different ACC platoons in various traffic conditions are investigated with a series of simulation experiments. Results show that all the ACC systems are string unstable, and more unstable than human drivers. The behavior of the Ford-ACC system is most similar to human drivers with a relative low instability, while the Peugeot-ACC system behaves most differently to human drivers, and aggressively with the highest instability.
      Citation: Transportation Research Record
      PubDate: 2022-08-08T09:26:23Z
      DOI: 10.1177/03611981221113313
       
  • Safety Assessment of the Interaction Between an Automated Vehicle and a
           Cyclist: A Controlled Field Test

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      Authors: Maria Oskina, Haneen Farah, Peter Morsink, Riender Happee, Bart van Arem
      Abstract: Transportation Research Record, Ahead of Print.
      The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a controlled field experiment consisting of interaction scenarios in which a vehicle approached the cyclist from behind. Four interaction scenarios were included: manual and automated following and manual and automated overtaking of the cyclist. The vehicle operated in all scenarios in a manual mode for safety reasons. However, before each ride, participants received information about the vehicle’s operation mode (automated or manual). The following attributes were considered: overtaking speed, overtaking lateral distance, following distance, and roadside objects. The objective and the subjective risks were evaluated in each scenario. The objective risk was assessed using the probabilistic driving risk field, and the subjective risk was assessed based on the cyclists’ self-reported risk values, cycling behavior, and their trust in AVs. The results show that automated and manual following have similar objective and subjective risks, while automated overtaking has a higher level of objective and subjective risks than manual overtaking. The results also show that a longer interaction time leads to an increase in cycling speed and a decrease in the lateral distance of the cyclist to the curb. Thus, we conclude that automated following is a safer option for short traveling distances, while for longer traveling distances, manual overtaking is preferred. Additionally, a short lateral distance from the cyclist when overtaking increases the subjective and objective risks.
      Citation: Transportation Research Record
      PubDate: 2022-08-08T09:26:20Z
      DOI: 10.1177/03611981221112423
       
  • Evaluating an Eco-Cooperative Automated Control System

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      Authors: Kyoungho Ahn, Jianhe Du, Mohamed Farag, Hesham A. Rakha
      Abstract: Transportation Research Record, Ahead of Print.
      The paper evaluates an Eco-Cooperative Automated Control (Eco-CAC) system on a large-scale network considering a combination of internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), and battery-only electric vehicles (BEVs) in a microscopic traffic simulation environment. We used a novel integrated control system that: (1) routes ICEVs, HEVs, and BEVs in a fuel/energy-efficient manner; (2) selects vehicle speeds based on anticipated traffic network evolution; (3) minimizes vehicle fuel/energy consumption near signalized intersections; and (4) intelligently modulates the longitudinal motion of vehicles along freeways within a cooperative platoon to minimize fuel/energy consumption. The study tested the system using the INTEGRATION software on the Los Angeles (LA), U.S., downtown network for three different demand levels: no congestion, mild congestion, and heavy congestion. The results demonstrated that the Eco-CAC system effectively reduces vehicle fuel and energy consumption, travel time, total delay, and stopped delay in heavily congested conditions. However, different vehicle compositions produced different results. In particular, the maximum energy consumption savings for BEVs (36.9%) for a current vehicle composition occurred at a 10% market penetration rate (MPR) of connected automated vehicles (CAVs) in mild congestion, while the maximum savings for a future vehicle composition (35.5%) occurred at a 50% CAV MPR in no congestion. The system reduced fuel consumption for ICEVs and HEVs by up to 5.4% and 6.3% at a 25% CAV MPR in heavy congestion for current and future vehicle compositions, respectively. However, the system increased total fuel consumption by up to 4.6% at a 50% CAV MPR in no congestion for a current vehicle composition. The study demonstrates that the effectiveness of the Eco-CAC system depends on traffic conditions, including congestion level, network configuration, CAV MPR, and vehicle composition.
      Citation: Transportation Research Record
      PubDate: 2022-08-08T09:26:12Z
      DOI: 10.1177/03611981221113315
       
  • Delays and Queue Lengths at Traffic Signals With Two Greens in One Cycle

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      Authors: Werner Brilon, Ning Wu, Ralph Koenig
      Abstract: Transportation Research Record, Ahead of Print.
      Under specific circumstances signal timing at a traffic signal allows the switching of two green times within one cycle. Practitioners expect a reduction in delays and queue length as a result of this control strategy. However, no analytical methodology is available to quantify this effect. To resolve this deficit, analytical considerations have been undertaken. They follow the principles that are also the basis for conventional signal performance analysis. The basic difference compared with a single green is that, within each cycle, the maximum length of the vehicle queue remains shorter under the two-green regime. This effect is expressed by the term uniform delay, w1. For that parameter, a specific deterministic derivation is proposed. The second element is the incremental delay, w2, which stands for the effects of randomness and temporary oversaturation. The analysis confirmed that this parameter could be adopted from conventional methods. Different formulas for the estimation of w2 were investigated using simulation studies. Thus, a set of equations is given for the prediction of average delay and of percentile queue length in the case of two green times. Verification of the derived formulas was performed using Monte Carlo simulations. The results could easily be applied in practice and might be implemented into guidelines. The application demonstrated how a second green within one signal cycle reduced delays and, notably, queue lengths.
      Citation: Transportation Research Record
      PubDate: 2022-08-06T05:46:08Z
      DOI: 10.1177/03611981221108981
       
  • Charging Infrastructure and Schedule Planning for a Public Transit Network
           with a Mixed Fleet of Electric and Diesel Buses

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      Authors: Amirali Soltanpour, Mehrnaz Ghamami, Mahsa Nicknam, Mehdi Ganji, Wei Tian
      Abstract: Transportation Research Record, Ahead of Print.
      Promoting battery electric buses (BEBs) can reduce fuel consumption and air pollution from the transit system. A complete transition from the current diesel fleet to BEBs is costly and time-consuming. Thus, the intermediate solution is a combination of diesel, hybrid, and BEBs. Therefore, a planning framework is required that simultaneously tackles three contiguous aspects of transit electrification and their interconnections, namely charging infrastructure, fleet configuration, and scheduling. Accordingly, this study considers a mixed fleet of diesel and BEBs. It aims to concurrently find (i) the optimal location and capacity of charging infrastructure, considering micro-grid specifications, the impact of distributed energy resources, and time-of-use electricity rates and (ii) optimum operation and refueling strategies. Another objective of this study is to capture the impacts of adverse weather conditions on transit electrification. A mixed-integer problem is proposed and solved using a metaheuristic algorithm based on simulated annealing to minimize system costs, including infrastructure, fleet, and operation costs. A subnetwork of transit in Worcester, Massachusetts, is selected as a case study, including three routes, five candidate charging locations, and three bus types. Findings suggest that BEBs can operate and serve the passenger demand with sufficient charging infrastructure. Sensitivity analyses show that even though high-power chargers are more expensive per piece, they reduce the overall cost as fewer chargers are required. The cost rises for chargers with power of 350 kW or more. It is worth noting that the benefits of BEBs are more significant in smaller buses and are heavily affected by adverse weather conditions.
      Citation: Transportation Research Record
      PubDate: 2022-08-06T05:40:35Z
      DOI: 10.1177/03611981221112405
       
  • Collapse of the Chirajara Cable-Stayed Bridge in Colombia

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      Authors: Thomas P. Murphy, Nohemy Y. Galindez, Frank A. Artmont, Andrew R. Adams, Maria Lopez de Murphy
      Abstract: Transportation Research Record, Ahead of Print.
      The Chirajara Bridge is part of a highway project located about 40 mi to the southeast of Bogota, Colombia. The collapsed structure was a cable-stayed bridge consisting of two diamond-shaped towers, with a main span length of 940 ft and two side spans of 262 ft. On January 15, 2018, while under construction and with only 164 ft of the floor system remaining to be constructed between the towers, the western tower suddenly collapsed, destroying that part of the bridge. The other tower remained standing, approximately in the same construction stage as the collapsed tower. Modjeski and Masters was engaged one week after the collapse to conduct a forensic investigation that included: an in situ inspection of the collapsed structure, analytical studies, an evaluation of the design, a review of the construction documentation, and testing of materials from critical structural components. Global analyses were performed to determine the loading effects in the bridge before collapse, and refined nonlinear analyses were conducted to estimate the capacity of the tower and to identify the failure mode. The investigation was concluded 4 months after the collapse and, based on the resulting data, the cause of the collapse was determined to be a deficiency in the strength of the tower. The design erroneously assumed that the reinforcing along most of the height of the diaphragm between the lower legs of the tower was effective to resist the horizontal tensile force caused by the tower’s geometry, as opposed to typical practice which utilizes a tension tie at the change in direction of the tower legs.
      Citation: Transportation Research Record
      PubDate: 2022-08-05T05:20:59Z
      DOI: 10.1177/03611981221111351
       
  • Analysis of Temporal Stability of Contributing Factors to Truck-Involved
           Crashes at Work Zones in South Carolina

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      Authors: Fahim Ahmed, Chowdhury K. A. Siddiqui, Nathan Huynh
      Abstract: Transportation Research Record, Ahead of Print.
      This study examines factors that contributed to truck-involved work zone crash injury in South Carolina, a state which experienced a rise in the number of injury crashes from 2014 to 2018. The outcome of interest is injury or property damage only (PDO) crashes. A binary logit model is developed using South Carolina statewide work zone crash data from 2014 to 2018. It considers various factors, including vehicle, crash, roadway, environment, day and time, and driver-related characteristics. Of particular interest to this study is the temporal stability of the contributing factors from year to year so that a long-term mitigating strategy can be developed. To this end, the test for parameter transferability is used, and it confirms that separate models should be used for each year, except for 2014. The only factor found to be temporally stable across all years (i.e., statistically significant in 2015–2018 models) is airbag deployment. Given that nearly all the factors are temporally unstable, an importance measure is introduced to enable transportation agencies to rank factors and develop countermeasures that target persistent contributing factors. Based on the importance measure, the top three ranked factors that contributed to work zone truck-involved crash injury in South Carolina from 2015 to 2018 are: (i) airbags deployed, (ii) tie between rear-end crashes and crashes on primary roadways, and (iii) crashes in dark conditions.
      Citation: Transportation Research Record
      PubDate: 2022-08-03T09:10:06Z
      DOI: 10.1177/03611981221112097
       
  • A Study of Driver Eye-Glancing Behavior at Two Different Types of
           Unsignalized Intersections Based on SHRP2 NDS Data

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      Authors: Beijia Zhang, Huaguo Zhou, Li Quan, Pan Liu
      Abstract: Transportation Research Record, Ahead of Print.
      The study aimed to analyze driver visual workload at unsignalized intersections with wide medians on high-speed divided highways. The study focused on two types of traffic movements: direct left-turns from minor roads at conventional intersections and right-turns followed by U-turn movements at restricted crossing U-turn (RCUT) intersections. A total of 430 left-turn trips and 40 right-turn followed by U-turn trips were collected from the Second Strategic Highway Research Program Naturalistic Driving Study database. Researchers analyzed the data from driver eye-glancing videos, demographic information, and driving history. The entropy rate of each trip was calculated as an indicator of the driver's visual workload and was treated as the dependent variable for the statistical analysis. Entropy rate is the metric of the randomness associated with drivers’ scanning patterns. The higher the entropy rate, the higher the workload. A comparative study of these two movements at these two types of intersections was conducted. Statistical analyses indicated that drivers at RCUT intersections engaged in less random scanning and longer average fixation and spent more than 70% of the time looking forward during the whole movement. Younger drivers at both types of intersections had higher entropy rates. Additionally, drivers at conventional intersections with higher annual average daily traffic (≥30,000) had higher entropy rates. These results could provide a better understanding of driver workload and its safety implications at different types of unsignalized intersections.
      Citation: Transportation Research Record
      PubDate: 2022-08-03T08:57:41Z
      DOI: 10.1177/03611981221112093
       
  • Pedestrian Crossing Decisions During Pedestrian Transition Signals at
           Signalized Intersections

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      Authors: Qun Chen, Shi Ye, Lu Chen
      Abstract: Transportation Research Record, Ahead of Print.
      In China, pedestrian transition signals that are set to green flashing or countdown signals are activated between red and green signals. They are used to remind pedestrians that the subsequent vehicle phase is ready to start and that pedestrians cannot start to cross; otherwise, pedestrian–vehicle conflicts may occur. However, during this phase, pedestrian crossing decisions are complex and are affected by many factors, such as distractions and companions. This paper aims to predict pedestrian crossing decisions by extracting these factors under various conditions. Four types of intersections in Changsha, China, including different transition signals (flashing green/countdown) and different crossing facilities (with a refuge island/with a median strip/without crossing facilities), were selected. A total of 1021 samples were collected. The assessment of crossing risks revealed that although crossing facilities can reduce risks, crossing pedestrians are still at a high risk. The results of logistic regression models indicate that the factors affecting crossing decisions vary at different intersections, and no single factor exerts the same impact.
      Citation: Transportation Research Record
      PubDate: 2022-08-03T08:55:16Z
      DOI: 10.1177/03611981221112091
       
  • Combined Effect of Changes in Transit Service and Changes in Occupancy on
           Per-Passenger Energy Consumption

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      Authors: Huiying Fan, Hongyu Lu, Ziyi Dai, Reid Passmore, Angshuman Guin, Kari Watkins, Randall Guensler
      Abstract: Transportation Research Record, Ahead of Print.
      Many transit providers changed their schedules and route configurations during the COVID-19 pandemic, providing more frequent bus service on major routes and curtailing other routes, to reduce the risk of COVID-19 exposure. This research first assessed the changes in Metropolitan Atlanta Rapid Transit Authority (MARTA) service configurations by reviewing the pre-pandemic versus during-pandemic General Transit Feed Specification (GTFS) files. Energy use per route for a typical week was calculated for pre-pandemic, during-closure, and post-closure periods by integrating GTFS data with MOVES-Matrix transit energy and emission rates (MOVES signifying MOtor Vehicle Emission Simulator). MARTA automated passenger counter data were appended to the routes, and energy use per passenger-mile was compared across routes for the three periods. The results showed that the coupled effect of transit frequency shift and ridership decrease from 2019 to 2020 increased route-level energy use for over 87% of the routes and per-passenger-mile energy use for over 98% of the routes. In 2021, although MARTA service had largely returned to pre-pandemic conditions, ridership remained in an early stage of recovery. Total energy use decreased to about pre-pandemic levels, but per-passenger energy use remained higher for more than 91% of routes. The results confirm that while total energy use is more closely associated with trip schedules and routes, per-passenger energy use depends on both trip service and ridership. The results also indicate a need for data-based transit planning, to help avoid inefficiency associated with over-provision of service or inadequate social distancing protection caused by under-provision of service.
      Citation: Transportation Research Record
      PubDate: 2022-08-03T08:34:46Z
      DOI: 10.1177/03611981221111160
       
  • Using Machine Learning to Predict Freight Vehicles’ Demand for Loading
           Zones in Urban Environments

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      Authors: Andres Regal Ludowieg, Ivan Sanchez-Diaz, Lokesh Kumar Kalahasthi
      Abstract: Transportation Research Record, Ahead of Print.
      This paper studies demand for public loading zones in urban environments and seeks to develop a machine learning algorithm to predict their demand. Understanding and predicting demand for public loading zones can: (i) support better management of the loading zones and (ii) provide better pre-advice so that transport operators can plan their routes in an optimal way. The methods used are linear regression analysis and neural networks. Six months of parking data from the city of Vic in Spain are used to calibrate and test the models, where the parking data is transformed into a time-series format with forecasting targets. For each loading zone, a different model is calibrated to test which model has the best performance for the loading zone’s particular demand pattern. To evaluate each model’s performance, both root mean square error and mean absolute error are computed. The results show that, for different loading zone demand patterns, different models are better suited. As the prediction horizon increases, predicting further into the future, the neural network approaches start to give better predictions than linear models.
      Citation: Transportation Research Record
      PubDate: 2022-08-02T06:04:17Z
      DOI: 10.1177/03611981221101893
       
  • Field Performance and Cost-Effectiveness of Chip Seals and Asphalt
           Concrete Overlays with and without Asphalt Concrete Stripping Damage

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      Authors: Hossam Abohamer, Mostafa A. Elseifi, Nirmal Dhakal, Zhongjie Zhang, Christophe N. Fillastre
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this study was to evaluate the effects of asphalt concrete (AC) stripping damage on the field performance and cost-effectiveness (CE) of chip seals and AC overlays in pavement maintenance and rehabilitation. To achieve this objective, in-service pavement sections were selected from the Louisiana pavement management system (LaPMS) database and the presence of moisture damage was confirmed through the visual inspection of extracted cores. Sections were categorized according to traffic volume and their pavement condition index before treatment (PCI-). Road sections in each group were then divided into two groups as stripped and non-stripped sections. The average deterioration rate (ADR), extension in pavement service life (ΔPSL), average condition improvement over the treatment service life (PI), and CE were compared for stripped and non-stripped sections. Results showed that for chip seal sections, moisture damage negatively affected the performance of the sections with PCI- < 80 and low traffic volumes. For sections with PCI-> 80, similar performance was observed for stripped and non-stripped sections. For AC overlays, moisture-induced damage significantly affected the long-term pavement performance at all traffic levels. On average, moisture-induced damage decreased ΔPSL, PI, and CE of AC overlays by 5 years, 24%, and 0.5%, respectively. Overall, results of the study demonstrated that moisture damage has a significant effect on the performance of chip seal and AC overlay. Therefore, it is critical to identify and repair stripped sections before the maintenance and rehabilitation of in-service pavements to ensure adequate performance and optimum CE.
      Citation: Transportation Research Record
      PubDate: 2022-08-02T06:02:36Z
      DOI: 10.1177/03611981221112407
       
  • Evaluating Driver Response to a Dynamic Speed Feedback Sign at Rural
           Highway Curves

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      Authors: Md Shakir Mahmud, Anshu Bamney, Megat Usamah Megat Johari, Hisham Jashami, Timothy J. Gates, Peter Tarmo Savolainen
      Abstract: Transportation Research Record, Ahead of Print.
      Research was performed to assess the effectiveness of a dynamic speed feedback sign (DSFS) as a speed reduction countermeasure when installed at horizontal curves on rural highways. It was of particular interest to assess whether the DSFS effectiveness varied based on curve advisory speed and to identify the optimal DSFS placement location with respect to the curve. A series of field evaluations were performed at five horizontal curves located along two-lane rural state highways in northern Michigan possessing posted speed limits of 65 mph and curve advisory speeds varying between 25 and 60 mph. The DSFSs were installed and evaluated at two different locations at each curve: 1. at the curve advance warning/advisory speed sign and 2. at the point of curvature. Vehicle speeds were tracked along the approach to each curve using handheld LIDAR guns. The results indicate that the DSFS was generally more effective at reducing motorists’ speeds when installed near the advance curve warning sign. Furthermore, the DSFS was more effective at locations with sharper curvature (i.e., lower advisory speeds). Continued use of DSFSs as a speed reduction countermeasure on rural horizontal curves is recommended, particularly at locations with a significant differential (e.g., at least 25 mph) between the upstream speed limit and the curve advisory speed. The DSFS should be positioned near the advance curve warning/advisory speed sign to provide adequate time for drivers to react and decelerate before reaching the curve.
      Citation: Transportation Research Record
      PubDate: 2022-08-02T05:58:34Z
      DOI: 10.1177/03611981221112401
       
  • Optimization-Based Traffic Safety Improvement Strategy for Autonomous
           Vehicle Driving at Level Crossings

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      Authors: Baye Yemataw Adane, Jin Hou, Bo Peng, Debalki Yonas Abate
      Abstract: Transportation Research Record, Ahead of Print.
      Railway level crossings pose a serious threat to the safety and mobility of drivers traversing them. Globally, a significant number of traffic violations occur annually at level crossings. This study proposes an optimization-based autonomous vehicle (AV) driving strategy to improve the traffic safety of AVs at level crossings. First, an optimization model considering the operational constraints is developed. The cost function of the proposed optimization-based driving strategy is the time difference between the time required by the train to reach the level crossing and the time taken by the AV to complete the whole crossing maneuver. Second, a MATLAB simulation model is developed to validate the proposed driving strategy. Simulation results show that the proposed driving strategy delivers optimized AV driving without stoppage. The comparative study also shows that the proposed method improves driving performance. For instance, when a train is 1 m away from the light signal while the AV’s initial speed is 36 km/h, the time required for the AV to reach the speed limit sign is about 0.44 s, while the time required by the train to reach the car block area is 0.13 s. Thus, the AV is forced to stop and then go after the train leaves the level crossing. Contrary to this, the proposed method allows a safe passage of the vehicle within 1.66 s without stoppage. Most importantly, the driving strategy is a collision avoidance strategy without unnecessary enforcement of stop-and-go when AVs have the chance of crossing safely. Consequently, the optimization-based driving strategy both improves traffic safety and reduces traveling time.
      Citation: Transportation Research Record
      PubDate: 2022-08-02T05:57:01Z
      DOI: 10.1177/03611981221110570
       
  • Robotic Competitions to Design Future Transport Systems: The Case of JRC
           AUTOTRAC 2020

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      Authors: Biagio Ciuffo, Michail Makridis, Valter Padovan, Emilio Benenati, Kanok Boriboonsomsin, Mamen Thomas Chembakasseril, Petros Daras, Viswanath Das, Anastasios Dimou, Sergio Grammatico, Ronny Hartanto, Malte Hoelscher, Yu Jiang, Suad Krilasevic, Shangrui Liu, Quang Nhat Nguyen Le, Cas Rosier, Pingbo Ruan, Zhensong Wei, Guoyuan Wu, Xuanpeng Zhao, Zhouqiao Zhao
      Abstract: Transportation Research Record, Ahead of Print.
      Vehicle automation and connectivity bring new opportunities for safe and sustainable mobility in urban and highway networks. Such opportunities are however not directly associated with traffic flow improvements. Research on exploitation of connected and automated vehicles (CAVs) toward a more efficient traffic currently remains at a theoretical level, and/or based on simulation models with limited reliability. Furthermore, testing CAVs in the real world is still costly and very challenging from an implementation perspective. A possible alternative is to use automated robots. By designing and testing both the low- and the high-level controllers of CAVs, it is indeed possible to reach a better understanding of the challenges that future vehicles will need to face. Robotic applications can effectively test these challenges within a wide variety of research communities—for example, via robotic competitions. Along this direction, the Joint Research Centre has organized the first European robotic traffic competition for automated miniature vehicles. Each team participated with four robots and was judged based on a set of indicators that assess the collective behaviors of the vehicles. Results show the suitability of the methodology with different teams proposing completely different approaches to deal with the challenge and thus achieving different results. Future competitions may further raise awareness about the possibility of using CAVs to improve traffic and to engage with a broader community to design systems that are really capable of achieving this goal.
      Citation: Transportation Research Record
      PubDate: 2022-08-02T05:53:34Z
      DOI: 10.1177/03611981221110566
       
  • Optimal Control of Automated Vehicles for Autonomous Intersection
           Management With Design Specifications

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      Authors: Shian Wang, Aidan Mahlberg, Michael W. Levin
      Abstract: Transportation Research Record, Ahead of Print.
      In this article, we study optimal control of automated vehicles (AVs) at an autonomous intersection with design specifications, where the intersection manager (computer) controls the acceleration/deceleration of AVs within a control region to determine their conflict-free trajectories. We develop a mathematical model to describe the cooperative dynamics of vehicles within the control zone of a signal-free intersection. Further, we formulate an optimization problem with the objective of maximizing traffic throughput while minimizing passenger discomfort. We then address the problem using mathematical programming to yield the optimal control input for each vehicle inside the control zone. We apply the proposed control mechanism for optimally coordinating the movement of AVs at an autonomous intersection subject to physical and safety constraints. In other words, the solution, if implemented, would allow vehicles to pass the intersection with safety guarantees (avoiding collisions), high-level efficiency (maximizing throughput), and good comfort (minimizing discomfort) without deploying traffic lights. In addition, we derive analytical specifications for the design and deployment of autonomous intersections, which appears to have been largely ignored in prior studies. Finally, we conduct a series of numerical experiments to show the effectiveness of the methodology proposed in this article. As the framework developed here is fairly general and can be extended to cover many complex traffic scenarios, we believe that the procedure presented in this article will be useful with the advent of AVs in the near future.
      Citation: Transportation Research Record
      PubDate: 2022-08-02T05:49:34Z
      DOI: 10.1177/03611981221109166
       
  • Prediction of Travel Time Reliability on Interstates Using Linear Quantile
           Mixed Models

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      Authors: Xiaoxiao Zhang, Mo Zhao, Justice Appiah, Michael D. Fontaine
      Abstract: Transportation Research Record, Ahead of Print.
      Under the Moving Ahead for Progress in the 21st Century Act (MAP-21), state Departments of Transportation (DOTs) are responsible for reporting travel time reliability and also setting targets and showing progress toward those targets. To know how to improve travel time reliability and what to expect from investments in transportation infrastructure, state DOTs need a better understanding of the factors that affect travel time reliability and methods to predict future travel time reliability. This paper proposes linear quantile mixed models (LQMMs) to quantify travel time reliability impact factors and predict selected reliability measures (level of travel time reliability [LOTTR] and the 90th percentile) to address these needs. The method was demonstrated using probe vehicle data from interstate segments in Virginia that had been partitioned into approximately homogeneous clusters based on the similarity of their cumulative distribution functions (CDFs) of travel times. Using clustered data meant that LQMMs were only necessary for a limited number of clusters rather than for hundreds of individual segments, thus making the process more efficient and manageable. The LQMMs showed that frequencies of non-recurrent events, such as incidents and weather, were correlated with higher travel time percentiles. The prediction performance of LQMMs was compared with trend line predictions, a common method used in practice. The results showed that LQMMs significantly improved prediction accuracy.
      Citation: Transportation Research Record
      PubDate: 2022-08-02T05:46:03Z
      DOI: 10.1177/03611981221108380
       
  • Leveraging Transformer Model to Predict Vehicle Trajectories in Congested
           Urban Traffic

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      Authors: Yufei Xu, Yu Wang, Srinivas Peeta
      Abstract: Transportation Research Record, Ahead of Print.
      Accurate vehicle trajectory prediction enables safe, comfortable, and optimal proactive motion planning for connected and autonomous vehicles (CAVs). Because of rapid advances in learning techniques and increasing access to massive amounts of data, deep learning techniques have been applied to predict vehicle trajectories, especially the long short-term memory (LSTM) model. However, the accurate prediction of vehicle trajectories for congested urban traffic remains problematic, as existing LSTM models do not perform well. To address this gap, this paper proposes to leverage an emerging deep learning technique—transformer—and utilizes a recently released dataset (pNEUMA) for predicting vehicle trajectories in congested urban traffic. The proposed transformer model uses the self-attention mechanism, which helps to identify dependencies within the model inputs, to systematically determine the impacts of vehicular interactions on the target vehicle’s future trajectory. The pNEUMA dataset, which provides drone-based large-scale data of congested urban traffic, is processed to fit a typical trajectory prediction scenario, and used to train the transformer model. Numerical studies are conducted to analyze the effectiveness of the proposed modeling approach. A comparison of the proposed model with representative LSTM models highlights the advantages of leveraging the transformer model characteristics for the vehicle trajectory prediction of congested urban traffic. By contrast, existing LSTM models may suffice for the trajectory prediction of freeway traffic. The results also indicate that, unlike for vehicle trajectory prediction for freeway traffic, a longer time window of inputs does not guarantee better prediction performance for congested urban traffic.
      Citation: Transportation Research Record
      PubDate: 2022-08-01T12:35:50Z
      DOI: 10.1177/03611981221109594
       
  • Safety Evaluation of Changing Speed Limit from 55 mph to 60 mph on
           Two-Lane, Two-Way Road Segments

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      Authors: Taha Saleem, Raghavan Srinivasan
      Abstract: Transportation Research Record, Ahead of Print.
      This paper describes the efforts to evaluate the safety impacts of increasing the speed limit from 55 mph to 60 mph on selected two-lane, two-way state highway road segments in Minnesota, U.S. An empirical Bayes (EB) before–after analysis was used to estimate crash modification factors (CMFs) for both segments (1,909.11 mi) and intersections (1,722 3-leg and 1,191 4-leg). Aggregate analysis conducted using all the segment and intersection data showed a 2.9% increase in total crashes, a 2.5% increase in injury (KABC) crashes, and a 0.05% reduction in the injury (KAB) crashes. These results—along with before-and-after operating speed data from another study by Minnesota Department of Transportation (MnDOT) (2019) showing that the 85th percentile operating speed remained the same and that the mean operating speeds increased by 1 mph following the speed limit increase—can lead to a conclusion that the speed limit increase from 55 mph to 60 mph had a minor effect on combined segment and intersection crashes or operating speeds. It is important to note that these results are specific to the corridors that were selected by MnDOT for the increase in speed limit; caution must be exercised when extending these to systemwide increases in speed limits in Minnesota or in other states, and when estimating long-term effects of speed limit increases as operating speeds can change over a longer period of time.
      Citation: Transportation Research Record
      PubDate: 2022-08-01T07:28:18Z
      DOI: 10.1177/03611981221110569
       
  • Influence of Internal and External Pressure Sensing on Green Travel
           Intention: Based on a Theoretical Model of the Theory of Planned Behavior
           and Pressure-state-response Model

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      Authors: Ranran Yang, Lanlan Li, Cuicui Wang, Chunxiao Yue, Jia Wei
      Abstract: Transportation Research Record, Ahead of Print.
      Factors that affect environmentally sustainable travel behavior (or “green travel”) and their mechanisms of action are important to understand to conserve energy and reduce emissions. We constructed a model by integrating the theory of planned behavior (TPB) and the pressure-state-response (PSR) model with individual cognition of green travel policies (external pressure) and sensitivity of environmental problems (internal pressure). Then, an empirical study of 796 urban residents in eastern China was conducted. The results show that, with regard to the TPB, attitude has a direct and significant impact on self-practiced and interpersonal intentions, while perceived behavior control has a similar effect on self-practiced green travel intentions. Further, our results also indicate that subjective norms have indirect influence on both self-practiced and interpersonal intentions by affecting attitudes. With regard to the PSR model, urban residents’ cognitions of external and internal pressures affect their green travel intentions in various ways. Based on the results, some relevant policy recommendations aimed at promoting green travel are proposed.
      Citation: Transportation Research Record
      PubDate: 2022-08-01T07:15:50Z
      DOI: 10.1177/03611981221110227
       
  • Safety Effectiveness of Autonomous Vehicles and Connected Autonomous
           Vehicles in Reducing Pedestrian Crashes

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      Authors: Susilawati Susilawati, Wei Jie Wong, Zhao Jian Pang
      Abstract: Transportation Research Record, Ahead of Print.
      This research aims to study the safety effectiveness of autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) in reducing pedestrian crashes in various scenarios. The proposed methodology involves (1) identifying factors that contribute to pedestrian crashes, (2) developing crash-frequency models to predict the pedestrian crash and identifying the model that performs the best, (3) identifying the AV and CAV technologies that can minimize and remove those identified factors, and (4) assessing the effectiveness of AV and CAV technologies in reducing pedestrian crashes for various road classifications. Using crash data obtained from San Francisco Transportation Injury Mapping System (TIMS) for 2016 to 2020, a two-level Bayesian Poisson lognormal (TLBPL) model is developed to assess the effectiveness of AVs and CAVs in reducing pedestrian crashes. The outcomes of the TLBPL model suggest that weather, lighting, and road classifications tend to influence more vehicle–pedestrian crashes in all road classifications. The results of TLBPL indicate that driver faults related to prediction ability contribute more to pedestrian crashes for all road classifications, while driver fault related to sensing (perception) on urban arterials is the factor contributing most to pedestrian crashes. This paper provides a framework for researchers and engineers to evaluate AVs’ and CAVs’ safety effectiveness by considering crash contributing factors and road classifications.
      Citation: Transportation Research Record
      PubDate: 2022-08-01T07:10:30Z
      DOI: 10.1177/03611981221108984
       
  • Relationship Between Daylight Saving Time and Traffic Crashes in Florida

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      Authors: Jesus E. Molina, Angela Kitali, Priyanka Alluri
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this study was to examine the effect of transitions between daylight saving time (DST) and standard time (ST) on traffic crashes in Florida. The study was conducted using 37 years of crash data from Florida from 1983 to 2019. The analysis was based on crashes that occurred during the week before and the week following the time change. The paired Wilcoxon rank test implemented using a Bayesian approach was used to compare the difference in crash frequency following the clock shift to DST. The analysis showed that the time shift has a significant effect on traffic crashes. More specifically, the beginning of DST in the spring, when the clock moves forward by one hour, was associated with a higher frequency of fatal and nighttime crashes. The shift at the end of DST in the fall, when the clock moves back by one hour, resulted in a significant increase in all, no injury, morning peak hours, afternoon off-peak hours, two-vehicle, and multiple-vehicle crashes. Crashes during evening peak hours decreased in the week immediately following the time change. These findings were particularly significant on the Sunday when the shift occurred and the following Monday and Tuesday. It can be inferred from these findings that the impact of DST on safety may be attributed to the disruption of circadian rhythms as well as to the one-hour loss in the spring and one-hour gain in the fall. The study findings could assist researchers and practitioners in understanding the impacts of DST on roadway safety.
      Citation: Transportation Research Record
      PubDate: 2022-08-01T07:08:31Z
      DOI: 10.1177/03611981221108396
       
  • Spatial Analysis of Relationships Between Intersection Safety, the Urban
           Built Environment, and Average Income Level: A Case Study of Des Moines

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      Authors: Dorcas Okaidjah, Monica Haddad, Christopher Day, Biswa Das
      Abstract: Transportation Research Record, Ahead of Print.
      This study makes a methodological contribution by exploring the relationship between motor vehicle traffic crashes at intersections and the built environment. The study focuses on specific neighborhoods within the city of Des Moines, Iowa, with contrasting socio-economic characteristics to examine variation between the neighborhoods. Exploratory spatial data analysis was used to locate crash clusters at intersections using seven-year crash data (2013–2019) obtained from the Iowa Department of Transportation. Google Street View was used to survey the built environment variables. Regression modeling was then utilized to establish a relationship between intersection crash clusters and the built environment. The results show that commercial/institutional land uses, bus stops, and signalized intersections are statistically significant and have a positive impact on intersection crash incidence. Additionally, crash incidences were higher in neighborhoods with below-average income percentages. These findings potentially can enlighten policymakers to focus on appropriate safety treatments such as traffic-calming measures and identify areas where traffic safety policies need to be prioritized. Policy re-evaluation for bus stop locations and design ideas for the urban form could be established to reduce motor vehicle intersection crashes.
      Citation: Transportation Research Record
      PubDate: 2022-08-01T07:07:09Z
      DOI: 10.1177/03611981221108392
       
  • Impact of Wildlife Crossing Structures on Wildlife–Vehicle
           Collisions

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      Authors: Wisnu Sugiarto
      Abstract: Transportation Research Record, Ahead of Print.
      This paper examines whether wildlife crossing structures reduce the number of wildlife–vehicle collisions. Using Washington state crash data from 2011 to 2020, I employed a difference-in-differences methodology at the year level on each of 13 observed wildlife crossing structures in Washington. The treatment area consisted of wildlife–vehicle collisions within 10 mi of a wildlife crossing structure, and the control area included wildlife–vehicle collisions that were 60 to 70 mi from the same wildlife crossing structure. I found evidence that wildlife crossing structures resulted in one to three fewer wildlife–vehicle collisions on average per mile per year. The marginal treatment effect also held within a 5-mi treatment area, a 15-mi treatment area, and when controlling for the presence of other structures within the baseline of a 10-mi treatment area. However, the collision reductions were more consistent among wildlife bridges than culverts, suggesting that not all wildlife crossing structures have the same effect in reducing accidents involving wildlife. Using a back-of-the-envelope approach, each wildlife crossing structure yielded annual benefits of $235,000 to 443,000 in 2021 U.S. dollars.
      Citation: Transportation Research Record
      PubDate: 2022-08-01T07:06:24Z
      DOI: 10.1177/03611981221108158
       
  • Clustering-Based Travel Pattern for Individual Travel Prediction of
           Frequent Passengers by Using Transit Smart Card

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      Authors: Pengyao Ye, Yiqing Ma
      Abstract: Transportation Research Record, Ahead of Print.
      Individual travel prediction is very important for the construction of intelligent urban transportation systems. Previous studies mainly focus on the improvement of algorithms, but pay little attention to the mining of data information. In this paper, the concept of the travel pattern is introduced into the field of individual travel prediction of frequent bus passengers. The travel pattern of passengers refers to the trip with similar boarding time and similar boarding and alighting stations of the same person. Through clustering the travel pattern by DBSCAN algorithm, the regularity of passenger travel can be better exploited and travel information can be integrated into a unified unit as well. In the process of prediction, we first predict whether the passenger will travel, and then, if so, predict the probability distribution of the next trip conditional on the previous one. The proposed method is tested using the Automatic Fare Collection data of Chengdu’s frequent bus passengers in May 2019. Based on travel pattern, the average accuracy of travel information prediction is about 41%, which is 13% higher than the method without using travel pattern. Furthermore, this paper also discusses the influence of spatial threshold in clustering on the prediction results.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T12:29:27Z
      DOI: 10.1177/03611981221111355
       
  • The Impacts of Incentives on Seat Yielding Behavior on the Bus

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      Authors: Farrukh Baig, Dong Zhang, Jie-ao Chen, Jaeyoung Lee
      Abstract: Transportation Research Record, Ahead of Print.
      The global target to achieve inclusive public transportation includes the availability of courtesy seating for vulnerable individuals such as elderly people, people with disabilities, pregnant women, and children. The frequent usage of courtesy seats by passengers who are not vulnerable individuals is an issue pertaining to public transportation. It is important to encourage the travelers to yield seats in the presence of vulnerable individuals because the latter might get seriously injured by falling if they stay on a moving vehicle. This study explores the influence of incentives and situational factors affecting individuals’ decisions to yield seats to vulnerable people. Through an online questionnaire survey, 404 valid responses were obtained. The generalized linear mixed model (GLMM) with repeated measures was used to identify the influential factors affecting the self-reported decisions of yielding seats to vulnerable individuals. The results indicate that the situational factors (health, crowd, vulnerable passenger type, standing time after yielding seats), incentive types, and incentive amounts are significant factors affecting the decisions to yield seats. The study’s findings also indicate that travelers are more sensitive to people with disabilities and pregnant women than to elderly people and children. The practical implications, including campaigning, education interventions, and incentive-based mechanism, were suggested to encourage travelers to yield seats to vulnerable individuals.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T12:10:53Z
      DOI: 10.1177/03611981221113311
       
  • Context Classification and Associated Transportation Expectations in
           Support of Contextual Roadway Design

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      Authors: Nikiforos Stamatiadis, Adam Kirk, Hermanus Steyn, Jennifer Musselman, Mary Raulerson
      Abstract: Transportation Research Record, Ahead of Print.
      In the United States, highway functional classification has played a central role in planning and designing roadway projects. Classifications have served as a surrogate for design inputs (e.g., design speed). However, functional classification lacks the resolution needed to develop context-sensitive designs and prioritizes motor vehicles over other modes of transportation. NCHRP Report 855 introduced an expanded context classification system that supports more integrative and context-adapted roadway designs. This system was subsequently adopted in the 7th Edition of the Policy of Geometric Design for Highways and Streets (Green Book). Transitioning from functional classification to context classification as the primary basis of design entails a major shift in design practices. Context sets expectations for each setting and informs the entire project development process—from visioning to design and implementation. Based on a review of context classification systems adopted by state departments of transportation (DOTs), this paper updates the Green Book’s context classifications and introduces the concept of Transportation Expectations, which are fundamental concepts that define how users expect to move in each context. A case study focused on Lexington, Kentucky, U.S., explores these concepts and discusses how they facilitate multimodal roadway designs—the focal point of the upcoming Green Book 8th Edition.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T12:09:33Z
      DOI: 10.1177/03611981221112397
       
  • Assessment of Polyacrylamide Concentration in Construction Stormwater
           Runoff Using an ASTM D6459 Rainfall Simulator

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      Authors: Christin Manning, Michael Perez, Wesley Donald
      Abstract: Transportation Research Record, Ahead of Print.
      Polyacrylamide (PAM) is a polymer used in construction stormwater management as both an erosion and sediment control measure. PAM is considered one of the environmentally safest polymers on the market, however overapplication concerns dictate that large quantities in runoff be avoided. For slope erosion applications, ensuring proper concentration requires methods for testing residual concentrations. This research investigated residual concentrations of PAM when dry-applied at a rate of 25 lb/acre (28 kg/ha) for slope stabilization and subjected to 1-h of simulated rainfall following ASTM D6459-19 protocols at three 20-min successive 2-, 4-, and 6-in./h (5-, 10-, and 15-cm/h) intensities. Residual concentrations were determined by centrifuging runoff samples to remove soil and reading absorbance from an ultraviolet-visible spectrometer, comparing values to those at known concentrations. Concentrations in collected runoff samples were found to surpass values found in previous research and in other PAM applications, especially during first flush, and were high enough to affect water viscosity. An alternative application method is presented that may mitigate PAM runoff concentration. The spectrometry method was also used to highlight the possibility that polymers used in hydromulches may also deposit excess concentrations in stormwater runoff, and that formal residual testing of such products is warranted. The processes used for this study demonstrated how discharge may be monitored and regulated to minimize undesirable runoff conditions from construction sites and underscore the importance of appropriate design and implementation when using additives for erosion control.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T12:07:32Z
      DOI: 10.1177/03611981221111157
       
  • Analysis of Roadway Grade Estimations From Global Positioning Systems and
           Barometer Measurements

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      Authors: Michael P. Pratt, Raul E. Avelar
      Abstract: Transportation Research Record, Ahead of Print.
      Roadway grade is used as an input variable for several highway analysis tasks, including evaluating curve margin-of-safety, applying safety prediction models, assessing the adequacy of sight distance, and maintaining state roadlog databases. However, collecting accurate grade data is often expensive owing to the need to obtain field measurements or review as-built plan sets. Agencies would benefit from the development of a method to compute roadway grade from an automated data collection system. This paper documents a comparison of roadway grade estimations computed from global positioning system (GPS) and barometric altimeter data streams obtained during test drives on highway segments of interest. To calibrate the estimation method, the authors obtained ground-truth grade measurements collected from the field and then modeled those measures as responses in a time series model with the two data stream types as explanatory variables. The authors found that for several applications, the elevation data obtained from GPS were adequate to obtain reasonable estimates, but such estimations could be improved with a supplemental data stream from a barometer.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T12:06:15Z
      DOI: 10.1177/03611981221111154
       
  • Safe System for Intersections Method Scoring: Comparing Intersection
           Alternatives Based on Exposure, Kinetic Energy Management, and Movement
           Complexity

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      Authors: Michael R. Dunn, Ivy Huang, Richard J. (R.J.) Porter
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation agencies across the U.S. are increasingly looking to the Safe System approach as a path toward achieving Vision Zero and other similar road safety performance goals. Vision Zero and the Safe System approach seek to eliminate traffic fatalities and serious injuries. The Federal Highway Administration (FHWA) funded an effort to create a Safe System for Intersections (SSI) method to provide a technical basis by which road planners and designers could apply Safe System principles on intersection projects, detailed in the report A Safe System-Based Framework and Analytical Methodology for Assessing Intersections. Applying the SSI method results in a set of SSI scores for each intersection design under consideration. The SSI scores characterize the extent to which an intersection alternative aligns with Safe System principles. This paper builds on the content presented in the FHWA report and describes how the key SSI method components of user exposure, conflict point severity, and intersection movement complexity are combined to produce the SSI scores. This additional background and detail on the development of the SSI scores will support future applications of the method and the identification of future research needs and method improvements.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T12:02:32Z
      DOI: 10.1177/03611981221111152
       
  • Vulnerability Analysis of Casablanca Road Network by Capacity Weighted
           Spectral Analysis

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      Authors: Meilan Jiang, Othman El Mourabiti, Tomio Miwa, Takayuki Morikawa
      Abstract: Transportation Research Record, Ahead of Print.
      The serviceability of a road network often faces challenges of traffic congestion and natural disasters which can damage the performance of many links within the network. To ensure the high performance of a road network, it is essential to identify and protect the critical links which if disrupted will cause substantial damage to the network. This study analyzes the vulnerability of the road network of the city of Casablanca in Morocco. Capacity weighted spectral analysis of the graph Laplacian is used to evaluate the road network vulnerability and identify potential critical links. We consider two cases concerning the weight definition: capacity weighted without considering travel demand and reserve capacity weighted with consideration of travel demand. After finding the critical links of the network, we investigate its vulnerability with consideration of a future tramway project. We compare two cases: the road network with the current tramway lines and that including two additional tramway lines planned for the future. The results show shifts in the critical links between the two cases. Furthermore, an increase in vulnerability is observed after the construction of the new tramway lines if no measures are taken to maintain the corresponding link capacities.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T11:57:51Z
      DOI: 10.1177/03611981221110565
       
  • Arterial Signal Offset Optimization Using Crowdsourced Speed Data

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      Authors: Liang Xia, Xiaofeng Li, Mohammad Razaur Rahman Shaon, Yao-Jan Wu, Xinguo Jiang
      Abstract: Transportation Research Record, Ahead of Print.
      Signal offset for coordinated traffic signal control is traditionally optimized based on posted speed limit, free-flow speed, or average speed among intersections, without considering the variations of travel speed. Variation in travel speed caused by interference on arterials may lead to inaccurate offset estimation, reducing the efficiency of coordination control. Therefore, this study develops an arterial offset optimization method for traffic signal coordination control using real-time speed collected from high-resolution crowdsourced data. The objective of the proposed method is to minimize the average delay on the corridor. The optimization problem is formulated as integer programming, and a genetic algorithm (GA) is utilized to search for the best offset solution. The proposed method is evaluated on a major arterial (Speedway Boulevard) in Tucson, Arizona. In the numerical exercise, the effectiveness and performance of the proposed method are evaluated in various scenarios, including a scenario with non-recurring congestion. The results show that using high-resolution real-time speed data can reduce travel delay time in a coordinated direction by 32.5% and 17.6% when compared with methods using speed limit and free-flow speed, respectively, and the proposed method is more reliable and robust for handling traffic conditions with varying volume and speed.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T10:28:08Z
      DOI: 10.1177/03611981221109177
       
  • Multi-Stage Equitable Bus-Based Hurricane Evacuation Model With a
           Stochastic Driver Availability Component

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      Authors: Ding Wang, Kaan Ozbay
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation planning before the actual landfall of a hurricane can save lives by allowing evacuees to be transferred from the affected area to shelters in a safe and timely manner. This paper aims to fill an important research gap by proposing a detailed framework for bus-based evacuation planning with fair resource allocation in dense urban areas. We deconstruct the bus-based evacuation problem into multiple stages. Firstly, we identify a subset of existing bus stops to serve as bus pickup locations during the evacuation through the use of an integer programming model. The objective is to minimize the total number of pickup locations while ensuring full coverage of the demand. Secondly, the selected bus pickup locations are assigned to shelters where safe shelters are provided by the government. An equity component was introduced in the shelter assignment stage to ensure fair evacuation resource allocation. Finally, a bus driver management model was proposed that can be used to determine the optimal crew size in bus-based evacuation planning. A hypothetical hurricane evacuation scenario in New York City was used to evaluate the performance of the proposed methodology and the impact of model parameters. The results can provide feasible decisions on identifying bus pickup locations, shelter assignment, as well as the number of drivers needed for transit-based evacuation planning. The equity component shows a noticeable increase in equity index despite it only adding a small cost to the average travel distance.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T10:26:20Z
      DOI: 10.1177/03611981221109158
       
  • Mobility Hubs: Review and Future Research Direction

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      Authors: Thomas Arnold, Matthew Frost, Andrew Timmis, Simon Dale, Stephen Ison
      Abstract: Transportation Research Record, Ahead of Print.
      Globally, cities face a range of transport-related environmental, social, and economic challenges, not least congestion, air pollution, and promotion of sustainable modes of public transport. Mobility hubs (MHs) have been identified as a mechanism to aid the move toward a sustainable transport network and are at various stages of implementation in cities throughout the world. The growing prevalence of MH schemes highlights the requirement for a holistic overview of MH networks to ascertain their characteristics and inform policy direction. Consequently, this study presents a review of current MH deployment and literature, with the aim of examining this global phenomenon and identifying a future research agenda. The study combines a comprehensive review of web searches with gray literature and a limited number of articles from academic journals. Twenty locations, at different stages of development and implementation, were identified as examples to be reviewed and analyzed, thereby providing a context for the review. Subsequently, four themes have emerged: objectives of MHs, format, location, and operational factors. Key findings include the importance of stakeholder engagement in design and location choices, the significance of branding, and connection with existing travel infrastructure including public transport and active travel. Additionally, the provision of amenities is common to MH schemes because it promotes usage and integration into the local landscape. From this detailed review of the state of MHs, a future research agenda has been identified, including further defining MHs, understanding the origin and applicability of MH objectives, considering day-to-day operations, policy transfer implications, and further evaluations of single and network MHs.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T10:23:09Z
      DOI: 10.1177/03611981221108977
       
  • Challenges in Rear-end Conflict-based Safety Assessment of Highly
           Disordered Traffic Conditions

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      Authors: Ritvik Chauhan, Ashish Dhamaniya, Shriniwas Arkatkar
      Abstract: Transportation Research Record, Ahead of Print.
      Surrogate safety measure (SSM)-based proactive safety assessment in developing economies like India with weak lane discipline mixed traffic conditions is limited and often lacks qualitative aspects of reliability. On further investigation, challenges of data acquisition, the viability of a specific SSM, the corresponding threshold value for the identification of conflict, and availability of reliable road crash data are observed to be the key hurdles in achieving robust results and proposing measures for mitigating rear-end conflicts and risks of crashes. The present study highlights the hurdles in performing the safety assessment for rear-end conflicts in mixed traffic conditions with weak lane discipline and proposes possible measures to overcome these hurdles.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T06:28:47Z
      DOI: 10.1177/03611981221108156
       
  • Impact of Variability of Car-Following Parameters on Road Capacity: The
           Simple Case of Newell’s Model

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      Authors: Carlos Mario Gomez Patiño, Christine Buisson, Mehdi Keyvan-Ekbatani
      Abstract: Transportation Research Record, Ahead of Print.
      This paper contributes to the vehicle-level analysis of two macroscopic features of the road traffic: capacity variability and capacity drop. This paper focuses only on car-following (CF) behavior and leaves the part related to lane-change maneuvers for future research. In particular, a simplistic CF model (Newell’s with bounded acceleration) for a single-lane scenario is studied. In this work, by introducing a speed limitation across a zone, a bottleneck with variable nominal capacity has been created. A continuous event-based numerical resolution method is used. Consequently, it is possible to vary the three Newell’s model parameters: maximal acceleration, minimal distance, and reaction time. It has been shown that the variability of those CF parameters (e.g., reaction time, minimal distance, and maximal acceleration) has a strong impact on pre-breakdown capacity variation and also on queue discharge flow. It has been concluded that this parameters variability does affect the drop (provided that the maximal acceleration has a relatively high mean value). Various distribution shapes (uniform, truncated Gaussian, and Gamma) have been explored. It has been realized that this does not have any significant impact on the capacity distribution. Concerning the amplitude of the capacity distribution, it is demonstrated that reaction time is the parameter with the highest impact followed by minimal distance. If all parameters vary with an amplitude of 30%, it is shown that the capacity standard deviation, in this scenario without lane changes, is about half the experimental values reported in the literature.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T06:23:32Z
      DOI: 10.1177/03611981221105278
       
  • Machine Learning and Image Recognition Technologies to Identify Built
           Environment Barriers and Incentives to Walk

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      Authors: Shanna Trichês Lucchesi, João de Abreu e Silva, Ana Margarita Larranaga, Douglas Zechin, Helena Beatriz Bettella Cybis
      Abstract: Transportation Research Record, Ahead of Print.
      The local built environment characteristics deeply influence pedestrians’ behavior, favoring or imposing barriers on walking trips. However, identifying micro-scale built environment data is challenging and time consuming, and in developing countries there is a general lack of reliable information at street level. The recent development of machine learning and image recognition algorithms is helping researchers to collect data quickly, automatically, and on a large scale. Therefore, this study aims to test the application of an existing semantic segmentation algorithm to represent urban scenes in the city of São Paulo. A confirmatory multivariate technique (structural equation model [SEM]) is used to test if a combination of the predetermined categories derived from machine learning algorithms helps to understand which type of environment (urban scenes) represents barriers or incentives to walk. The impacts of the urban scenes on the walking behavior mediated by the walkability perceptions were tested using the aforementioned SEM model. Car-oriented and unoccupied areas, with a high presence of heavy vehicles and a large presence of vegetation, are considered detrimental to the walkability perception and consequently to the walking frequency. On the other hand, densified areas, proximity to public transportation routes, and the presence of lighting and other pedestrians are considered friendlier for pedestrians, encouraging residents to walk.
      Citation: Transportation Research Record
      PubDate: 2022-07-30T06:18:48Z
      DOI: 10.1177/03611981221097965
       
  • GPS-Based Traffic Conditions Classification Using Machine Learning
           Approaches

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      Authors: Usman Ahmed, Ran Tu, Junshi Xu, Glareh Amirjamshidi, Marianne Hatzopoulou, Matthew J. Roorda
      Abstract: Transportation Research Record, Ahead of Print.
      This paper addresses the problem of accurately estimating traffic conditions based on sparse GPS information. GPS data have limited spatial-temporal availability, particularly at a regional scale. Therefore, it lacks reliability to accurately estimate traffic conditions of a transportation network. This study proposes a novel methodology to address this problem. First, instead of estimating traffic conditions on a geographic road segment, traffic conditions are estimated for trip segments, which span multiple road segments. Second, machine learning methods are applied to classify traffic conditions. In this study, traffic conditions are defined as the combination of congestion level and road type. This study develops two machine learning models—a random forest (RF) model and a supervised clustering method—to classify traffic conditions, using trip characteristics such as average speed and acceleration. The two models are compared in relation to their accuracy and computational efficiency. Results show that speed-related trip characteristics, such as average instantaneous speed, are the most important variables for classifying traffic conditions in both methods. In addition, the proportion of idling in a trip is essential in distinguishing the Congested Highway and Uncongested Urban traffic conditions when applying the supervised clustering method. The comparison shows that the RF model has a higher estimation accuracy (81%) than the supervised clustering method (72%). Overall, this study shows that traffic conditions can be determined efficiently even in cases of limited GPS data.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T07:05:37Z
      DOI: 10.1177/03611981221111370
       
  • Allocation of Drivers’ Visual Attention During Preliminary Uses of
           Automated Driving: A Wizard-of-Oz Study

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      Authors: Jessy Barré, Aisha Sahai, Mercedes Bueno
      Abstract: Transportation Research Record, Ahead of Print.
      In this experiment, we analyzed drivers’ visual attention during their first experiences with automated driving (AD). At the beginning of the study, participants (n = 45) received one of three AD training modules: paper, video, or practice. They then drove two sessions on a public road with a Wizard-Of-Oz vehicle, each ending with a request to intervene (RTI). The first session (forward path) included 10 min of AD with a mandatory non-driving-related task (NDRT). The second session (return path) included 10 min of AD with a nonmandatory NDRT. Control checks (number and duration of gazes) toward the road and rear-view mirrors and three self-assessment questionnaires (trust, acceptability, and technophilia) were measured during both sessions. The results indicated a decrease in road and rear-view mirror gazes over time, mainly for the practice group. Drivers with a low level of trust glanced at the road and mirrors more often than participants with a high level of trust. In addition, participants with a high level of technophilia spent less time controlling the road traffic but only during the forward path. Visual attention on the road decreased rapidly during the first minutes of AD, mainly among drivers who followed the practice training and those who had a high level of trust and were tech-savvy. We observed that participants looked at the rear-view mirrors after 10 and 14 s on average after the RTI. These results raise questions about driver situation awareness in critical situations, including the capacity to intervene in an efficient and safe way during takeover requests.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T07:04:11Z
      DOI: 10.1177/03611981221108980
       
  • Dynamic All-Red Extension: An Innovative Safety Countermeasure to Treat
           Red Light Running Crashes

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      Authors: Carrie L. Simpson
      Abstract: Transportation Research Record, Ahead of Print.
      The purpose of this project was to evaluate the safety effectiveness of Dynamic All-Red Extension (DARE) systems. North Carolina Department of Transportation has used DARE to combat red light running (RLR) crashes on major road approaches of selected rural, isolated traffic signals since 2011. Sixteen intersections were included in the before–after analysis. DARE systems in this study were implemented to target a specific crash type: frontal impact crashes (angle, left turn, right turn, head on) caused by vehicles traveling through the intersection and running the red light. Although there was some variability in the magnitude and significance of the results among treatment groups, there was a general reduction in the frequency of target RLR crashes. The crash modification factor (CMF) using empirical Bayes (EB) methodology was 0.93 (7% reduction in target RLR crashes) for all 16 treatment sites; for seven multilane at two-lane sites where DARE was the sole treatment, CMF was 0.65 (35% reduction in target RLR crashes), which was statistically significant at the 95% confidence level. The benefit–cost ratio of the treatment was 143:1, realized from low installation cost and the high cost of RLR crashes. The treatment appeared promising as a systemic safety treatment applied to isolated intersections with higher speed limits, especially for intersections with multilane major roads. Safety professionals should consider adding this safety countermeasure to the limited list of tools available to treat RLR crashes. DARE was inexpensive, demonstrated safety benefits, and caused minimal delays in rural applications without creating driver habituation.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T07:01:56Z
      DOI: 10.1177/03611981221108386
       
  • Deep Reinforcement Learning Approach for Automated Vehicle Mandatory Lane
           Changing

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      Authors: Rami Ammourah, Alireza Talebpour
      Abstract: Transportation Research Record, Ahead of Print.
      This paper proposes a reinforcement learning-based framework for mandatory lane changing of automated vehicles in a non-cooperative environment. The objective is to create a reinforcement learning (RL) agent that is able to perform lane-changing maneuvers successfully and efficiently and with minimal impact on traffic flow in the target lane. For this purpose, this study utilizes the double deep Q-learning algorithm structure, which takes relevant traffic states as input and outputs the optimal actions (policy) for the automated vehicle. We put forward a realistic approach for dealing with this problem where, for instance, actions selected by the automated vehicle include steering angles and acceleration/deceleration values. We show that the RL agent is able to learn optimal policies for the different scenarios it encounters and performs the lane-changing task safely and efficiently. This work illustrates the potential of RL as a flexible framework for developing superior and more comprehensive lane-changing models that take into consideration multiple aspects of the road environment and seek to improve traffic flow as a whole.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T07:00:35Z
      DOI: 10.1177/03611981221108377
       
  • Tabu-Search-Based Combinatorial Subset Selection Approach to Support
           Investigation of Built Environment and Traffic Safety Relationship

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      Authors: Onur Alisan, Hediye Tuydes-Yaman, Eren Erman Ozguven
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic crashes are a leading cause of death globally, with an increasing rate in urban areas. Thus, this study focuses on the relationship between built environment (BE) and traffic safety (TS), by constructing a relationship model using BE variables. The aim of this paper is to determine the best subset of BE variables through a generalizable methodology. The BE is operationalized through the D-classification (e.g., density, diversity, and design), and various datasets are collected from different agencies. TS is operationalized through motor vehicle involved (MOT) and vulnerable road user (VRU)-involved crash frequencies at the zonal level. A preliminary GIS-based process is conducted to associate the crash data at the census block group (BG) level, followed by examining the BE-TS relationships through a series of negative binomial models optimized for subset selection. The model generation is performed automatically by an embedded Tabu Search procedure. Two case studies are presented: a single-county case (Leon County, Florida, U.S.) and a tri-county case (Miami-Dade, Broward, and Palm Beach Counties, Florida, U.S.). Results show that some BE variables such as total population, age of housing stock, number of bus stops, and traffic volume have consistently positive relationships with crash occurrences. In contrast, several factors show varying effects by crash type or location. For example, motorized mode percentage has a negative relation with crash occurrences in the single-county case whereas it is insignificant for the tri-county case where the non-motorized mode percentage has a positive effect on crash occurrences.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T06:57:15Z
      DOI: 10.1177/03611981221108161
       
  • Understanding Productivity in the Transportation Construction Industry

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      Authors: Guillermo Nevett, Paul M. Goodrum, Ray L. Littlejohn
      Abstract: Transportation Research Record, Ahead of Print.
      There is an ongoing long-term debate about trends in construction productivity. This research examines the productivity of the transportation construction segment, specifically the transportation construction industry in Colorado. The paper examines 14 years of transportation data from 880 projects executed in the state of Colorado between 2004 and 2016. By evaluating the coefficients extracted from over 35 linear regression models, it analyzes how productivity in the Colorado transportation construction industry has evolved over recent years. Provided with a rich database, the study focuses on productivity at the more detailed project level, which will help explain the varying trends observed by different authors. This level of detail presents a comprehensive analysis of productivity for a segment of the transportation construction industry that has not yet been described in the literature.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T06:53:35Z
      DOI: 10.1177/03611981221108157
       
  • Verification and Efficacy of Automated Queue Detection Systems on
           Interstate Intelligent Work Zones

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      Authors: Li Zhao, Laurence R. Rilett
      Abstract: Transportation Research Record, Ahead of Print.
      Intelligent work zones have been widely adopted in the United States because they have been proven to improve traffic safety and operations. One specific intelligent work zone system, known as automatic queue detection (AQD), is designed to measure work zone-related queueing in real time, and inform drivers upstream so they may be prepared to slow down or stop. This paper describes an evaluation of the performance and efficacy of four AQD systems implemented at work zones on Interstate 80 in Nebraska. Specifically, (i) the system performance was verified by examining whether the messages displayed on the portable dynamic message signs (PDMS) were consistent with the underlying AQD logic, and (ii) the system efficacy was measured by determining whether the overall speeds of individual vehicles and the space mean speed (SMS) were reduced when warning messages were provided. It was found that the AQD systems were functioning well as evidenced by an error rate of 0.7 to 2.3%. It was concluded that the SMS was reduced in response to the PDMS warning display indicating that there was slow or stopped traffic ahead. The decrease in SMS was found to be statistically significant and in the range of 3.5 to 7 mph. This was approximately 47% greater than the reduction in SMS that occurred when the PDMS did not display any message. In summary, it was found that the AQD systems were operating correctly and, more importantly, they were effective in reducing the speeds of the traffic stream downstream of the PDMS.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T06:47:30Z
      DOI: 10.1177/03611981221108155
       
  • Multi-Criteria Assessment of Bridge Sites for Conducting PSTD/ISTD: Case
           Histories

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      Authors: Abdolreza Osouli, Mostafa Ebrahimi, Daniel Alzamora, Heather Z. Shoup, James Pagenkopf
      Abstract: Transportation Research Record, Ahead of Print.
      The Federal Highway Administration (FHWA) has recently developed the Portable Scour Testing Device (PSTD) to improve scour analysis around bridge piers in cohesive soils as part of the NextScour project. The PSTD is a compact field erosion testing device that, apart from a drill rig and larger water pump, has a lot of similarity with the In-situ Scour Testing Device (ISTD) in mechanism and data acquisition. The purpose of this paper is to provide recommendations on the suitability of using PSTD and ISTD at sites that have cohesive subsurface soils. An overview of the capabilities and limitations of the PSTD/ISTD in relation to hydraulic considerations, soil types, depth coverages, and erodibility potential is given. A multi-criteria assessment methodology to evaluate site suitability for conducting PSTD/ISTD is presented. The assessment methodology was utilized to detect suitable sites among 30 Illinois bridge sites using soil layer information, boring locations, groundwater level readings, in-situ testing results, geospatial analysis, site accessibility, and aerial photos.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T06:45:50Z
      DOI: 10.1177/03611981221108153
       
  • Determinants of Influence Factors in Crashes Alongside an Intersection
           Using a Multinomial Logit Approach

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      Authors: Baye Yemataw Adane, Jin Hou, Bo Peng, Hamid Ullah, Debalki Yonas Abate
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic violations are the leading cause of fatalities and injuries, and current trends indicate that this will proceed in the foreseeable future, especially alongside intersections. This study aims to examine the determinants of crash influencing factors alongside intersections using unweighted data points collected from the Michigan counties of Wayne, Genesee, and Macomb. Firstly, the random forest method identifies the significant predictor variables. Meanwhile, six predictor variables are considered: the speed limit, distance, light condition, crash location, train involvement, and weather conditions. Secondly, the multinomial logit approach is adopted to investigate the relationships among crash violation categories. Thus, the model predicts the likelihood of crash violation outcomes: angle, head-on, rear-end, rear-end right/left turn, same sideswipe, opposite direction, and single-vehicle crash. Likewise, the results confirmed that the predictor variables of the distance between 0 and 82 ft and train involvement increased the likelihood of a crash violation when driving at a speed limit of 26–50 mph. In addition, when the speed limit is between 0 and 25 mph, the odds ratios were greater than 1.0 (4.01, 3.85), indicating statistically significant positive relationships between the same sideswipe and opposite direction violations. Therefore, speeding is risky, but the safest speed is not always the slowest speed. Thus, the results provide evidence that the predictor variables are linked to various crash violations. Consequently, the findings of this study can be used to reduce the occurrence of crash violation and improve intelligent modes of transportation by transforming large datasets into knowledge and actionable intelligence considering the future roles of driving strategies.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T06:44:02Z
      DOI: 10.1177/03611981221108150
       
  • Advanced Gap Seeking Logic for Actuated Signal Control Using Vehicle
           Trajectory Data: Proof of Concept

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      Authors: Andalib Shams, Christopher M. Day
      Abstract: Transportation Research Record, Ahead of Print.
      As detection systems improve, opportunities are emerging for using vehicle position and speed to drive signal control. This study explored how basic actuation processes might be improved by using vehicle position and speed. The position and speed of arriving vehicles were used to calculate their estimated time of arrival. Two variations on vehicle extension logic were developed that extended a green until there was a headway in the arriving traffic above a size that corresponded to a minimum flow rate, at which it was desired to terminate the phase. In the first method, the headway was measured from the point where the leading vehicle passed the stop bar, whereas the second method measured the headway from where the leading vehicle was unlikely to stop at the onset of yellow. This was compared against a control with a conventional stop bar and upstream detectors. A simulation study was carried out for an eight-phase intersection. The results suggest that at higher levels of demand, trajectory-based actuation could yield substantial reductions in delay. The trajectory-based methods were able to terminate green more efficiently, leading to reductions in delay in some cases, and reductions in emissions and fuel consumption, although there was a tradeoff in the number of split failures. These early results show promise for the development and fine-tuning of the methods.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T06:42:42Z
      DOI: 10.1177/03611981221108147
       
  • Predicting for Traffic Risk Degree: Novel Prediction Method and Samples

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      Authors: Bo Li
      Abstract: Transportation Research Record, Ahead of Print.
      To effectively predict the risk degree in both maritime and road traffic, a novel method is proposed in this study. First, the improved Dempster–Shafer evidence theory was derived to address multiple evidence based on the uncertain mass in the traffic environment. Further, the iterative combination equations reduced the computational complexity when computing the traffic risk degree in a given scan. Accordingly, the modified adaptive Kalman filter was explored to predict the traffic risk degree for the next scan. To maintain a positive definiteness in the estimation covariance during the whole filtering process, the Cholesky decomposition was applied to enhance reliability. By transmitting the lower triangular matrix from the Cholesky decomposition of estimation covariance, the computational complexity was reduced relatively. Finally, the experiment results indicated that the proposed method had satisfactory prediction performance for the traffic risk degree.
      Citation: Transportation Research Record
      PubDate: 2022-07-28T06:41:59Z
      DOI: 10.1177/03611981221110225
       
  • Overfitting Prevention in Accident Prediction Models: Bayesian
           Regularization of Artificial Neural Networks

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      Authors: Nicholas Fiorentini, Diletta Pellegrini, Massimo Losa
      Abstract: Transportation Research Record, Ahead of Print.
      In the present paper, we implemented the Bayesian regularization (BR) backpropagation algorithm for calibrating an artificial neural network (ANN) as an accident prediction model (APM) to be used on Italian four-lane divided roads. We chose the BR-ANN since it efficiently allows for dealing with small sample size and avoiding overfitting issues by adding a regularization term in the objective function to be minimized during training. Moreover, BR-ANNs are sparsely employed in road safety analyses, and their peculiarities deserve to be emphasized. In our work, the BR-ANN aims to predict the number of fatal and injury (FI) crashes across 236 road elements, for a total length of 78 km. The input features are road element length, horizontal and vertical alignment, cross-section geometry, operating speed, traffic flow, sight distance, and road area type (i.e., a categorical predictor accounting for the potential influence of merge and diverge influence areas). Training and test phases of the BR-ANN have been evaluated by determination coefficient (R2), root mean square error (RMSE), overfitting ratio (OR), scatterplots, residuals analysis, and by the same ANN architecture trained with the gradient descent (GD) with momentum and adaptive learning rate backpropagation algorithm (GD-ANN). Results demonstrate that the BR-ANN markedly outperforms the GD-ANN, which suffers severe overfitting issues. Furthermore, BR-ANN does not overfit data (OR close to the unity), reports a satisfactory R2 (0.726), and shows a Gaussian residual distribution with zero mean. Therefore, road authorities could consider regularized ANNs for performing appropriate safety analyses, especially when dealing with small road sample sizes.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T10:01:54Z
      DOI: 10.1177/03611981221111367
       
  • Transfer Penalty Estimation of Bus Passengers Considering Travel Frequency
           in Chengdu, China

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      Authors: Pengyao Ye, Yifeng Deng, Hong Yang, Wenbo Fan
      Abstract: Transportation Research Record, Ahead of Print.
      The paper aims to examine bus passengers’ route choice behavior in the context of transfer penalty estimation. Methodologically, it leverages passengers’ stop-level trip information inferred from automatic vehicle location (AVL) and automated fare collection (AFC) data and compares the stop-level origin–destination (O-D) pairs with direct paths and transfer paths. The route choice models were established with the inclusion of normalized travel frequency as a key variable. A case study was performed using the trip data of adult card holders from the bus systems in Chengdu, China. The results show that the normalized travel frequency is a variable that makes an informative contribution to the explanation of passenger route choices. Specifically, passengers with higher travel frequency prefer to choose the transfer path. Moreover, the transfer penalty function in the context of the monthly travel frequency was obtained and shows that the travel frequency can reduce a passenger’s transfer penalty. Finally, the stabilities of the normalized travel frequency function and transfer penalty function were assessed using the trip data from the weekdays in four weeks with the results showing that the normalized travel frequency function is similar in shape. In addition, the relationship between a passenger’s monthly travel frequency and their familiarity with the bus network was discussed using the second derivative of the normalized travel frequency function.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:58:33Z
      DOI: 10.1177/03611981221110229
       
  • Examining the Relationships between Multimodal Environments and
           Multitasking Driving Behaviors

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      Authors: Tianqi Zou, Huizhong Guo, Moein Khaloei, Don MacKenzie, Linda Ng Boyle
      Abstract: Transportation Research Record, Ahead of Print.
      This study examined multitasking behaviors of drivers in environments that include large numbers of pedestrians and cyclists, using video and vehicle data from the second Strategic Highway Research Program (SHRP2). The study includes 15 sites in both Seattle, WA, and Tampa, FL, U.S., (nine pedestrian and six cyclist locations), including three marking and signal types for crosswalks and two types for bike treatments. A total of 1,458 SHRP2 traversals with time-series data and forward videos were extracted with face/dash videos for about 50% of these traversals. Forward video coding was conducted for all daytime traversals starting from one block before to one block after the selected site. Face/dash video was coded for all traversals with pedestrians or cyclists. A matched set of traversals without pedestrians or cyclists were also coded. The final data set included 458 traversals with coded data on multitasking behavior and the multimodal environment. Mixed-effect binary logistic regression models were used to examine the associations of pedestrian/cyclist presence and the facility type with drivers’ multitasking behavior. The findings show that the presence of pedestrians/cyclists and facility types could be related to drivers’ multitasking behavior. The findings can provide the foundation for future studies that examine safety for non-motorists with respect to infrastructure design, signage, and policies. There is also the potential to provide insights into assistive driving systems within automated vehicles, which are discussed in this paper.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:54:07Z
      DOI: 10.1177/03611981221110223
       
  • Telecommuting and Travel during COVID-19: An Exploratory Analysis across
           Different Population Geographies in the U.S.A.

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      Authors: Rezwana Rafiq, Michael G. McNally, Md Yusuf Sarwar Uddin
      Abstract: Transportation Research Record, Ahead of Print.
      This study explores the impact of the COVID-19 pandemic on telecommuting (working from home) and travel during the first year of the pandemic in the U.S.A. (from March 2020 to March 2021), with a particular focus on examining the variation in impact across different U.S. geographies. We divided 50 U.S. states into several clusters based on their geographic and telecommuting characteristics. Using K-means clustering, we identified four clusters comprising 6 small urban states, 8 large urban states, 18 urban–rural mixed states, and 17 rural states. Combining data from multiple sources, we observed that nearly one-third of the U.S. workforce worked from home during the pandemic, which was six times higher than the pre-pandemic period, and that these fractions varied across the clusters. More people worked from home in urban states compared with rural states. As well as telecommuting, we examined several activity travel trends across these clusters: reduction in the number of activity visits; changes in the number of trips and vehicle-miles traveled; and mode usage. Our analysis showed there was a greater reduction in the number of workplace and nonworkplace visits in urban states compared with rural states. The number of trips in all distance categories decreased except for long-distance trips, which increased during the summer and fall of 2020. The changes in overall mode usage frequency were similar across urban and rural states with a large drop in ride-hailing and transit use. This comprehensive study can provide a better understanding of the regional variation in the impact of the pandemic on telecommuting and travel, which can facilitate informed decision-making.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:51:45Z
      DOI: 10.1177/03611981221109182
       
  • Effects of Speed Reduction Marking Patterns on Simulated Driving Speed and
           Lane Position

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      Authors: Kentaro Iio, Hiroshi Nakai, Shinnosuke Usui
      Abstract: Transportation Research Record, Ahead of Print.
      Speed reduction markings have been installed on highways as perceptual countermeasures for speeding. However, little is known about the effects of the shape and interval of road markings on driving speed and lane position. In this paper, a driving simulator experiment and questionnaires were performed to explore the effects of speed reduction marking patterns on driving speed and standard deviation of lane position (SDLP), as well as drivers’ subjective feelings, mental workload, and visual attention. Thirty-nine participants drove on a simulated two-lane rural highway where speed reduction markings with different shapes and intervals were presented at horizontal curves. The pavement markings were associated with reduced throttle values and mean speed in advance of a horizontal curve. The marking shape did not affect participants’ speed choice or SDLP. A cognitive alerting effect of the speed reduction markings was dominant because the participants did not drive more slowly with the markings with converging intervals toward the traveling direction compared to those with a constant interval. A questionnaire on drivers’ attention reflected a potential use of road markings for drivers’ lane-position maintenance. Since less than 18 % of the participants noticed the convergence in marking intervals, speed reduction markings may also induce the perceptual illusion of acceleration.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:47:44Z
      DOI: 10.1177/03611981221108979
       
  • Content Analysis on Homelessness Issues at Airports by News Media Mining

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      Authors: Subasish Das, Javad J. C. Aman, M. Ashifur Rahman
      Abstract: Transportation Research Record, Ahead of Print.
      The number of homeless people at airports has increased in recent years. As airports are safe, transit-accessible, convenient, and climate-controlled facilities with food and amenities, these places are attractive to homeless people who need a safe and secure place to stay. The main struggle of airports in this regard is maintaining a balance between customers, who are mostly the traveling public, and dealing with homeless people delicately. Moreover, because of their poverty and insufficient or no access to healthcare, these people suffer from physical and mental issues. With the COVID-19 pandemic, this problem became more critical. Many news media outlets started to report on homelessness at airports. News-framing impacts have some contribution in the context of this issue. However, the impact of news coverage on “airport and homelessness” has not yet been studied. News-framing effects have been identified in the context of tourist destinations. Although many studies have explored homelessness and transit, this issue at airports has not been well studied. This study provides a brief overview of the issue of homelessness in the transportation domain, including transit and aviation. Additionally, this study collected news articles related to “airport and homelessness” (71 articles) both during the COVID-19 pandemic (March 1, 2020–July 21, 2021) and before the pandemic (before March 1, 2020). These news articles contain around 50,000 words. As the data is unsupervised in nature, a text network analysis was performed to determine the latent information from these textual contents. The findings of this study can shed some light on this scientifically unexplored but widely discussed issue.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:44:20Z
      DOI: 10.1177/03611981221108151
       
  • Trip Destination Prediction Based on Hidden Markov Model for Multi-Day
           Global Positioning System Travel Surveys

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      Authors: Zeqian Jin, Yanyan Chen, Chen Li, Zexin Jin
      Abstract: Transportation Research Record, Ahead of Print.
      Different individuals may move to different regions over time, but every individual has several fixed travel positions or unique travel patterns. Predicting destinations of each individual facilitates traffic demand management, which has great research value. Based on the data of multi-day GPS and passengers’ travel survey, a hidden Markov model (HMM) is employed in this paper to predict trip destination for weekdays and weekends. Firstly, the habit of destination choice among consecutive days and weeks can be discovered by identifying frequently visited destinations. Then, on the basis of Viterbi algorithm, this paper takes frequently visited destinations as one of the factors of the predicting process and constructs a travel destination prediction model based on HMM. Then, the HMM is calibrated with Baum-Welch algorithm and passengers’ travel destination characteristics are effectively analyzed. Finally, the HMM was compared with several classical algorithms. The results show that the place of residence and work are the most probable activities to occur and workplace dominates the activities when duration is longer than 8 h. Moreover, the results of frequently visited destinations identification indicate that the patterns of destination choice on weekdays and weekends are different from each other. In addition, the results show that the prediction accuracy on weekdays is higher than that on weekends and HMM outperforms other prevailing algorithms. The method proposed in this paper can be applied to real-time travel navigation applications, as well as supporting health and safety fields, such as epidemic prevention and control.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:42:00Z
      DOI: 10.1177/03611981221107919
       
  • Comparison of Vehicle-Based Crash Severity Metrics for Predicting Occupant
           Injury in Real-World Oblique Crashes

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      Authors: Morgan E. Dean, Douglas J. Gabauer, Luke E. Riexinger, Hampton C. Gabler
      Abstract: Transportation Research Record, Ahead of Print.
      The flail space model (FSM) is currently used in U.S. roadside hardware crash testing as a means of assessing occupant injury risk using observed vehicle kinematics data. European roadside hardware crash tests use an FSM variant along with a variant of the acceleration severity index (ASI). Although the FSM and ASI are currently used in roadside hardware testing, other vehicle-based crash severity metrics exist. Previous research has focused on examining the ability of these metrics to predict injury in frontal crashes. Despite the Manual for Assessing Safety Hardware prescribing a significant number of oblique crash tests, there has been little research on how well these metrics predict real-world oblique crash injury. This study compared the ability of six different vehicle-based metrics to predict occupant injury in oblique crashes: maximum delta-v, occupant impact velocity, ridedown acceleration, ASI, occupant load criterion, and vehicle pulse index. The crash severity metrics were calculated from real-world crash pulse data recorded by event data recorders. Oblique crashes from the National Automotive Sampling System Crashworthiness Data System were used to train logistic regression models that predict moderate to fatal injuries. The models were then compared on a dataset of oblique crashes from the Crash Investigation Sampling System. The results of this study confirmed that vehicle-based metrics provide a reasonable means of predicting real-world occupant injury risk in oblique crashes and suggest little difference between the investigated metrics. In addition to the vehicle-based metrics, belt use and vehicle damage location were found to influence injury risk.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:28:51Z
      DOI: 10.1177/03611981221107640
       
  • Estimating Average Daily Traffic on Low-Volume Roadways in Louisiana

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      Authors: Afia Serwaa Yeboah, Julius Codjoe, Raju Thapa
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic volume is an important parameter that agencies use as a decisive factor, especially at the time of design, maintenance, and operation of roadways. Thus, its correct estimation is very essential. There are already a few established proprietary products available on the market that can predict traffic volumes. In addition, past studies have used several mathematical models to predict traffic volume. Relatively fewer studies have been conducted on predicting traffic volume on low-volume roadways. To bridge the gap on the prediction of traffic volume for low- and high-volume roadways, this study seeks to find practical, cost-effective, and progressive methods of estimating and classifying traffic on low-volume rural roadways. Across the state of Louisiana, 395 locations with low traffic volumes of less than 500 vehicles per day were selected. Census tract data was used to extract demographic and socioeconomic information for each location. Two prediction models—linear regression and random forest regression models—were developed to predict traffic volumes on these low-volume roadways. The results showed that the linear regression model had the highest predictive accuracy, with R-square of 0.979 and root mean square error of 70.26 compared with the RMSE of 110.23 for the random forest regression model. Both models found functional class, land use, number of lanes, population density, median age, median household income, and household density significantly affecting the traffic volume.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:25:30Z
      DOI: 10.1177/03611981221106166
       
  • Are Damages to Remainder Parcels in Right-of-Way Acquisitions
           Stationary' A Spatial Analysis of Appraisal Report Data

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      Authors: Antora Mohsena Haque, Iman Mahdinia, A. Latif Patwary, Asad J. Khattak
      Abstract: Transportation Research Record, Ahead of Print.
      The acquisition of private property by right-of-way projects causes economic changes to the remainder of the property. An issue is the deviations in remainder parcel values between appraisers. Therefore, it is vital to understand whether appraisers in different locations consider and value the same or different factors. The objective of this paper is to identify spatial heterogeneity in the factors contributing to damages (as percentages) to remainders of affected parcels. Data on 507 appraisal reports for affected remainder parcels in Tennessee were collected and coded, creating a unique database with 23 variables. Applying a geographically weighted Gaussian regression model uncovered whether relationships were stationary over space. Results show that the local model outperforms the global model with an improved adjusted R2 of 0.81 compared with 0.77 in the global model. The most significant factors contributing to damage percentages that varied spatially are ratio of acquisition, adverse change in utility, major acquisition of landscape, highest and best use changed to assemblage, and major damage to access (landlocked). A larger area, corner parcels, and all categories of existing land use compared with residential use tend to lower the percentage damage to the remainder. Nashville is less severely affected by major damage to access, presumably for its high price of land. This study can assist appraisers in getting an early estimate of damage during partial takings. Property owners will have clarity about the impact of the eminent domain procedure on their land’s price.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:22:33Z
      DOI: 10.1177/03611981221105073
       
  • Rotated Mask Region-Based Convolutional Neural Network Detection for
           Parking Space Management System

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      Authors: Long Ngo Hoang Truong, Edward Clay, Omar E. Mora, Wen Cheng, Mankirat Singh, Xudong Jia
      Abstract: Transportation Research Record, Ahead of Print.
      Parking space management systems help organize and optimize available parking spaces for consumers, making the process of finding and using parking spaces more efficient. Current parking space management systems include manual recognition, the employment of magnetic and ultrasonic sensors, and, recently, computer vision (CV). One relatively new region-based convolutional neural network (R-CNN) model, Mask R-CNN, has shown promise in its ability to detect objects and has demonstrated superior performance over many other popular CV methods. Building on Mask R-CNN, an updated version, Rotated Mask R-CNN, which can generate bounding boxes the axes of which are rotated with respect to the image’s axis, was proposed to address the limitation of Mask R-CNN. Albeit with the documented theoretical benefits, the application of the rotated version is rare because of its recent invention. To this end, the study aims to detect vehicle instances in one parking lot using various Rotated Mask R-CNN models based on unmanned aircraft system collected images. Both average precision and average recall were utilized to assess the performance of the alternative models with different backbone and head networks. The results reveal the high accuracy level associated with Rotated Mask R-CNN in real-time detection of vehicles. In addition, the results indicate that the inference speed and total loss are highly correlated with head networks and training schedules.
      Citation: Transportation Research Record
      PubDate: 2022-07-26T09:21:13Z
      DOI: 10.1177/03611981221105066
       
  • Multiple-Drones-Multiple-Trucks Routing Problem for Disruption Assessment

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      Authors: Alireza Ermagun, Nazanin Tajik
      Abstract: Transportation Research Record, Ahead of Print.
      This study proposes a multiple-drones-multiple-trucks (MDMT) routing problem to assess infrastructure in the areas of disruption epicenters using multiple drones that operate in synchronicity with multiple trucks. Incorporating the trucks as moving depots enables drones to move across disrupted areas further from their flight range. The MDMT routing problem is formulated as mixed integer linear programming (MILP). This is an NP-Hard (Non-deterministic Polynomial-time Hardness) problem, which is solved by introducing a greedy heuristic algorithm to cluster the disrupted locations and plan each drone’s schedule within each disrupted cluster and between clusters. Both MILP and the greedy heuristic algorithm are tested for small to large test problems extracted from the Minneapolis–St. Paul freeway system with a grid-like network topology. Results show that disrupted locations’ spatial distribution affects the efficient number of active drones and trucks in the system. When direct travel between two nodes takes longer than other alternative paths, increasing the number of trucks accelerates the assessment procedure. Findings also indicate that the spatial distribution of disruptions clustered by the greedy heuristic algorithm is correlated with the routing time and affects drone scheduling. If clusters are scattered, each drone is typically assigned to one cluster for damage assessments. With a dense pocket of clusters in the network, however, a drone moves back and forth between multiple clusters. The proposed framework for disruption assessment provides insights on the optimal deployment of resources to collect information following a network disruption. Practitioners will also benefit from the findings to augment resource management.
      Citation: Transportation Research Record
      PubDate: 2022-07-25T11:16:54Z
      DOI: 10.1177/03611981221108378
       
  • Through Running and Integration of Federal Railroad Administration and
           Federal Transit Administration Regulated Passenger Trains: A Path Toward
           Mixing Intercity, Commuter, Metro, and Light Rail on the Same Tracks

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      Authors: Dennis Lytton
      Abstract: Transportation Research Record, Ahead of Print.
      U.S. rail transit (subways, metros, and light rail) and Federal Railroad Administration (FRA) regulated heavy rail (commuter, intercity and regional rail) operate completely separately in revenue service. This necessitates transfers between the modes at terminals. While not unique to the U.S.A., its version of this practice is extreme and prevents the development of robust seamless rail networks. Especially in the post-Covid environment, this leaves commuter rail in search of a mission and rail transit isolated from suburbs. This paper discusses the statutory regulatory scheme that divides the two modes in the U.S.A. It will analyze the justification for the segregation and its history. Such issues include potential collisions, weight, crashworthiness, electrification, signaling, loading gauge, platform height, and operating practices. This paper concludes that the regulatory barrier preventing an FRA-regulated train from going onto a non-FRA railroad are surmountable. Running through trains between the FRA-regulated system and the rail transit network would enhance regional networks. The “Karlsruhe model” in Germany and the through running of regional trains onto the Tokyo subway network are two prime examples. Recent technological advances—such as dual mode battery multiple units, robust signaling systems such as Communications Based Train Control and Positive Train Control, and advanced car body designs able to deal with different loading gauges—make through running more practical. With little or no new right-of-way, it is possible to create far more useful rail networks. Potential shared networks at the conceptual level are discussed for Los Angeles, Seattle, Washington, D.C., Dallas, and Sacramento.
      Citation: Transportation Research Record
      PubDate: 2022-07-25T11:15:14Z
      DOI: 10.1177/03611981221102153
       
  • Multiobjective Timetable Development Tool for Railway Strategic Planning
           in Norway

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      Authors: Nicola Coviello, Giorgio Medeossi, Andrew Nash, Thomas Nygreen, Paola Pellegrini, Joaquin Rodriguez
      Abstract: Transportation Research Record, Ahead of Print.
      Strategic planning is critical in helping railways develop optimal programs for improving their business by making service more attractive and efficient. Preparing a strategic plan requires comparing multiple alternatives and options, each requiring time-consuming planning, evaluation, and analysis. To improve this process Jernbanedirektoratet, Norway’s Railway Directorate, began a research project to develop a state-of-the-art railway timetable generation tool that could be integrated into the agency’s existing timetable-planning process. The new tool, called Automatic Timetabler with Multiple Objectives, is designed to transform conceptual passenger and freight service requirements into working timetables, while ensuring robustness and minimizing time losses. It is designed to bridge the gap between less detailed (macroscopic) models used in timetable development and detailed (microscopic) traffic simulation models. More specifically, it is a mesoscopic model, simplifying some infrastructure elements while using more detailed representations of others (e.g., using specific track allocations in stations). In practice, the tool quickly provides planners with many feasible and good timetables using high-level timetable requirement data. This ability is very useful for strategic planning because it enables planners to quickly evaluate alternative timetable concepts. This paper describes the new timetable generator tool, its development, and the results of a case study application.
      Citation: Transportation Research Record
      PubDate: 2022-07-25T11:13:14Z
      DOI: 10.1177/03611981221101392
       
  • Evaluating Crack Identification Performance of 3D Pavement Imaging Systems
           Using Portable High-Resolution 3D Scanning

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      Authors: Ryan Salameh, Pingzhou (Lucas) Yu, Zhongyu Yang, Yi-Chang (James) Tsai
      Abstract: Transportation Research Record, Ahead of Print.
      With the increasing adoption of three-dimensional (3D) pavement imaging systems by highway agencies for automated pavement condition assessment, coupled with the advent of diverse systems from different manufacturers, there is a need for standard procedures for the verification and certification of systems’ performance in regard to distress identification, especially for cracking that is a key contributor for triggering maintenance and rehabilitation activities. Although some procedures were adopted by agencies for a rough verification of cracking identification accuracy using ground reference established subjectively by trained raters, a more rigorous and objective method is needed to match the continuous advancement in the systems’ capabilities and data quality requirements. As portable high-resolution 3D scanning technologies have become commercially available, there is an opportunity to leverage them for establishing a more trustable ground reference for the data quality evaluation. This paper proposes a methodology that uses high-resolution 3D scanners to establish the ground reference for field pavement cracking distress to evaluate the crack identification capability of 3D pavement imaging systems in regard to crack quantity, position, and width. A case study was performed by scanning sample pavement cracking spots using “FARO Arm Quantum S” scanner to collect ground reference images and a 3D pavement imaging system installed on the “Georgia Tech Sensing Van” to collect test images to validate the feasibility of the proposed methodology.
      Citation: Transportation Research Record
      PubDate: 2022-07-25T11:11:23Z
      DOI: 10.1177/03611981221100239
       
  • Application of Balanced Mix Design Strategies to Missouri Dense-Graded
           Asphalt Mixtures

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      Authors: Hamed Majidifard, Punyaslok Rath, Behnam Jahangiri, William G. Buttlar
      Abstract: Transportation Research Record, Ahead of Print.
      This study focused on the improvement or redesign of dense-graded mixtures in Missouri by applying various strategies typified by a balanced mix design (BMD) approach. Briefly, the BMD approach involves designing mixtures using appropriate thresholds of mixture performance tests to control major distresses. In this study, two existing dense-graded mixtures from Missouri were adopted with 33% binder replacement by recycled asphalt pavement (RAP). Appropriate thresholds from three commonly used cracking tests, namely the disk-shaped compact tension test, or DC(T), the Illinois Flexibility Index Test (I-FIT), and the indirect tensile asphalt cracking test (IDEAL-CT), were paired with the Hamburg wheel track test (HWTT) toward the improvement or rebalancing of mixes designed before the availability or specified use of these tests. Preliminary test results showed that the existing mix designs did not satisfy the cracking thresholds adopted in this study, and thus the following modifications were made to the mixtures: (a) replacing the base binder with a softer grade binder, (b) adding a rejuvenator, and (c) adding ground tire rubber (either 10% or 20% by weight of base binder). According to the results, modification with rubber and softer binder was the most efficient strategy for improving and balancing DC(T) fracture energy and HWTT performance. On the other hand, the use of a softer binder or rejuvenator led to the best success in meeting semicircular bend (SCB) (I-FIT) and IDEAL-CT test requirements in balance with HWTT requirements.
      Citation: Transportation Research Record
      PubDate: 2022-07-23T08:33:09Z
      DOI: 10.1177/03611981221110219
       
  • Analysis of Washington State Department of Transportation Risks

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      Authors: Evan P. Dicks, Keith R. Molenaar
      Abstract: Transportation Research Record, Ahead of Print.
      Risk management is an important part of ensuring the successful delivery of major transportation projects. The first step in the risk management process is to identify the risks facing the project team so they can proactively complete the remaining steps: analyzing the severity; choosing how to respond; and controlling the level of risk throughout the lifecycle of the project. Although some state agencies have been practicing risk management for nearly two decades, little analysis of the risks identified during project development has been done. This study analyzes the risk registers pertaining to 51 major transportation projects undertaken by the Washington State Department of Transportation valued at approximately $7.7 billion to determine the distribution of risks among categories in the risk breakdown structure and find the most common risks in each category. The findings were then explored through interviews with industry professionals to gain insight into the results, add context, and illustrate the importance of identified risks. The results contribute to a better understanding of the risks facing transportation departments and lay the foundation for a more comprehensive risk identification step at the project level.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:26:23Z
      DOI: 10.1177/03611981221109599
       
  • Automation Preferences by Traffic Climate and Driver Skills in Two Samples
           From Countries with Different Levels of Traffic Safety

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      Authors: İbrahim Öztürk, Henriette Wallén Warner, Türker Özkan
      Abstract: Transportation Research Record, Ahead of Print.
      Automated systems present great capabilities with a wide range of options. In this respect, vehicle preferences and factors affecting these preferences are important for the future of automated systems. While automated systems offer varied features and improvements for drivers and general traffic safety, the relationship between drivers’ perceptions of traffic systems and driver skills have not been studied. The present study, therefore, focuses on country differences and the relationships between traffic climate and driver skills and their impact on the preferred level of vehicle automation for drivers in Turkey and Sweden. The study was conducted with 318 drivers (age: mean [M] = 22.41, standard deviation [SD] = 2.77) from Turkey and 312 drivers (age: M = 28.80, SD = 8.53) from Sweden in 2020. A questionnaire package asking for demographic information and preferred levels of vehicle automation—Traffic Climate Scale (TCS) and the Driver Skill Inventory (DSI)—was completed. A series of analyses of covariance (ANCOVA), hierarchical regression, and moderated moderation analyses were conducted. Drivers from Turkey preferred higher automation levels than drivers from Sweden. Drivers with higher perceived safety skills, with lower perceived perceptual-motor skills or perceiving the traffic system as more externally demanding preferred higher automation levels. Drivers’ automation preferences were affected by various individual and country-level factors. For the first time, drivers’ automation preferences were elaborated in relation to traffic climate and driver skills in two countries with different levels of traffic safety. Theoretical and practical implications of the findings are discussed in the light of the literature.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:25:04Z
      DOI: 10.1177/03611981221109593
       
  • Planning for Speed in the Public Space: The Case of Speed E-bikes in
           France, Belgium, and Switzerland

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      Authors: Hadrien Bajolle, Julie Chrétien, Marion Lagadic, Nicolas Louvet
      Abstract: Transportation Research Record, Ahead of Print.
      Speed e-bikes are electrically assisted pedal cycles with a speed of up to 45 km/h. Because of their high speed, these vehicles are not classified as bicycles in the European Union. However, their external aspect and their mode of propulsion—the user needs to pedal for the electric assistance to work—make them part of the symbolic universe of bicycles. This raises the following question: should these vehicles ride on cycle lanes, or on the road' The authors argue that answering this question implies understanding both how these vehicles are used, and how speed e-bike users perceive themselves. How do users experience their high-velocity bikes' Using qualitative interviews with speed e-bike users in France, Belgium, and Switzerland, this research offers novel data on the actual usage of this emerging mode of transport and what it represents symbolically to users. Results show that speed e-bike users consider themselves as cyclists and value the opportunity to ride on cycle lanes, whether this is allowed or not. However, they self-regulate their positioning on the road depending on their actual speed. When they want to accelerate, speed e-bike users tend to leave bike lanes to ensure their own safety as well as that of other cyclists. These results allow a case to be made for a speed-based regulation according to which riders could use different segments of the public space alternatively depending on their actual speed at a given moment.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:23:24Z
      DOI: 10.1177/03611981221109183
       
  • Agent-Based Model of Electric Vehicle Charging Demand for Long-Distance
           Driving in the State of Indiana

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      Authors: Donghui Chen, Kyubyung Kang, Dan Daehyun Koo, Cheng Peng, Konstantina Gkritza, Samuel Labi
      Abstract: Transportation Research Record, Ahead of Print.
      Historically the U.S. transportation system has been continuously improved to adopt new policies and technologies. The transportation vehicle energy transition from fossil fuels to electricity is promoted by policymakers and major automakers with an expectation of enhancing sustainability aspects such as fossil fuel consumption reduction, carbon emissions reduction, and lower operations and maintenance costs. However, the electrification of the existing transportation infrastructure system requires substantial upgrades to overcome two major concerns from ordinary drivers and the public. One is the driver’s range anxiety based on the current capability of the electric vehicle (EV) technologies. The other is the availability of EV charging stations near the planned route. To address these two issues, we introduce an agent-based simulation model to project the consequences of electrification in the Indiana state highway system. Specifically, the model is developed to monitor the status of long-distance EV trips between different regions. The multi-agent engine method guarantees the model can adapt to diverse scenarios and complex environments. The simulation experiment verifies that the proposed model can provide the expected outcomes, including the numerical data of electric energy demand and the geospatial information (as location coordinates) of failed trips. By performing a GIS-based analysis of the results, the derived geospatial data can help state transportation agencies determine where to deploy the charging facilities to satisfy the overall charging demand. The proposed simulation framework offers a novel and strategic way to resolve the challenges for EV charging-related research and projects.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:21:20Z
      DOI: 10.1177/03611981221107921
       
  • Integrated Simulation-Optimization Framework for Assessing the Impact of
           I-66 Dynamic Toll Pricing on Pavement Deterioration and Maintenance
           Decisions

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      Authors: Mirla Abi Aad, Montasir Abbas
      Abstract: Transportation Research Record, Ahead of Print.
      Tolled facilities are undoubtedly expected to alter the distribution of traffic across the transportation network. On the other hand, traffic volumes and loading have an impact on deteriorating pavement conditions. These traffic volumes are considered by Departments of Transportation (DOTs) while allocating annual budgets to maintain and rehabilitate roadway segments to sustain pavement performance targets. This research studies the specific site around I-66 inside the Beltway, which newly applied dynamic tolls during a.m. and p.m. peak hours. An integrated traffic-management/pavement-treatment framework was applied to address both the operational and the pavement performance of the network. Aimsun hybrid macro/meso dynamic user equilibrium experiments were used to simulate the network with the modified cost function taking care of the dynamic pricing along the I-66 tolled facility. An optimization was Python-coded into a Pyomo framework to specify the optimal maintenance and rehabilitation treatment plan, taking into account critical condition index (CCI) deterioration based on the traffic load distribution on the network. Finally, the results of the simulation showed the importance of having an optimized treatment schedule to achieve optimal pavement performance outcomes, with a difference in CCI index that could range all the way from 68 to 95.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:18:08Z
      DOI: 10.1177/03611981221105867
       
  • Solving Hub Location Problems With Profits Using Variable Neighborhood
           Search

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      Authors: Chunxiao Zhang, Xiaoqian Sun, Weibin Dai, Sebastian Wandelt
      Abstract: Transportation Research Record, Ahead of Print.
      This paper proposes variable neighborhood search (VNS) heuristics to solve hub network design problems with profits, which are uncapacitated hub location problems with incomplete hub networks. These problems seek to locate hub facilities, design hub networks, and assign spokes to hubs to maximize total profits. Six problems consisting of multiple allocation, single allocation, and r-allocation strategies, with optional direct connections, are solved. Unlike hub location problems that minimize costs satisfying all service demands, the operators can choose to satisfy a subset of travel demands to maximize profits. Although exact methods and heuristics are both commonly used for solving hub location problems, the problems with profits are mainly solved by the former. Therefore, VNS-based heuristics are proposed to solve six variants of hub location problems. The proposed heuristics have the same shaking procedure to escape local optima, while neighborhood structures in the improvement procedure depend on the allocation strategies. To evaluate the heuristics, this study also designs enhanced Benders decomposition methods which are exact algorithms. Computational experiments on existing benchmark datasets reveal an extraordinary performance of the heuristics. For the instances that can be solved by exact methods, the heuristics solve over 90% to optimality while being one to three orders of magnitude faster than the commercial solver CPLEX and Benders decomposition. Given the outstanding accuracy, with significantly reduced computational cost, the study contributes to the usage of heuristics for hub location problems with profits, especially for larger-scale networks, where exact methods cannot be executed because of limited computational resources.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:14:16Z
      DOI: 10.1177/03611981221105501
       
  • Spatial and Temporal Variability of Rail Transit Costs and Cost
           Effectiveness

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      Authors: Zakhary Mallett
      Abstract: Transportation Research Record, Ahead of Print.
      Previous research has evaluated the temporal variability of transit costs and shown that peak period service costs more to operate in both gross and net terms. However, research on spatial variability of transit costs, particulalry for modes other than bus transit, is quite limited. Using transit agency data on labor and train allocations in the United States, I develop an accounting cost model that allocates variable and semi-fixed capital costs to times of day and each link and station of two regional rapid rail transit networks—the San Francisco Bay Area Rapid Transit District (BART) and the Metropolitan Atlanta Rapid Transit Authority (MARTA)—to evaluate temporal and spatial variability of costs and average costs per rider. I find that costs per hour are highest, but average costs per rider are lowest, during weekday peak periods in both systems, and that costs are highest and costs per rider are lowest in the urban core area of the BART system, while there is no clear spatial pattern in the MARTA system.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:09:55Z
      DOI: 10.1177/03611981221104807
       
  • Development and Evaluation of Connected-Vehicle-Enabled Optimal Dynamic
           Path Planning with Bus Stops

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      Authors: Hao Yang, Kentaro Oguchi
      Abstract: Transportation Research Record, Ahead of Print.
      The frequent stops of transit buses significantly block lanes on roads and generate vehicle queues behind. The passenger cars traveling behind buses may be stuck in the queues and miss the green light in the downstream intersection. They will be very tempted to make lane changes to avoid the stopping vehicles efficiently. However, without knowing the information of bus stations and traffic signals, it is very difficult and dangerous for the queued vehicles to make lane changes at last minute. In this paper, an optimal dynamic path planning system will be developed to assist passenger cars avoid buses so as to improve their mobility on local roads. The system utilizes connected vehicles to receive stop information, including times, duration, and locations, of buses, and the signal timing information from intersections. The information is applied to predict the delay of connected vehicles caused by the buses and intersections. The system also estimate optimal paths for the target vehicles to make lane changes and overpass the buses and the downstream intersection to minimize its travel time delay. In this paper, both synthetic and realistic examples are designed with microscopic traffic simulations to evaluate the performance of the proposed system. The results indicate that the travel time delay for connected vehicles can be reduced by up to 35%. In addition, a sensitivity analysis of the market penetration rates of connected vehicles and demand levels is conducted to understand the benefits and reliability of the system under different stages of the connected environment.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:07:54Z
      DOI: 10.1177/03611981221100513
       
  • Extension of AASHTO Load-Spreading Method to Include the Full Benefits of
           Pavements for Reliable Load Rating of Buried Culverts

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      Authors: Michael G. Katona
      Abstract: Transportation Research Record, Ahead of Print.
      This paper develops a two-step procedure to extend the AASHTO Ad Hoc Method (AAM) for live-load spreading through soil to include the full benefits of pavement overlays. The two-step procedure is called AAMP-θ* (“P” for pavements), which combines the Fox two-layer elasticity solution for peak stress at the pavement–soil interface with the improved AAM-θ* theory for load spreading through soil. The AAMP-θ* procedure is applicable to all culvert analysis tools commonly used for Load and Resistance Factor Rating (LRFR) analysis ranging from simple frame models to sophisticated two-dimensional finite element model (2D-FEM) soil structure models. The AAMP-θ* procedure is rigorously and completely developed wherein all approximations are shown to be conservative so that the predicted benefits of pavements are trustworthy and not overstated. This is why the more accurate AAM-θ* load-spreading method is used instead of the simpler but unconservative AAM-30° method. Application of AAMP-θ* for LRFR load rating of buried culverts is described for simple frame models as well as 2D-FEM pavement–soil structure models. Lastly, the AAMP-θ* procedure is validated by comparing structural response predictions from 2D-FEM solutions with strain-gage measurements in a buried corrugated steel culvert loaded by a three-axle truck. One set of strain-gage measurements was made before, and another set of measurements was made after, asphalt pavement was installed. The correlation between field data and 2D-FEM/AAMP-θ* predictions is remarkable and underscores the bottom-line message that AAMP-θ* should be used when performing LRFR analysis on buried culverts to determine realistic rating factor values and avoid predicting false unsafe values.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:06:34Z
      DOI: 10.1177/03611981221096121
       
  • Multi-Vehicle Interactive Lane-Changing Velocity Change Model Based on
           Potential Energy Field

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      Authors: Yanli Ma, Biqing Yin, Ke Chen, Peng Zhang, Ching-yao Chan
      Abstract: Transportation Research Record, Ahead of Print.
      To quantitatively analyze velocity change in the interaction of multiple vehicles during the lane-changing process, this study defines the concepts of driving constraint region and multi-vehicle interaction region (MVIR) by analyzing the potential energy field. The attraction and repulsion effects of the target vehicle and surrounding vehicles are attributed to the area change in the overlapping parts of their MVIRs. A multi-vehicle interactive lane-changing method considering MVIR is proposed. A velocity change model of multi-vehicle interactive lane-changing is established to reveal the change regularity of velocity under multi-vehicle interactive lane-changing. The model parameters are calibrated using a P3-DT Beidou high-precision positioning direction finding receiver to collect vehicle coordinates and velocity. The error of vehicle velocity variation was less than 11%, which verified the validity of the velocity change model. The research results can guide drivers in completing the lane-changing process safely and quickly, and provide theoretical support for micro-traffic flow simulation, road traffic safety proactive prevention and control, multi-vehicle lane-changing rules, and multi-agent simulation platform construction.
      Citation: Transportation Research Record
      PubDate: 2022-07-22T10:04:41Z
      DOI: 10.1177/03611981221092383
       
  • Evaluating Safety Benefits of Vehicle-to-Everything Sensor Sharing on
           Rural Highways Using the Microscopic Simulation Model

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      Authors: Jose Gerardo Cazares, Ivan Damnjanovic
      Abstract: Transportation Research Record, Ahead of Print.
      Safety is a critical aspect of transportation design and operations. Practitioners utilize various references to ensure that roadways meet safety, operational, and sustainability requirements. Despite this, human error remains as a contributing factor toward unsafe driving behavior and potential crashes. Connected and autonomous vehicles (CAVs) have the potential to enhance traffic safety and operations. Although sensor perception ranges and capabilities pose challenges, the sharing of information via Vehicle-to-Everything (V2X) communication provides CAVs with a potential solution for overcoming sensor limitations. The objective of this study is to use the Simulation of Urban Mobility software to assess safety impacts when using V2X to share sensor-obtained roadway information with a CAV. To this end, this study proposes a novel method for simulating driver behavior that combines car following with consideration of the roadway’s geometric configuration. Several scenarios are utilized to observe the behavior of simulated drivers on a straight tangent approaching a sharp horizontal curve. This study evaluates driver performance using the measured values for longitudinal jerk, lateral jerk, and speed variance. The results of this study indicate that V2X sensor sharing can provide significant benefits to CAV performance and can reduce the safety risk. CAVs receiving sensor-obtained information behave in a manner more akin to their human-driven counterparts in comparison to those receiving basic safety messages. CAVs using sensor-obtained information maintain braking and lateral jerk values within safety thresholds. In addition, speed variance was at its lowest when CAVs utilized V2X sensor information.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:29:55Z
      DOI: 10.1177/03611981221110226
       
  • Modeling Road Pavement Rutting Using Artificial Neural Network and
           Conventional Measurements

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      Authors: Nawras Shatnawi, Mohammed Taleb Obaidat, Amjad Al-Sharideah
      Abstract: Transportation Research Record, Ahead of Print.
      Rutting leads hydroplaning, accidents, poor riding quality, and significant maintenance costs. This study assists the development of statistical and Artificial pavement rutting models. The proposed methodology is reliable, time-saving, cost-saving, and comfortable. The suggested technique to anticipate rutting considers traffic volumes, pavement, and geometrical parameters such as lane and shoulder widths. This research modeled 33 main highways' ruts. Most of these roads have serious de-stressing problems with rutted pavement. The developed rutting prediction models demonstrated a medium to high correlation between rut depth and independent variables including annual average daily traffic, truck fleet percentage, pavement thickness, and number of lanes. The correlation coefficients such as R2 were found to be moderate for most of the developed models. The linear models of rutting prediction were statistically significant, with R2 values averaging around 66%, whereas the logistic regression model was the best developed rutting model, with an R2 value of 67%, when all variables, including traffic, pavement, and geometry, were considered. Nonlinear models with an R2 value of 57% were used to get similar findings. The artificial neural network (ANN) has been used in this study to model rut depth with same independent variables and gave higher results with R2 value of 82%. The findings showed that an ANN outperformed regression modeling in predicting the depth of a rut.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:28:13Z
      DOI: 10.1177/03611981221110224
       
  • Did Operating Speeds During COVID-19 Result in More Fatal and Injury
           Crashes on Urban Freeways'

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      Authors: Subasish Das, Minh Le, Kay Fitzpatrick, Dayong Wu
      Abstract: Transportation Research Record, Ahead of Print.
      Impacts of the COVID-19 pandemic in the transportation arena included less traffic, higher speeds, and higher fatal and injury crash frequencies. Many news media reported on speeding and its impact. However, the majority of these reporting are based on partial or incomplete information. The current study aims to understand the association between speed and crash on the freeways of Dallas (Texas) by collecting data from the National Performance Management Research Dataset, the Texas Department of Transportation’s (TxDOT’s) roadway inventory, and TxDOT’s crash database for 2018–2020. The results show decreasing traffic volume, increasing average operating speed, and increasing fatal and severe crash frequencies per 100 million vehicle miles traveled during 2020 (April–November). This study developed 8-month- and daily-level safety prediction models for fatal and injury crashes. The 8-month-level dataset contains speed measures as an aggregate for the 8-month period. The daily-level database includes operating speeds and fatal and injury crashes at the daily level where segments experiencing fatal and injury crashes were temporally matched with the same segment with the same day of the week and with no fatal and injury crash occurrences. For the 8-month models, average operating speed and speed variability are positively associated with fatal and injury crash frequencies during the COVID period. This association was also found for daily-level models. The findings of this study can help transportation agencies in developing strategies (for example, posted speed limit reconsideration, additional enforcement at specific locations) for crash reduction.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:26:31Z
      DOI: 10.1177/03611981221109597
       
  • Emission and Flight Time Optimization Model for Aircraft Landing Problem

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      Authors: Ramazan Kursat Cecen, Tugba Saraç, Cem Cetek
      Abstract: Transportation Research Record, Ahead of Print.
      Aircraft landing is a critical operation for both terminal airspaces and airports. This study presents a multi-objective optimization model for this problem and aims to minimize the total flight time and emission value. A point merge system and vector maneuver techniques are implemented in aircraft to regulate air traffic. The model uses the augmented è-constraint method to reveal objective function relationships. To test the performance of the mathematical model, several realistic scenarios are generated and solved by GAMS/CPLEX solver. The algorithm can obtain Pareto-optimal solutions for each air traffic situation. In addition, noticeable reductions were observed in most of the Pareto-optimal solutions in emission values. The results showed that total emissions value and flight time were reduced up to 4.69% and 0.92%, respectively, compared with the first-come-first-served approach.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:22:49Z
      DOI: 10.1177/03611981221108398
       
  • Evaluation Model for a Port Hinterland Intermodal Freight Network
           Considering Environmental Impacts and Capacity Constraints

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      Authors: Yunqiang Wu, Rong Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      The huge demand for containerized cargo and the low market share of rail and inland waterway transport in the hinterland freight system in China are causing severe traffic congestion and pollution. Therefore, this paper focuses on innovative modeling to evaluate the effects of transport policies on the reduction of carbon emissions and the mode shift from road to low-carbon modes in a three-mode port hinterland freight network. The proposed model can capture the main characteristics of the freight system such as mode transfer at inland terminals, transport capacity and processing capacity constraints, flow-dependent link performance functions, and shippers’ perceptual error of generalized transport costs. The model assumes that shippers choose transport route, mode, and inland terminal at the same time in a user equilibrium manner, and that bundles of container flow passing competing ports follow the logit formulation. Computational results based on the freight network in the Yangtze River Economic Belt in China indicate that carbon tax, intermodal transport subsidy, and capacity expansion policies can reduce total carbon emissions and promote mode shift from road transport to rail and inland waterway transport, and policy packages show better network performance compared with a single policy type. It is noted that transport policies sometimes lead to the paradoxical phenomenon. Finally, sensitivity analyses are carried out on parameters of cost, time, carbon emissions, and error to test the robustness of the model.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:16:54Z
      DOI: 10.1177/03611981221107008
       
  • Extracting Highway Cross Slopes From Airborne and Mobile LiDAR Point
           Clouds

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      Authors: Alireza Shams, Wayne A. Sarasua, Brook T. Russell, William J. Davis, Christopher Post, Heidar Rastiveis, Afshin Famili, Leo Cassule
      Abstract: Transportation Research Record, Ahead of Print.
      Adequate water pavement surface drainage on highways is crucial in minimizing the potential of hydroplaning. Highway cross slope has a significant effect of draining water laterally from the pavement surface. Currently, field surveying techniques and other manual measurement methods are used to collect cross slope data on a limited basis in most states, despite these methods being labor intensive and exposing personnel to traffic. Furthermore, field surveying techniques cannot provide continuous data and can only be conducted at sample-based locations. This study conducted a technical evaluation of the effectiveness of airborne LiDAR (light detection and ranging) scanning and mobile terrestrial LiDAR scanning systems in measuring pavement cross slopes. Cross slope data were extracted from the LiDAR point cloud at five selected test sections using two different methods: (i) end-to-end method using elevations only from the pavement edge lines to generate the cross slope; and (ii) 0.2 ft interval point extraction along the cross-section and using a fitted linear regression line as the basis for the cross slope. Cross slopes were also measured at test section locations using conventional surveying methods and compared with LiDAR-extracted cross slopes. Results demonstrate that LiDAR methods are reliable for collecting accurate pavement cross slopes and should be considered for the purpose of cross slope verification on a braod scale such as statewide to address cross slope and pavement surface drainage issues proactively.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:14:55Z
      DOI: 10.1177/03611981221106482
       
  • Usability of Physical Internet Characteristics for Achieving More
           Sustainable Urban Freight Logistics: Barriers and Opportunities Revealed
           by Dominant Stakeholder Perspectives

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      Authors: J.H.R. van Duin, Kees B.H. van Son, Lori A. Tavasszy, Arjan J. van Binsbergen, Peter A. Kee, Edgar M. Huitema
      Abstract: Transportation Research Record, Ahead of Print.
      Urban freight logistics currently have to deal with multiple unsustainable conditions. Physical Internet (PI) characteristics show promise in making urban freight logistics more sustainable. This paper explores the opportunities and barriers to implementing this concept. Q-methodology is a method used to reveal different stakeholder perspectives. The results of the Q-methodology show four different perspectives out of which three display a positive attitude toward PI characteristics. One perspective is more moderate and states that a lot is possible already without any changes. One of the barriers is that there is no urgency to change. Further, most perspectives have a positive attitude toward regulations as long as they are nationally coordinated. Based on these results, policy recommendations are developed for individual and collaborative actions for stakeholders.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:13:04Z
      DOI: 10.1177/03611981221105071
       
  • Alternative Pickup Locations in Taxi-Sharing: A Feasibility Study

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      Authors: Sanaz Aliari, Ali Haghani
      Abstract: Transportation Research Record, Ahead of Print.
      Taxi-sharing is a known solution for reducing congestion and is more beneficial when the traveled miles, imposed by detours while serving additional passengers, are minimized. This study proposes incorporation of alternative meeting points in taxi-sharing routes to boost the efficiency of the system by eliminating unnecessary detours and improving the chances of passengers being matched. Unlike most ridesharing systems, in the proposed approach, passengers are not necessarily picked up or dropped off at their original location, but at a walkable distance from their origin. The proposed framework deals with practical challenges of including meeting points in a real-world high-demand taxi-sharing system with hundreds of requests per minute. This includes efficient selection of alternative pick up locations and incorporation of these alternatives into a novel mixed integer linear programming (MILP) formulation to find the optimal schedule. Using the 2015 New York City (NYC) yellow cab dataset, first, the potential benefits of introducing meeting points in Manhattan road network are demonstrated. Given the Nondeterministic Polynomial-time Hard (NP-hard) nature of the associated optimization problem, the problem is then broken down into smaller-sized problems forming clusters of passengers with high potential of sharing a ride. Then, the proposed MILP model is used to find the optimal route for each cluster, while selecting the best pickup point for each passenger. Testing on a sample of the NYC dataset, it is shown that the proposed methodology improves the efficiency of the taxi-sharing system by reducing the wait times by about 50% while considerably reducing total travel times and the number of vehicles used.
      Citation: Transportation Research Record
      PubDate: 2022-07-21T12:09:37Z
      DOI: 10.1177/03611981221104690
       
  • “It Is Our Problem!”: Strategies for Responding to
           Homelessness on Transit

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      Authors: Anastasia Loukaitou-Sideris, Jacob Wasserman, Hao Ding, Ryan Caro
      Abstract: Transportation Research Record, Ahead of Print.
      Buses, bus stops, trains, and train platforms represent sites of shelter for many of the over 500,000 Americans who are unhoused every night. This study seeks to understand how transit agencies are responding to them. Based on interviews with staff members and partners at 10 different transit agencies and on program performance data, where available, we provide detailed case studies of four sets of strategies taken in response to homelessness on transit systems: hub of services, mobile outreach, discounted fares, and transportation to shelters. We analyze each strategy’s scope, implementation, impact, challenges, and lessons learned. Reviewing these strategies, we note that they may differ depending on the context, need, and available resources. We find value in transit agencies fostering external partnerships with social service organizations and other municipal departments and keeping law enforcement distinct from routine homeless outreach. We also underline the key need for funding from other levels of government to allow transit operators to adopt, expand, and refine homelessness response programs.
      Citation: Transportation Research Record
      PubDate: 2022-07-20T12:02:40Z
      DOI: 10.1177/03611981221111156
       
  • Building Back Better: Transportation Recovery Challenges From the 2018
           Kaua`i Flooding Disaster

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      Authors: Karl Kim, Jason Chun, Eric Yamashita
      Abstract: Transportation Research Record, Ahead of Print.
      This study describes and analyzes the recovery of transportation systems damaged by flooding and landslides in 2018 on the island of Kaua’i, Hawai’i. Following describing the record-setting rainfall and massive landslides that closed the major highway connecting the North Shore communities with the rest of the island, the challenges of “building back better” are investigated. While there was an urgency to finish the roadway repairs as quickly as possible, there was also a need to reduce future risks from flooding and landslides. Strong leadership, coordination, communications, and resource sharing helped improve pre-existing traffic, congestion, parking, and accessibility concerns for residents and tourists. There are important lessons learned concerning the need for timely, accurate data and information. Mitigation and adaptation projects that go beyond simply replacing and repairing assets before the storm are also analyzed. Opportunities to utilize greener, nature-based, and context-sensitive design, engineering, and planning solutions to mitigate and adapt highways to climate-induced extreme events remain challenging even in a community known for scenic beauty, pristine natural areas, and rich cultural heritage. While the community-led efforts to implement improvements to the State park at the end of the road were exemplary, there are still ongoing challenges of increased climate threats and inflexible, limited systems for funding—not just in disaster recovery but also investments in community resilience.
      Citation: Transportation Research Record
      PubDate: 2022-07-20T11:59:38Z
      DOI: 10.1177/03611981221111150
       
  • Driver Psychology Latent Classes as Predictors of Traffic Incident
           Occurrence in Naturalistic Driving Study Data

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      Authors: Sadia Sharmin, John N. Ivan, Kerry L. Marsh, Alexandra Paxton, Andrew Tucker
      Abstract: Transportation Research Record, Ahead of Print.
      Crash risk depends on several factors, driver factors being the most significant of all. Previous studies have tended to use roadway and driver demographic information to explain crash risk, overlooking driver psychological characteristics, which are also important for crash risk estimation. Crash data from police reports are available only for reportable crashes and do not detail driver characteristics or comparable information on driving activities. Naturalistic driving studies (NDSs) offer unique opportunities to obtain information about driver attributes, behavior, or other precrash factors for predicting crash occurrence. This study estimated NDS event-oriented models to evaluate the interaction between driver attributes and roadway environmental factors for predicting safety critical events. A latent class clustering approach was used to uncover categories of drivers by psychological, perceptual, and cognitive characteristics, and by driving experience. The results revealed four driver types: risk-taker, careful-impaired, careful-unimpaired, and distractible. These types were incorporated in mixed-effects binary logistic models, with roadway, traffic, and environmental variables to estimate and predict crash risk. The models that included driver factors more successfully predicted crash risk than those without. Risk-takers showed the highest probability of being in crashes. However, careful-impaired drivers—those whose impairments made it difficult to identify the location of another vehicle, visualize missing information, who had difficulties with visual–spatial perception and executive functioning—posed a higher crash risk in roadway conditions such as snow, lack of lane markings, and certain traffic operating conditions. The results point to novel avenues for educational and behavioral interventions to improve road safety.
      Citation: Transportation Research Record
      PubDate: 2022-07-20T11:55:54Z
      DOI: 10.1177/03611981221108985
       
  • Characterizing Incident Responder Crashes Involving Move Over Law
           Violations

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      Authors: Grady Carrick, Sivaramakrishnan Srinivasan
      Abstract: Transportation Research Record, Ahead of Print.
      This research sought to understand secondary crashes involving incident responders in which a citation was issued for violation of Florida’s Move Over Law. From 2011 to 2020, there were 519 crashes involving a Move Over Law citation, for which the circumstances of the crashes had required a driver to slow or change lanes because of a stopped responder vehicle. The majority occurred during times other than daylight, and driver distraction and alcohol were notably present in the data. Alcohol increased crash and injury severity and the likelihood of injury. Law enforcement traffic stops were the most common precipitating activity, followed by previous crashes and vehicle disablements. Over two-thirds of crashes involved a law enforcement vehicle, the remainder comprised other responder vehicle types. A distribution of posted speed limits showed that more than half of move over violation crashes occurred on roadways with a posted speed of 45 mph or less. In 41 crashes, a pedestrian was struck, including 32 involving incident responders. In responder struck-by crashes, law enforcement officers, lack of high-visibility safety apparel, and operating on the traffic side of incident scenes were prominent. Local roadways comprised a significant number of struck-by crashes, but higher-speed roadways were more dangerous for towing operators and had higher incidence of serious injuries. The move over violation approach to filtering crash data for responder-involved incidents was valid, however, not every crash involving a responder resulted in a move over citation, so the approach was more representative of the responder-involved crash type than comprehensive.
      Citation: Transportation Research Record
      PubDate: 2022-07-20T11:54:46Z
      DOI: 10.1177/03611981221108385
       
  • Understanding Interest in Personal Ownership and Use of Autonomous
           Vehicles for Running Errands: An Exploration Using a Joint Model
           Incorporating Attitudinal Constructs

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      Authors: Irfan Batur, Katherine E. Asmussen, Aupal Mondal, Sara Khoeini, Tassio B. Magassy, Ram M. Pendyala, Chandra R. Bhat
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation has been experiencing disruptive forces in recent years. One key disruption is the development of autonomous vehicles (AVs) that will be capable of navigating roadways on their own without the need for human presence in the vehicle. In a utopian scenario, AVs may enter the transportation landscape and foster a more sustainable and livable ecosystem with shared autonomous electric vehicles (SAEV) serving mobility needs and eliminating the need for private ownership. In a more dystopian scenario, AVs would be personally owned by households—enabling people to live farther away from destinations, inducing additional travel, and roaming roadways with zero occupants. Concerned with the potential deleterious effects of having personal AVs running errands autonomously, this paper aims to shed light on the level of interest in sending AVs to run errands and how that variable affects the intent to own an AV. Using data from a survey conducted in 2019 in four automobile-oriented metropolitan regions in the United States, the relationship is explored through a joint model system estimated using the generalized heterogeneous data model (GHDM) methodology. Results show that even after accounting for socio-economic and demographic variables as well as latent attitudinal constructs, the level of interest in having AVs run errands has a positive and significant effect on AV ownership intent. The findings point to the need for policies that would steer the entry and use of AVs in the marketplace in ways that avoid a dystopian future.
      Citation: Transportation Research Record
      PubDate: 2022-07-19T02:24:36Z
      DOI: 10.1177/03611981221107643
       
  • Developing Car-Following Models for Winter Maintenance Operations
           Incorporating Machine Learning Methods

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      Authors: Ehsan Kamjoo, Ramin Saedi, Ali Zockaie, Mehrnaz Ghamami, Timothy Gates, Alireza Talebpour
      Abstract: Transportation Research Record, Ahead of Print.
      Car-following models have been explored thoroughly for different vehicle types, such as cars and trucks. Although snowplows can be classified as trucks, their unique physical and operational characteristics impose a distinct following behavior. Michigan Department of Transportation has recently tested a collision avoidance system to reduce rear-end crashes. The incorporated radar in this system provides valuable information, defining two objectives for this study: (1) investigating the impacts of snowplows on car-following behavior considering car–car and car–snowplow vehicle-type combinations; (2) exploring the effects of the proposed collision avoidance system on car-following behavior by comparing car-following models for collected data with and without such a system. Firstly, space and time headway analyses are performed to compare different vehicle-type combinations. Then, the Gipps’ model is calibrated, and two data-driven car-following models are trained incorporating support vector regression and a long short-term memory network. These models are calibrated/trained to evaluate the performance of models with and without considering the heterogeneity of driving behavior among road users. The results indicate that the presence of snowplows leads to statistically significant different car-following models. Besides, it is shown that the collision avoidance system slightly improves the behavior of the following vehicles, which is not statistically significant. Also, it is concluded that considering driving behavior heterogeneity leads to more realistic prediction of the following behavior, compared to assuming homogeneous driving styles in traffic. Finally, the performances of the three developed car-following models are compared. Developing specific models for winter maintenance operations is an early step toward developing microsimulation models for adverse weather conditions.
      Citation: Transportation Research Record
      PubDate: 2022-07-19T02:21:36Z
      DOI: 10.1177/03611981221107630
       
  • Adopting a Bi-level Optimization Method for the Freight Transportation
           Problem: A Multi-objective Programming Approach

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      Authors: Shahab Rahiminia, Amir Mehrabi, Mohsen Pourseyed Aghaee, Amin Jamili
      Abstract: Transportation Research Record, Ahead of Print.
      Nowadays, various companies find it a crucial task to elevate their distribution system efficiency to survive in what is an intensely competitive environment. Freight transportation via road systems may not always be a practical option for the shipper because of financial, social, and environmental aspects. So, in addition to the road system, the shipper can benefit greatly from the rail system. Thus, taking advantage of different transportation modes can help shippers to tackle, to some extent, arising issues. In this paper, we aim at investigating a freight transportation network including rail and road transportation modes in which the shipper’s choice affects the decisions deeply. Given that this problem as a bi-level programming model, the rail operator acts as a leader and the shipper is treated as a follower. Once the rail operator reveals the rail transportation price, an appropriate response is received from the shipper and this pattern is repeated until an equilibrium is achieved. From the sustainability view, a multi-objective mixed-integer programming model is developed to simulate their interactions considering a sustainable triple bottom line. Employing the Karush–Kuhn–Tucker approach, we converted the formulated bi-level programming model into a single one. Several numerical examples are investigated to evaluate the validity of the developed model and approaches. Different in-depth sensitivity analyses are carried out and the impacts of several factors, such as line and train capacity, on the rail operator and shipper’s decisions are investigated. The results reveal that the rail operator could increase their market share by a wise long-term investment in the rail infrastructure.
      Citation: Transportation Research Record
      PubDate: 2022-07-19T02:18:22Z
      DOI: 10.1177/03611981221107627
       
  • Results From a Campus Population Survey of Near Misses, Crashes, and Falls
           While E-Scooting, Walking, and Bicycling

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      Authors: Rebecca L. Sanders, Trisalyn A. Nelson
      Abstract: Transportation Research Record, Ahead of Print.
      Dockless e-scooters were used for 86 million trips in the United States in 2019, indicating great potential as a new transportation mode in U.S. cities and on university campuses. Yet, little is known about how e-scooter users interact with people walking, bicycling, and driving. Although several studies have examined e-scooter injuries reported in hospital data, transportation-related near misses are chronically understudied in general, and even more so for this newer mode of transportation. In this paper we present the results of an online survey of 1,256 university staff (22% response rate) in Tempe, AZ. Using a single population, we compared the prevalence of self-reported incidents and injuries among those who use e-scooters, walk, and bicycle. Our results indicated a higher percentage of respondents reported incidents associated with walking (25%) than e-scooting (11%) or bicycling (9%), but e-scooter users were the most likely to report incidents resulting in a crash. E-scooter users were also more likely to report issues related to pavement, equipment, or losing control, whereas people walking and bicycling were more likely to report conflicts with other roadway users. Our findings suggest important areas for policy and infrastructure innovation, including prioritizing separate space for e-scooters to mitigate conflicts with pedestrians, and continuing to evolve rider training and speed governance to help keep e-scooter users safe. Other findings underscore the importance of measuring near misses to develop a comprehensive picture of transportation safety.
      Citation: Transportation Research Record
      PubDate: 2022-07-18T06:14:43Z
      DOI: 10.1177/03611981221107010
       
  • Assessing Safety Performance on Urban and Suburban Roadways of Lower
           Functional Classification: An Evaluation of Minor Arterial and Collector
           Roadway Segments

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      Authors: Meghna Chakraborty, Timothy J. Gates
      Abstract: Transportation Research Record, Ahead of Print.
      Previous research of urban roadway safety performance has generally focused on roadways of high functional classifications, such as principal arterials. However, roadways with lower functional classifications, including minor arterials and collectors, typically possess characteristics that differ from those of higher roadway classes. Therefore, assumptions made on the general effect of the predictor variables from typical safety performance functions may not apply to lower roadway classes. To address these knowledge gaps, a safety performance evaluation of urban/suburban minor arterial and collector roadway segments was performed using traffic and roadway data along with 8 years of crash data from 189 mi of two-lane urban and suburban roadways in Washtenaw County, MI. Mixed-effects negative binomial models with a segment-specific random intercept were developed for minor arterial and collector road segments, considering total-, fatal and injury-, and property damage only crashes. In general, minor arterial roadways showed greater crash occurrence compared with collector roads. Posted speed limit had a significant positive association with crash frequency, and this effect increased when the speed limit exceeded 40 mph. The effect of speed limit was stronger on minor arterial segments and for fatal and injury crashes. Additionally, driveway density was found to have a significant effect on safety performance, which was stronger for commercial/industrial driveways compared with residential driveways and for collector roads compared with minor arterials, particularly when considering residential driveways. On-street parking was associated with lower crash occurrence, with a stronger effect on collector roadways, most likely because of greater parking turnover when compared with minor arterials.
      Citation: Transportation Research Record
      PubDate: 2022-07-18T06:12:24Z
      DOI: 10.1177/03611981221106480
       
  • Last-Mile Strategies for Urban Freight Delivery: A Systematic Review

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      Authors: Torrey Lyons, Noreen C. McDonald
      Abstract: Transportation Research Record, Ahead of Print.
      Trends in retail and e-commerce have led to greater demand for urban freight and last-mile deliveries. This is a concern for urban planners, parcel carriers, and citizens as they struggle to cope with the demands that increased freight flows create in an urban context. This topic has also seen a corresponding expansion in the academic literature as researchers propose solutions to the problem of last-mile delivery. We conduct a systematic review of the literature to identify innovative last-mile delivery strategies as well as ways that those strategies are evaluated by researchers. This study will help academics as they consider directing future research as well as practitioners as they assess how delivery patterns may shift. We identify 22 last-mile delivery strategies and group them into four categories: innovative vehicles, urban goods consolidation, technological and routing advances in city logistics, and emerging planning tools and policies. We find that urban consolidation centers, freight bicycles, and collaborative logistics are the strategies that have received the most attention to date. Analyses of these options has focused on operational, environmental, social, and economic impacts with operational efficiency, emissions, and congestion being the three evaluation criteria discussed most in the literature. We propose that safety has not been adequately considered as a means for evaluating last-mile delivery strategies and should be a higher-priority focus for urban freight research going forward.
      Citation: Transportation Research Record
      PubDate: 2022-07-18T06:10:04Z
      DOI: 10.1177/03611981221103596
       
  • Performance of Risk-Based Estimating for Capital Projects

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      Authors: Mark Gabel, Mark Sujka, Zachary W. Davis, Alan E. Keizur
      Abstract: Transportation Research Record, Ahead of Print.
      Risk-based approaches to capital project cost and schedule estimation have been adopted by many public agencies in recent years. Such techniques are intended to produce more reliable cost and schedule forecasts, enhance risk management, and improve project management and project delivery outcomes. However, limited research has been conducted in relation to the true effectiveness of such risk assessment programs. The impact of process change must be measured to appraise the value differential. Where a high-value proposition exists, it is the duty of public servants to disseminate the opportunity to the industry for the good of the public. This paper measures and compares the cost and schedule performance of 28 highway projects completed in Washington state between 2016 and 2019. Results from a group of projects that deployed a formal cost/schedule risk assessment with risk management (referred here as “CRA”) are compared with a second group that did not. The data reveal that projects that completed a CRA were more likely to be completed with a total contract cost at or below the engineer’s estimate, experience lower post-award cost and schedule growth, and experience more predictable outcomes than those projects that did not deploy a CRA. Additional observed benefits of a CRA process are also discussed.
      Citation: Transportation Research Record
      PubDate: 2022-07-18T05:54:03Z
      DOI: 10.1177/03611981221103238
       
  • Influence of Transit Station Proximity on Demographic Change Including
           Displacement and Gentrification with Implications for Transit and Land Use
           Planning After the COVID-19 Pandemic

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      Authors: Arthur C. Nelson, Robert Hibberd
      Abstract: Transportation Research Record, Ahead of Print.
      A key purpose of fixed-route transit systems is to attract people and households to live near transit stations. There is very little research into the extent to which this occurs, however. This article is the first to apply a consistent methodology using census data to evaluate the extent to which people and households are attracted to transit stations. Using census American Community Survey 5-year sample data applied to 30 metropolitan areas for 2013 and 2019—a period between the Great Recession and the COVID-19 pandemic—we found that nearly all people and households were attracted to transit stations located within the first 100 m with very little occurring in the rest of the “½-mi circle” (about 800 m). With the exception of streetcar systems that serve mostly downtowns, we found that most of the change in residents in the first 100 m involved minority persons, which is somewhat inconsistent with displacement and gentrification expectations. Also, with the exception of streetcar systems, large to very large shares of all new households with children were attracted to the first 100 m from transit stations, which was again somewhat inconsistent with expectations. We use analysis to suggest implications for the post COVID-19 pandemic period. Although major cities have lost population as households have moved mostly into nearby suburbs, recent trends combined with data from preference surveys suggest that future demand for transit station proximity may be higher than before the pandemic. We conclude with long-term implications for transit and land use planning.
      Citation: Transportation Research Record
      PubDate: 2022-07-18T05:51:47Z
      DOI: 10.1177/03611981221105872
       
  • Surveying Disadvantaged Children’s Traffic Safety Education in a
           Comparison between Paper and Electronic Methods: A Case Example for the
           Expanded Use of Educational Technology

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      Authors: Aleksandar Trifunović, Svetlana Čičević, Dalibor Pešić, Andreja Samčović, Vladan Marković
      Abstract: Transportation Research Record, Ahead of Print.
      New generations of children are growing up amidst rapidly developing modern technology that completely changes how educational content is presented, how children’s skills and attitudes are developing, and the way children are tested on what they know, including with regard to traffic safety education. In contrast to participants from many existing studies for which data have been collected via personal computer devices, children who are disadvantaged have minimal experience of the use of hi-tech tablet computers. Thus, in this experiment, we aimed to compare the results of a test on traffic safety taken by socially disadvantaged children in two different formats: a traditional method (paper form); and a contemporary method (tablet computer). We found these children to be more engaged with touch screens than with paper tests and more naturally interested in interacting with tablet computers, which resulted in their achieving better results in tests in the field of traffic safety education. We discussed the benefits of conducting studies in which children use tablet computers for assessing their behavior in traffic situations, while highlighting the methodological challenges of this approach and potential solutions.
      Citation: Transportation Research Record
      PubDate: 2022-07-16T12:35:10Z
      DOI: 10.1177/03611981221106477
       
  • Exploratory Analysis of Mobility of Care in Montreal, Canada

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      Authors: Léa Ravensbergen, Juliette Fournier, Ahmed El-Geneidy
      Abstract: Transportation Research Record, Ahead of Print.
      “Mobility of care” refers to the daily travel required to complete care labor such as travel to the grocery store, or to escort children. Though past research has examined the distribution of individual types of household-serving travel, little research to date, especially in the North American context, has examined mobility of care which combines all travel required to fulfill a household’s care needs. This paper presents the results of an exploratory analysis of mobility of care drawing on the 2018 Montreal Origin–Destination Survey. Specifically, this paper explores who completes this type of travel and how this mobility is completed. Findings indicate that mobility of care comprises 28% of adults’ daily mobility. Further, women are found to complete more of this type of travel than men, especially women from lower-income households. The presence of children in the household further widens this gendered gap, though the number of children present does not alter this trend greatly. Mobility of care trips are shorter on average than other types of travel and are frequently completed as part of a trip-chain. Further, car use and walking are more frequently used for mobility of care than other types of travel, while the opposite is true for public transport and cycling. The use of public transport for mobility of care trips is greater amongst women than men, especially those living in lower-income households. Taken together, results highlight the importance for practitioners to explicitly address mobility of care in transport planning, and particularly in public transport planning.
      Citation: Transportation Research Record
      PubDate: 2022-07-16T12:16:31Z
      DOI: 10.1177/03611981221105070
       
  • Investigation Into Collection Variability of Surface Crack Data for
           Network-Level Asphalt Pavement Evaluation

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      Authors: Xiaoyang Jia, Mark Woods, Ulises Martinez, Di Zhu, Baoshan Huang
      Abstract: Transportation Research Record, Ahead of Print.
      Surface cracking is a major type of pavement distress that is of interest to pavement engineers. Cracks are generally categorized in relation to patterns, orientations, and locations. Each type of crack is associated with one or more failure modes of pavements. Accurately detecting and rating surface cracks is crucial in pavement condition surveying. Currently, many State Highway Agencies employ automated survey methods to collect pavement condition data at network level. As network-level pavement evaluation is based on a single run, the traditional way of characterizing data variation based on multiple runs is no longer valid. Therefore, it is necessary to introduce a new method to evaluate the variability of pavement condition data at the network level. In this study, the variability of network-level surface crack data was evaluated by means of network-level sample parallel tests. The parallel test was conducted from 2018 to 2020 using two vehicles equipped with identical automated survey systems which consisted of a 3-D imaging system and automated distress identification system. A matrix-based method was proposed to evaluate the variations of crack data obtained from two testing vehicles. Crack data investigated in this study included fatigue cracks, longitudinal wheel-path and non-wheel-path cracks, and transverse cracks. Results indicated that change of testing speed could potentially influence the variation of automated crack data. The variations between severity levels for fatigue cracking were higher than other types of cracks. The variation of crack data decreased with the increase of reporting intervals.
      Citation: Transportation Research Record
      PubDate: 2022-07-16T12:10:51Z
      DOI: 10.1177/03611981221105069
       
  • Traffic Event Detection from Consumer Vehicle Sensor Data: An Autonomous
           Vehicle Study

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      Authors: Zhenhua Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Traffic event detection from vehicles’ on-board sensors can detect the road information and improve traffic management and safety. Current sensor-based traffic event detection is mainly based on probe vehicles, test vehicles, or other designated vehicles, which is costly and cannot be deployed on a large scale. With the fast development of on-board equipment, data collection from consumer vehicle sensors is becoming popular and can cover a large geographic scale with almost no equipment or labor cost. However, there are very few studies of the data features and potential for application. This paper presents a pipeline for employing consumer vehicle sensors to detect roadworks. The unique data features and deficiencies of the consumer vehicle sensor are discussed and summarized. A clustering method is employed to distinguish the roadwork sites. A route builder method is proposed to reconstruct the routes of the roadworks and to extract the corresponding start and end locations. Compared with ground truth, roadworks detection from consumer vehicle sensors can cover up to 86% of the roadworks on freeways and over 40% of the roadworks on non-freeway roads. The average offset errors are 4.7% on freeways, and 24.9% on non-freeway roads. Compared with point-based roadworks detection from “ViaMichelin Traffic information,” the results from consumer vehicle sensors achieved a matching ratio of nearly 90% and were advantageous in extracting the roadworks route information. This study proves the possibility of employing consumer vehicle sensors for route-based traffic event detection and provides insights for countering uneven distribution and trajectory truncation issues related to privacy protection.
      Citation: Transportation Research Record
      PubDate: 2022-07-16T12:08:13Z
      DOI: 10.1177/03611981221105065
       
  • Comparative Analysis of the Influence of Transport Modes on Tourism:
           High-Speed Rail or Air' City-Level Evidence from China

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      Authors: Jieping Chen, Na Yan, Shanlang Lin, Shijun Chen
      Abstract: Transportation Research Record, Ahead of Print.
      This paper quantifies and compares the influence of two modes of transport on tourism, namely, high-speed rail (HSR) and air travel, and explores their substitute or complementary relationships. To facilitate the analysis, we apply data from 291 prefectural administrative cities in China from 2003 to 2019. Empirical tests show that both modes have a significant positive influence on the development of tourism. Moreover, the effect of air travel is greater than that of HSR. The findings remain robust and reliable with changes in the explanatory variables and sample size, and with regard to time window adjustment and endogeneity. Further, we explore the differences in the strength of the influences and find the two modes exhibit various effects according to regional heterogeneity. Finally, we investigate the joint effect of the two modes and find the existence of a substitute relationship. However, the relationship changes to complementary in specific areas. The findings of this paper provide important implications for the development of the regional tourism economy and the spatial layout of the transport infrastructure.
      Citation: Transportation Research Record
      PubDate: 2022-07-15T06:03:36Z
      DOI: 10.1177/03611981221106476
       
  • Early Age Monitoring of High Cement Replacement Mixtures for Pavement

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      Authors: Aniruddha Baral, Jeffery R. Roesler
      Abstract: Transportation Research Record, Ahead of Print.
      Decarbonization of concrete will require a combination of alternative binding materials and higher cement replacement rate with supplementary cementitious materials. Developing tools and methods that help engineers evaluate the properties of early age concrete pavement, such as setting time and strength gain, will be necessary to adopt new concrete mixes. Two concrete pavement test sections were constructed, a high early strength concrete mix with 25% (control) and 40% replacement of cement with fly ash (HVFAC), along with monitoring of the concrete’s setting time, saw-cut timing, and strength gain. A non-contact ultrasonic device was used to estimate setting time through measuring leaky Rayleigh wave energy transmission. The laboratory setting time of the control and HVFAC mix measured with the non-contact device was 5.5 h and 15 h, respectively, and agreed with measured isothermal calorimetry results. Further calorimeter tests showed that adding an accelerating admixture or replacing part of the cement with nano-limestone decreased the HVFAC setting time up to 4.4 h. The field setting time of the control mixture with the non-contact device measured 4.2 h, which was shorter than the laboratory estimate. Based only on the experience of construction personnel, saw-cutting for these mixtures was initiated too early and caused significant joint raveling, reinforcing the importance of in situ setting time measurement. The maturity method was successfully implemented with embedded wireless temperature sensors that rapidly and easily estimated the in-place compressive strength and improved opening time determination for concrete with high cement replacement levels, which are sensitive to the volume of supplementary cementitious materials, admixtures, and ambient conditions.
      Citation: Transportation Research Record
      PubDate: 2022-07-15T06:01:10Z
      DOI: 10.1177/03611981221105500
       
  • Role of High-Speed Roads and Vehicle Ownership on Traffic Fatalities in
           India

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      Authors: Ruchika Agarwala, Vinod Vasudevan
      Abstract: Transportation Research Record, Ahead of Print.
      The development of higher quality road infrastructure in developing countries improves ride quality but also enables greater driving speeds. Similarly, a growing middle class allows more people to afford personal vehicles but increases the number of drivers on the road. Improved mobility has historically been associated with economic growth, and its impact on traffic safety has been explored in high-income countries. However, the behavior of road users and vehicle ownership characteristics in middle-income countries are substantively different than those in high-income countries. This study explores the relationship between mobility and traffic safety at a region-wide level in India, a middle-income country. The results show that increasing lengths of National Highways are associated with an improvement in traffic safety while increasing lengths of all other types of roads and total number of motor vehicles are both associated with a deterioration in traffic safety. This study shows that safe roadway infrastructure has a huge role in enhancing overall safety even in countries with high vehicle heterogeneity, lack of driver education, and weak enforcement. This study’s contribution should guide decision-makers in other middle-income countries to invest in traffic safety measures alongside any investments in higher quality road infrastructure.
      Citation: Transportation Research Record
      PubDate: 2022-07-15T01:20:12Z
      DOI: 10.1177/03611981221104803
       
  • Does Taxing TNC Trips Discourage Solo Riders and Increase the Demand for
           Ride Pooling' A Case Study of Chicago Using Interrupted Time Series
           and Bayesian Hierarchical Modeling

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      Authors: Hoseb Abkarian, Sharika Hegde, Hani S Mahmassani
      Abstract: Transportation Research Record, Ahead of Print.
      This paper studies the tax intervention applied to transportation network company (TNC) trips starting on January 6, 2020 in the City of Chicago. An interrupted time series (ITS) with an autoregressive integrated moving average (ARIMA) methodology is employed to infer the causal impact of the intervention on the percentage of shared trips and the counts of shared and private trips. Analysis is conducted at a community area level, either as pickup or drop-off. The results show a significant but small increase in the share of shared trips as well as the count of shared trips, specifically on weekends because of the intervention. Private trips, on the other hand, are found to have decreased on the weekdays, but potentially increased on the weekends. A Bayesian hierarchical model is then employed to combine information across community areas, examine a posteriori if there are significant spatial differences, and estimate the common treatment effect. The analysis suggests minimal spatial differences across community areas. The common treatment effect on weekdays ($1.75 tax difference) is a 3.78 percentage point increase in the share of shared trips, a 27% increase in the count of shared trips, and a 12% decrease in the count of private trips (at an approximate base of 10% market share of shared trips). Thus, the intervention likely shifted demand toward pooled rides, reducing congestion caused by TNCs. However, there is little evidence that this shift is sufficient to offset or reverse the systematic trend of declining use of shared rides.
      Citation: Transportation Research Record
      PubDate: 2022-07-15T01:19:16Z
      DOI: 10.1177/03611981221098665
       
  • Incident Duration Time Prediction Using Supervised Topic Modeling Method

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      Authors: Jihyun Park, Joyoung Lee, Branislav Dimitrijevic
      Abstract: Transportation Research Record, Ahead of Print.
      Accurate prediction of the duration of traffic incidents is one of the most prominent prerequisites for effective implementation of proactive traffic incident management strategies. This paper presents a novel method for immediate prediction of traffic incident duration using an emerging supervised topic modeling. The proposed method employs natural language processing techniques for semantic text analysis of the text-based incident traffic incident dataset. The model applies the labeled latent Dirichlet allocation approach, and it is trained using 1,466 incident records collected by the Korea Expressway Corporation from 2016 to 2019. For training purposes, the proposed method divides the incidents into two groups based on the incident duration: incidents shorter than 2 h and incidents lasting 2 h or longer, following the incident management guidelines of the Federal Highway Administration Manual on Uniform Traffic Control Devices for Streets and Highways (2009). The model is tested with randomly selected incident records that were not used for the model training. The results demonstrate overall prediction accuracies of approximately 74% for incidents lasting up to 2 h, and 82% for incidents lasting 2 h or longer.
      Citation: Transportation Research Record
      PubDate: 2022-07-14T10:26:01Z
      DOI: 10.1177/03611981221106786
       
  • Machine-Learning Approaches to Identify Travel Modes Using
           Smartphone-Assisted Survey and Map Application Programming Interface

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      Authors: Yilin Sun, Yinan Dong, E. Owen D. Waygood, Hamed Naseri, Yuhao Jiang, Yijie Chen
      Abstract: Transportation Research Record, Ahead of Print.
      Travel mode choice prediction is essential for transportation planning and travel demand prediction. One of the conventional travel survey methods is collecting data over landline telephones, which lacks efficiency because of financial and time resource needs. In this regard, smartphone-assisted travel surveys can be applied to overcome the mentioned deficiencies. Smartphone-assisted travel surveys allow respondents to record GPS data, travel purpose, and travel mode via an application, simplifying the survey process. With various sensors equipped, the precision of data is ensured. Based on the survey results, varied approaches have been seen to travel mode identification. For this study, a travel survey was conducted in Hangzhou, China, supported by the smartphone application TraceRecord integrated with online mapping services. Several steps were undertaken to recognize different kinds of travel modes. First, preprocessing was adopted to screen out defective logs. With the employment of A-Map Application Programming Interface (API), trajectory segmentation was substantially boosted. Then, separately, features related to velocity, acceleration, and heading were extracted from the survey data. To achieve better accuracy and efficacy, two classification algorithms—support vector machine (SVM) and gradient boosting decision tree (GBDT)—were applied to model the travel mode identification problem. Compared with the SVM, GBDT produced a higher prediction accuracy of 90.16%. Further analysis was implemented based on the results of the GBDT model, and velocity-related features contributed the most to the identification problem. The study explores the possibility of applying travel mode recognition in real-world conditions and discusses further mining of the survey data.
      Citation: Transportation Research Record
      PubDate: 2022-07-14T10:23:19Z
      DOI: 10.1177/03611981221106483
       
  • Evaluating the Impacts of Freeway Speed Limit Increases on Various Speed
           Measures: Comparisons Between Spot-Speed, Permanent Traffic Recorder, and
           Probe Vehicle Data

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      Authors: Nischal Gupta, Md Shakir Mahmud, Hisham Jashami, Peter T. Savolainen, Timothy J. Gates
      Abstract: Transportation Research Record, Ahead of Print.
      The state of Michigan increased the maximum speed limit for passenger cars from 70 to 75 mph on 614 mi of rural freeways between May and June of 2017. The maximum speed limit for trucks was also increased from 60 to 65 mph on all freeways where the passenger car limit was 65 mph or above. This study examined the effects of these changes on traffic speed characteristics. Speed data were collected before the speed limit increases were introduced, as well as at several intervals afterward using three different data sources. Free-flow speed data were collected from spot-speed studies using light detection and ranging (LIDAR) devices whereas aggregate-level traffic speed data were obtained from both permanent traffic recorder (PTR) stations, as well as from probe vehicle data. These data were integrated with associated roadway and traffic characteristics and the impacts of the speed limit changes were evaluated using seemingly unrelated regression equations, which provide insights into how these increases affected the 15th, 50th, and 85th percentile speeds, as well as the standard deviation in speeds. Regardless of data source, the results consistently showed increases in each speed metric. However, the magnitude of these increases varied from 1.1 to 3.2 mph depending on the specific metric and data source. Marginal changes in speeds were observed at sites where speed limits were not changed, suggesting limited spillover effect. Several site-specific characteristics were also correlated with speed selection, with these effects being less pronounced when considering free-flow and probe vehicle data as compared to PTR.
      Citation: Transportation Research Record
      PubDate: 2022-07-14T10:20:59Z
      DOI: 10.1177/03611981221106481
       
  • Evaluation of Enforcement and Messaging Campaign Focused on Reducing Cell
           Phone-Related Distracted Driving

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      Authors: Nusayba Megat-Johari, Megat-Usamah Megat-Johari, Peter Savolainen, Timothy J. Gates
      Abstract: Transportation Research Record, Ahead of Print.
      Cellular telephone use has increased significantly in the United States as 97% of residents now own some type of cell phone. The ubiquity of cell phones has introduced concerns with respect to traffic safety as cell phone-related distractions have been shown to affect driving ability and increase crash risk. Various countermeasures have been implemented to address this issue, including public outreach campaigns and targeted enforcement activities. However, the efficacy of such strategies has been the subject of limited research. This paper examines cell phone use rates in consideration of enforcement activities in conjunction with targeted safety messages on roadside dynamic message signs. Two phases of enforcement were conducted in two urbanized areas of Michigan. Data were collected before, during, and after the enforcement period. A two-way random effects logistic regression model was estimated, and the results showed that cell phone use rates were lower during and, particularly, after the enforcement activities were conducted. Use rates were also found to vary based on age, gender, and race, allowing for the identification of target groups for public awareness and outreach campaigns. Use rates were also lower at freeway exit ramps as compared to signalized and stop-controlled surface street intersections. Lastly, cell phone-specific safety messages were associated with lower use rates compared with other message types, suggesting a potential synergistic effect.
      Citation: Transportation Research Record
      PubDate: 2022-07-14T10:14:51Z
      DOI: 10.1177/03611981221106163
       
  • Demonstration of Mechanics-Based Track Geometry Deterioration Models

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      Authors: Stephen Wilk, Hugh B. Thompson, Theodore R. Sussmann, Dinqing Li, Yudhisthir Paudel
      Abstract: Transportation Research Record, Ahead of Print.
      The Transportation Technology Center, Inc. (TTCI) is working to build on and extend existing mechanics-based track geometry deterioration forecasting models to support improved safety and reliability of ballasted tracks. This paper demonstrates how the railway track lifecycle model (RTLM) ballast model performs against field data and makes recommendations for improvement. Overall, the demonstration showed the mechanics-based model matches the general field behavior and its variations well, and it also identified potential improvements. The field data reinforced ballast fouling index (BFI) as a key factor in track geometry degradation. Additional factors that can cause variation in the BFI–track geometry degradation relationship were also identified, along with proposed curves that are easier to fit with field data. Linear track geometry degradation, with reference to mid-chord offset measurement with tonnage, fits the field data better than a logarithmic curve, which, historically, has been used to fit settlement as a function of tonnage. Using these improvements to the model, future work will focus on making the model as flexible as possible. This means identifying and incorporating key variables, in addition to BFI, that affect track geometry deterioration and allowing the model to either give general projections in situations with little historical data or become site-specific to a particular track section by incorporating historic data.
      Citation: Transportation Research Record
      PubDate: 2022-07-14T10:11:30Z
      DOI: 10.1177/03611981221104682
       
  • Construction and Live Load Behavior of a Skewed Steel I-Girder Bridge

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      Authors: Siang Zhou, Larry A. Fahnestock, James M. LaFave, Ricardo Dorado
      Abstract: Transportation Research Record, Ahead of Print.
      As part of a long-term monitoring project, a two-span continuous steel I-girder bridge (skewed 41° with seat-type abutments) was instrumented and evaluated in the field during construction and after the bridge was in service. This paper discusses data from when the first stage (of a three-stage sequence) was constructed and initially opened to traffic. Girders and cross-frames were instrumented with strain gauges using a data acquisition system with a high sampling frequency (up to 20 Hz). Data collection began just before deck placement, and a series of live load tests was then conducted on the completed Stage I (half of the bridge) using a loaded truck. Three-dimensional finite element analyses were carried out to provide enhanced understanding of bridge behavior. Good agreement was observed between the numerical simulation results and the field monitoring data for both deck placement and live load testing. A slight inconsistency between numerical simulation and field measurement data at one girder section and an adjacent cross-frame indicated an unexpected local site condition, which was confirmed through a targeted field inspection. Live load distribution factors used during design conservatively overestimate bridge girder strong-axis bending response under live load (by around 50%). Maximum flange lateral bending stresses of 6.3 MPa (0.9 kips per square inch [ksi]) and 2.5 MPa (0.4 ksi) were observed during deck placement and truck tests, respectively. In addition, out-of-plane response of 10.6 MPa (1.5 ksi) was observed at girder web plates under concrete dead load.
      Citation: Transportation Research Record
      PubDate: 2022-07-14T10:09:14Z
      DOI: 10.1177/03611981221105276
       
  • Identifying Risks in the Cruise Supply Chain: An Empirical Study in
           Shanghai, China

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      Authors: Jingen Zhou, Shu-Ling (Peggy) Chen, Wenming (Wendy) Shi
      Abstract: Transportation Research Record, Ahead of Print.
      The increased frequency and severe consequences of risks in the cruise industry have attracted increasing attention from both academics and practitioners, especially after the 2012 ‘Costa Concordia’ disaster and the 2020 coronavirus outbreak on the ‘Diamond Princess’. Although the literature on risk studies associated with the cruise industry and supply-chain risk management is growing, the extant literature lacks a study to view risks in the cruise industry associated with the supply chain. This paper addresses this gap by reviewing the literature on risks related to the cruise industry and general supply-chain risks to create a framework of cruise supply-chain risks. Then, semi-structured interviews were conducted to validate the identified risks and explore potential undiscovered risks. A novel risk typology of the cruise supply chain was then built based on the literature review and the empirical study. This includes macro risks, safety, security, and health risks, information risks, and supply risks. This framework can be applied for the purpose of systematically identifying the risks and their impacts on the cruise supply chain. This paper contributes to the development of a comprehensive cruise supply-chain risk classification with a detailed explanation of each risk in the cruise supply chain, which can be used by stakeholders in the cruise industry to identify and measure the impact of each risk. Additionally, this paper provides avenues for future research by scholars interested in assessing and managing cruise supply-chain risks.
      Citation: Transportation Research Record
      PubDate: 2022-07-13T11:36:16Z
      DOI: 10.1177/03611981221105859
       
  • Short-Term Safety Performance Functions for Freeways Including High
           Occupancy Vehicle Lanes

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      Authors: Jingwan Fu, Mohamed Abdel-Aty, Nada Mahmoud, Yina Wu
      Abstract: Transportation Research Record, Ahead of Print.
      Short-term safety performance functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions and bridge the gap between annual crash frequency prediction and real-time crash likelihood prediction. The proposed short-term SPFs consider the temporal variation in crashes and traffic characteristics. This study contributes to the literature by developing short-term SPFs at hourly aggregation levels for freeways that include high-occupancy vehicle (HOV) lanes using loop detector data from Arizona State, U.S. Variables that capture the short-term traffic turbulence were prepared and considered in the developed SPFs. Further, this study investigated the factors contributing to crash frequency using three different ways to represent the hourly traffic: annual average hourly traffic, annual average weekday hourly traffic (AAWDHT), and annual average weekday peak hour traffic (AAWDPT). The results indicated that the traffic volume variable was found to be significant in all the developed models. Further, the variables that represent the speed and occupancy differences between HOV lanes and general-purpose lanes were positively associated with crash frequency. This study proposed a series of variables that reflect the short-term traffic turbulence. The models comparison results showed an improvement in [math] from 2.4% to 12.8% when including the proposed variables. Further, the results indicated that the Poisson-lognormal approach outperformed the basic negative binomial model in both AAWDHT, and AAWDPT models. Further, the AAWDPT model was found to have the best performance in relation to Akaike information criterion and [math].
      Citation: Transportation Research Record
      PubDate: 2022-07-13T11:33:36Z
      DOI: 10.1177/03611981221105275
       
  • The Role of Walkability, Socio-Economic and Parental Cognitive
           Characteristics in Long Walking Journeys to School

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      Authors: Mohsen Fallah Zavareh, Mehdi Barati, AmirReza Mamdoohi, Michael Abraham
      Abstract: Transportation Research Record, Ahead of Print.
      Previous research has identified the socio-economic, built environment, and psychological barriers to children walking to school. Long journeys, however, have been identified as a crucial constraint reducing the likelihood of walking to school. Determining a threshold to distinguish between long and short journeys, the present study sought to examine whether the contribution of the factors reducing walking to school differs between short and long journeys. Questionnaires were distributed among 7 to 12-year-old children in a neighborhood of Tehran (n = 272) to be completed by parents. In addition, instead of walkability at the neighborhood level that considers walkability within a radial buffer from home or destination, we measured walkability along the school routes. ROC (Receiver Operating Characteristic) curve analysis found a threshold of 12.5 min to differentiate between long and short journeys. Walking journeys longer or shorter than the threshold were classified to be long or short, respectively. We developed two separate models, one to estimate walking for all (including long and short) journeys; and the other for only long journeys. Compared with all journeys, long walking journeys were explained by more built-environment variables. Parental attitudes toward walking were also significant in long walking journeys. However, analysis of interaction effects between walking time to school and the study variables confirmed that among all variables examined, the contribution of only environmental factors of crosswalks, walkways, and physically permeable frontages was significantly different between long and short walking journeys. Policy implications of the findings have been discussed.
      Citation: Transportation Research Record
      PubDate: 2022-07-13T11:31:36Z
      DOI: 10.1177/03611981221104805
       
  • Research on Differential Pricing and Train Operation Decisions for Railway
           Cargo Transportation Under Competitive Conditions

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      Authors: Jin Zeng, Xiaoqing Zhang, Kehuai Jin
      Abstract: Transportation Research Record, Ahead of Print.
      Railway freight operations aim not only to market themselves aggressively to capture the market in a competitive environment but also to achieve refined management. The operational decisions chosen by carriers can have a significant impact on the revenue across freight services. Nowadays, various forms of transported products, train make-up, and schedules are developed from the perspective of production convenience, with less consideration of shippers’ needs for the time utility, frequency, and tariffs of transportation services. This paper investigates a joint optimization approach to railroad operation planning that combines meeting the transport demand preferences of different shippers in a competitive environment. Considering the heterogeneity of shippers’ transportation demands and the competitive environment with freight trucking, a new bi-level programming model is proposed that incorporates pricing decisions and operational planning policies, such as car blocking, train routing, and make-up. An exact solution for this model is developed by adding valid inequalities to the mixed-integer formula and the experiment is conducted with data from bulk coal cargo transportation of the S Railway Bureau Group Corp. A simple transportation network is presented, and the calculation results of the pricing decisions that maximize the profit in each operation decision in this network are reported.
      Citation: Transportation Research Record
      PubDate: 2022-07-13T11:28:56Z
      DOI: 10.1177/03611981221102147
       
  • Identifying the Adaptability of Different Control Types Based on Delay and
           Capacity for Isolated Intersection

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      Authors: Ali Danesh, Wanjing Ma, Ling Wang
      Abstract: Transportation Research Record, Ahead of Print.
      In urban road networks, intersections are the main bottlenecks. Selecting an appropriate intersection control type can significantly improve the performance of an isolated intersection. Therefore, this paper offers recommendations for selecting the most efficient control type among two-way stop control, signalized intersection (SIG), roundabout (RB), and signalized roundabout (SIGRB) based on capacity and delay. The procedure to calculate delay and capacity is taken from the Highway Capacity Manual 6th edition (2016), or developed separately if needed. Two flow patterns are assumed: fixed and time-varying demand. For fixed demand, the results show that SIGRB outperforms other control types both in capacity and delay at higher demand levels. It was also observed that increase in left-turn ratio increases the delay and decreases the capacity of all control types while its impact on SIGRB was the least. Considering time-varying demand, traffic volume fluctuates over the 5-h period of the analysis. It was found that using both RB and SIGRB together creates significantly less delay compared with the other options. Additionally, using RB provides less variability in delay when there is fluctuation in demand. The major finding of this research is that RB and SIGRB have potential benefits for delay in conditions of (i) high traffic volume, (ii) high left-turn ratio, and (iii) demand fluctuation. Furthermore, it is suggested that SIG should be used if the left-turn ratio is relatively low. The results of this study could help decision-makers to choose the best control type for an isolated intersection under various traffic conditions.
      Citation: Transportation Research Record
      PubDate: 2022-07-13T11:27:20Z
      DOI: 10.1177/03611981221099915
       
  • Analysis of Factors Affecting the Sustainable Success of Airlines During
           the COVID-19 Pandemic

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      Authors: Kasım Kiraci, Gökhan Tanriverdi, Ercan Akan
      Abstract: Transportation Research Record, Ahead of Print.
      The COVID-19 pandemic increased the risk of financial distress, bankruptcy, or both, in the airline industry. Whether airlines can survive or not during and/or after the pandemic is closely related to their decisions and actions which will enable their success by increasing their resilience. In crisis periods such as COVID-19, the decisions taken by airlines are strategically important for achieving sustainable success. Thus, it is critical to understand which factors are more important for airlines to shape their actions and make correct decisions. This paper investigates the sustainable success factors on which airlines should focus to provide resilience during the COVID-19 pandemic crisis. It provides a robust model using the interval type-2 fuzzy analytic hierarchy process (IT2FAHP) and interval type-2 fuzzy Decision Making Trial and Evaluation Laboratory (IT2FDEMATEL) to identify and rank success factors. The findings indicate that financial and operational factors are extremely important to ensure resilience for airlines. In addition, the results of the study reveal that operational factors and information sharing factors have an impact on financial factors and customer satisfaction.
      Citation: Transportation Research Record
      PubDate: 2022-07-13T05:11:55Z
      DOI: 10.1177/03611981221104462
       
  • Application of Unmanned Aerial Technologies for Inspecting Pavement and
           Bridge Infrastructure Assets Conditions

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      Authors: Surya Sarat Chandra Congress, Anand J. Puppala, Md Ashrafuzzaman Khan, Nripojyoti Biswas, Prince Kumar
      Abstract: Transportation Research Record, Ahead of Print.
      Infrastructure in the U.S.A. was graded with a “C–” in the 2021 ASCE report card. Frequent monitoring of infrastructure assets is key to ensuring the serviceability of the assets and safety of public users. Advancements in aerial technologies, compact sensors, computer processing, and image analysis software have given rise to various engineering applications of sensor-mounted unmanned aerial vehicle (UAV) platforms. Several contactless sensors are being mounted on UAVs to conduct a comprehensive assessment of infrastructure conditions compared to a qualitative visual examination by an experienced inspector. Many transportation agencies in the U.S.A. have been using UAVs for applications ranging from the research stage to regular inspection activities. These applications are mainly focused on inspecting infrastructure assets such as pavements, bridges, substructures, railways, and other assets. The current research discussed the approaches followed to conduct aerial condition monitoring of transportation infrastructure assets using optical sensors mounted on UAVs. Qualitative and quantitative inspections of pavement, bridge, and substructure infrastructure case studies were performed. Pavement distress extents were measured in three dimensions and a 360° inspection of bridges was conducted by accessing hard-to-reach areas. Scaled views of the four sides of a bridge were developed and the challenges in data collection and processing were outlined. Further, a localized inspection was also demonstrated to show the feasibility of using photogrammetry for remote condition assessments post-disaster/emergency. Overall, the rich visualization, safety, flexibility, and ease of handling offered by these technologies are expected to transform the method of conducting infrastructure performance monitoring inspections in the future.
      Citation: Transportation Research Record
      PubDate: 2022-07-12T05:26:54Z
      DOI: 10.1177/03611981221105273
       
  • Safety Impact of Automated Speed Camera Enforcement: Empirical Findings
           Based on Chicago’s Speed Cameras

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      Authors: Nebiyou Tilahun
      Abstract: Transportation Research Record, Ahead of Print.
      Speeding was a factor in over a quarter of crash fatalities annually in the U.S. from 2009 to 2018. In some cities, automated speed camera enforcement is being used to curb speeding and improve roadway safety in instrumented areas. This paper reviews the effectiveness of automated speed cameras and some of the considerations informing the public debate around them in the United States. It then employs data from the City of Chicago, Illinois and the empirical Bayes approach to examine how effective speed cameras have been at reducing injury crashes and fatalities. Chicago installed most of its currently operating speed cameras in the 2013 to 2014 period. From 2015 to 2017, we estimate a 12% reduction in fatal and injury crashes across treated locations included in our analysis. Fatality and severe injury crashes declined by 15%. Some treated sites did not see the expected safety benefits, however. Recommendations to improve efficacy are made.
      Citation: Transportation Research Record
      PubDate: 2022-07-11T12:35:51Z
      DOI: 10.1177/03611981221104808
       
  • Pavement Marking Practices, Standards, Applications, and Retroreflectivity

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      Authors: Uttara Roy, Omar Albatayneh, Khaled Ksaibati
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement markings are important elements of roadway networks and help guide traffic flow in an orderly manner. In recent years, transportation agencies are facing challenges to manage pavement markings because of the advent of new vehicle technologies. Existing pavement marking standards were developed for serving human road users but they may not be effective for both human drivers and machine vision systems. Therefore, the National Committee on Uniform Traffic Control Devices suggested amendments to the current pavement marking standards. Therefore, it is necessary to explore pavement marking practices for a variety of states. With this aim, the Wyoming Technology Transfer Center conducted an online survey as part of a comprehensive research project on developing pavement marking management plans for the Wyoming Department of Transportation. The main objective of the survey is to document the various state Departments of Transportation (DOTs’) pavement marking management plans, how the plans are developed, strategies for pavement marking data collection, and pavement marking retroreflectivity. The survey has 31 questions dealing with pavement marking striping, pavement marking data collection, pavement marking retroreflectivity, and a few miscellaneous questions. There are 29 DOTs who responded to the survey. This paper summarizes the responses from the survey on evaluating pavement marking management practices at a national level.
      Citation: Transportation Research Record
      PubDate: 2022-07-11T12:33:54Z
      DOI: 10.1177/03611981221107920
       
  • Longitudinal Study of the COVID-19 Pandemic Impact on Activity Travel
           Using Connected Vehicle Data

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      Authors: Sisinnio Concas, Achilleas Kourtellis, Vishal Kummetha, Mohsen Kamrani, Maysam Rabbani, Omkar Dokur
      Abstract: Transportation Research Record, Ahead of Print.
      The COVID-19 pandemic has had a once-in-a-century impact on human life on the planet. As of June 30, 2021, the Centers for Disease Control and Prevention reports that more than 194 million people have been infected and more than 4 million have succumbed. Our goal is to study and analyze the potential for structural long-term changes in activity travel behavior caused by this global disruption. We rely on a longitudinal panel of 308 drivers who provided high-frequency connected vehicle data (once per second up to 10 times per second) covering more than one year before the onset of the pandemic (January 2019) and one year and three months after the national state of emergency was first declared in the U.S.A. (June 2021). We combine this dataset with land-use data to produce a comprehensive activity travel database for studying the impact on personal vehicle trips made and their spatial dispersion, time spent traveling and on activities, time spent at home, and vehicle miles traveled (VMT). We find that the number of trips made to reach work and nonwork activities is reverting to pre-COVID-19 trends. Travel time and VMT in personal vehicles are steadily increasing as well. At this pace, granting the absence of new variants warranting travel restrictions, these activity travel measures are expected to reach pre-COVID-19 levels by the second half of 2021 or early 2022. The spatial dispersion of activities, after increasing during the opening phases, seems to stabilize at levels comparable with those experienced before the state of emergency was declared.
      Citation: Transportation Research Record
      PubDate: 2022-07-09T06:55:04Z
      DOI: 10.1177/03611981221107006
       
  • Planning-Level Crash Prediction Models in Southern California

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      Authors: Ian Hamilton, Scott Himes, Yang Wang, Riana Tanzen, Yuying Zhou
      Abstract: Transportation Research Record, Ahead of Print.
      Macro- or planning-level crash prediction models (CPMs) differ from traditional predictive safety models in that they predict crashes for a geographic area rather than at a specific segment or intersection site. These models lend themselves to traditional planning-level activities, particularly when the exact design or dimensions of a road facility have yet to be determined. This paper describes a research effort conducted by the Southern California Association of Governments (SCAG) to develop a series of models to support safety analyses as part of the agency’s quantitative planning approach. The models were found to support SCAG’s planning at two scales: one series of models addressed annual performance measure target setting for the entire SCAG region by predicting severe injuries per year (i.e., annual fatalities, serious injuries, and nonmotorized fatalities and serious injuries), and a second series of models predicted crashes that contribute to agencywide performance measures, but at a community- or neighborhood level. These latter community models predicted crashes at a scale that will assist in evaluating scenarios for future projects or local community growth. The models developed through this research were consistent with previous research and display a promising ability to accurately predict crashes and injuries that are key benchmarks for regional safety planning.
      Citation: Transportation Research Record
      PubDate: 2022-07-09T06:51:44Z
      DOI: 10.1177/03611981221106788
       
  • Crash Modification Functions for Rural Skewed Intersections

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      Authors: Anthony Ingle, Timothy J. Gates
      Abstract: Transportation Research Record, Ahead of Print.
      This study evaluated the safety influence of intersection skew angle on rural two-lane, two-way facilities by calibrating crash modification factors. Ten years of crash history among federal aid and nonfederal aid highways was used to develop crash modification functions at three-leg and four-leg stop-controlled intersections. Skew angle was investigated as a parameter in the safety performance functions models both as a continuous variable, with observed values ranging from zero to 80°, and categorized into ranges. A few transformations of the skew parameter were considered, such as the flexible-form model having skew interaction with annual average daily traffic, and a Hoerl curve. Both three-leg and four-leg intersections exhibited an initially increasing trend of crash rates followed by a decreasing trend as the skew angle increased. A categorical model was found to best describe the skew relationship using discrete skew angle ranges. Among three-leg intersections, a skew angle between 17° and 27° experienced 22% more crashes than perpendicular intersections. However, more highly skewed three-leg intersections exhibited a decreasing relationship to increasing skew angle. Among four-leg intersections, a skew angle between 17° and 27° experienced 40% more crashes, whereas intersections with a skew angle greater than 45° did not have significantly different crash occurrence than perpendicular intersections. The implications of assuming a monotonic increasing relationship to skew angle are challenged as a result of this study.
      Citation: Transportation Research Record
      PubDate: 2022-07-09T06:43:20Z
      DOI: 10.1177/03611981221105272
       
  • Development and Evaluation of Performance Measures for Capacity
           Utilization of Traffic Signals

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      Authors: Nemanja Dobrota, Aleksandar Stevanovic, Nikola Mitrovic, Suhaib Alshayeb, Milan Zlatkovic
      Abstract: Transportation Research Record, Ahead of Print.
      Emerging high-resolution datasets allow for developing traffic signal performance measures (TSPMs) which can provide a better understanding of traffic signal operations. One of the specific objectives of signal operations is related to the measurement of capacity utilization. A fundamental measure for capacity utilization is the “degree of saturation” (DS), and it has both volume-based and occupancy-based formulations. The former is known as “volume over capacity ratio” (V/C), whereas the latter is known as “green occupancy ratio” (GOR). When V/C is used to observe capacity utilization, it is not known whether the capacity is utilized from interrupted flow, free flow, or a combination of two. Similarly, the amount of time in the cycle utilized by volume (characterized with the first and last vehicle arrival time) is not revealed within V/C. On the other hand, GOR“overlooks” cases when a high number of vehicles travel without stopping or fewer vehicles depart the signal with significant startup delays and similar. In addition, because of a lack of scientific attention, GOR has often been misinterpreted as some similar, yet different TSPM. Therefore, if only V/C or GOR are used to monitor signal performance, the understanding of utilized capacity will be incomplete or misleading. This study proposes three TSPMs: “queued volume in volume to capacity ratio” (QViV/C), “cycle utilization” (CLU), and “volume-occupancy capacity utilization” (VOCU) to overcome the limitations of V/C and GOR. Also, by evaluating existing occupancy-based measures, it was found that they can be used to estimate capacity utilization, including oversaturated conditions.
      Citation: Transportation Research Record
      PubDate: 2022-07-09T05:14:27Z
      DOI: 10.1177/03611981221104460
       
  • Comparing the Efficiency and Effectiveness of Different Train-Following
           Control Algorithms for Fleets of Heavy-Haul Freight Trains under Moving
           Blocks

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      Authors: Geordie Roscoe, C. Tyler Dick
      Abstract: Transportation Research Record, Ahead of Print.
      With the nationwide installation of positive train control (PTC) technology recently completed, freight railroads are searching for ways to leverage the technology to improve their operations beyond increasing safety. One possibility is reducing train headways through developing and installing a PTC-based moving-block system, thus increasing the capacity of railroad mainlines without adding costly track infrastructure. Though operating trains at shorter headways can theoretically increase line capacity, effectively controlling following trains becomes more difficult compared with a fixed-block system, requiring a fast-reacting train crew or control algorithm that effectively minimizes headway and fuel consumption while attenuating all fluctuations in lead-train speed. Otherwise, rapid changes in throttle and brake settings may be required, reducing following-train fuel efficiency, generating in-train forces, and diminishing the expected capacity gains from shortened headways. This research, sponsored by the Federal Railroad Administration, aims to better understand how closely following freight trains respond to different throttle- and brake-control algorithms. Using insights from connected automobile and truck platooning technology, the project team developed several train-following control algorithms, analyzed their stability, and simulated their performance with fleets of freight trains subject to different speed profiles. While moving-block systems do require additional train spacing beyond the minimum safe braking distance to account for train control actions, effective train-following control algorithms can minimize this distance. Also, the developed control laws exhibit a trade-off between minimizing train headway and fuel consumption, potentially allowing railway operators to choose an optimal balance.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T09:47:43Z
      DOI: 10.1177/03611981221099917
       
  • Finite Element Modeling of FHWA-Accelerated Loading Facility Test Sections
           With Fatigue Damage Using a Nonlinear Viscoelastic Cohesive Zone
           Integrated With Gaussian Damage Evolution

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      Authors: Santosh Reddy Kommidi, Michael Elwardany, Yong-Rak Kim, David J. Mensching
      Abstract: Transportation Research Record, Ahead of Print.
      This study presents a computational fracture modeling approach for predicting highly nonlinear viscoelastic cracking, such as fatigue damage, in asphalt mixtures and pavements. The modeling approach is presented and validated against field performance data from the FHWA-Accelerated Loading Facility (ALF) performance test sections. To that end, five mixtures differing either in the type of binder used or the amount of reclaimed asphalt pavement and reclaimed asphalt shingles were selected to assess their linear viscoelastic behavior, fracture properties, and field performance. A nonlinear viscoelastic cohesive zone fracture model was used along with a Gaussian distribution damage evolution to characterize the mixture fracture properties through a numerical-experimental calibration process. Individual mixture characteristics were then used as inputs to analyze the ALF pavement structure, and the fatigue response was predicted and compared with the field performance data for model validation. Although there are several model limitations to improve, the good agreement in performance rank order among test lanes demonstrates the capability and validity of the modeling approach. This implies that the computational modeling approach attempted in this study could potentially be used to analyze and design pavements in a mechanistic manner. This could be done with just a few laboratory tests for mixture properties such as viscoelastic dynamic modulus and cohesive zone fracture parameters.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T09:00:41Z
      DOI: 10.1177/03611981221105067
       
  • Literature Review on Problem Models and Solution Approaches for Managing
           Real-Time Passenger Train Operations: The Perspective of Train Operating
           Companies

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      Authors: Luis Marques, Sergio Moro, Pedro Ramos
      Abstract: Transportation Research Record, Ahead of Print.
      This study presents a comprehensive review of different problem models for managing railway operations by problem-type classification. Railway terminology was used to identify the studies that encompass the existing body of knowledge. The 28 articles analyzed showed that existing studies are focused on the individual schedule components, such as rolling stock, schedules, crews, and passengers. Few studies have adopted a broader scope by covering several of those components. Two of the most popular approaches include the integer linear program and the mixed integer linear program variant. The difference between them is that integer programming uses discrete decision-making variable data, while mixed integer programming also admits continuous variable data. In contrast, few studies involve combining computational algorithms with human knowledge-based approaches. This analysis reveals that the most significant variables for managing disruptive events are related to verifying suppressed circulation and the discrete events of real-time traffic, such as departures and arrivals at stations.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T08:57:58Z
      DOI: 10.1177/03611981221104810
       
  • Developing the Dynamic Bus Lane Using a Moving Block Concept

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      Authors: Yinjie Luo, Jun Chen, Shunying Zhu, Yuwei Yang
      Abstract: Transportation Research Record, Ahead of Print.
      Existing dynamic bus lanes (DBLs) typically use a fixed and long blocking space to guarantee bus priority, leading to a conflict between bus priority and traffic capacity. This study proposes an innovative approach in a connected-vehicle (CV) environment, called dynamic bus lane with moving block (DBLMB). The length of the moving block can be adjusted with the bus speed in real time, aiming to ensure bus priority with fewer road resources, thus improving traffic capacity. A three-lane cellular automata model is established to evaluate DBLMB in comparison with two other strategies, bus lane without priority and bus lane with intermittent priority (BLIP). First, the benefits of DBLMB over the established DBLs are analyzed qualitatively by the macroscopic fundamental diagram. Next, simulation experiments are conducted to compare the coordination between bus priority and capacity under different strategies. Then, the impact of DBLMB on microscopic traffic flow is investigated through evaluation indicators including lane density, lane speed, lane-changing frequency, and travel speed. Finally, the sensitivity of bus delay and traffic capacity to CV penetration is discussed. The results show that: (1) the capacity of a three-lane road adopting DBLMB strategy can be stabilized above 5200 passenger car units per hour (pcu/h) when the bus departure interval is higher than 60 s and the expected level of service is below B. (2) With 100%, 80%, 60%, 40%, and 20% of CV penetration, DBLMB improves the average capacity of the road by 523 pcu/h compared with BLIP, with only an incremental bus delay of 6.43 s per vehicle.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T08:53:59Z
      DOI: 10.1177/03611981221104693
       
  • How People Perceive the Safety of Self-Driving Buses: A Quantitative
           Analysis Model of Perceived Safety

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      Authors: Zehua Li, Xiang Li, Bin Jiang
      Abstract: Transportation Research Record, Ahead of Print.
      With the continuous development of automatic driving technology and advancements in related experimental research, the probability of traffic accidents caused by human factors has been greatly reduced. However, people are still cautious about the safety of automated driving technology. The purpose of this study was to investigate users’ perceived safety indicators and the psychological factors of their perceived safety judgment of self-driving buses. In this study, a structural model of the factors that influence self-driving buses, including behavioral intention of technology acceptance, trust theory, perceived risk, and perceived safety, was developed based on the technology acceptance model (TAM). Subsequently, a relevant survey of 215 respondents was conducted and analyzed using the partial least squares method. The results indicated that trust, perceived usefulness, and perceived ease of use were important factors for judging the perceived safety of self-driving buses. The structural model developed in this study can quantify and analyze user data to filter out the factors that influence the perceived safety of self-driving buses, which is conducive to improving people’s trust and acceptance of self-driving buses.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T08:51:37Z
      DOI: 10.1177/03611981221104455
       
  • Patrol Regimes for Traffic Officers in Transportation Asset Monitoring

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      Authors: Tom Strain, R. Eddie Wilson, Roger Littleworth
      Abstract: Transportation Research Record, Ahead of Print.
      In this paper, we investigate the feasibility of using highway traffic officers (TOs) for transportation asset management (TAM) alongside their primary role of incident response. Asset data, typically captured via highway surveys on an annual basis, are unsuitable for those assets whose condition might rapidly change, such as vegetation, streetlights, guardrails, or drainage systems. Therefore, we considered as a proof-of-concept, whether data collected from dashboard cameras installed in TO vehicles might provide analysts with near real-time asset data across an entire highway network. We considered a case study of a dedicated TO fleet deployed on the strategic road network (SRN) in England, UK, and developed a simulation based on publicly available data sets. Within the simulation, TOs patrolled under two distinct regimes and responded to dynamically generated incidents. The first regime aimed to minimize the the fleet’s incident response time, and the second aimed to maximize the fleet’s coverage, with the aim of capturing asset data across the entire highway network. Overall, our simulations showed that the TOs deployed for TAM reduced the SRN junction-to-junction section intervisit time by around 1 h 45 min, whereas their incident response time only increased by about 4 min. Moreover, 17% of SRN sections were not visited at all when the TOs prioritized fast incident response, which was reduced to 2% when the TOs prioritized the capture of asset data.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T08:49:36Z
      DOI: 10.1177/03611981221103243
       
  • Deep Learning Approach for Detecting Lane Change Maneuvers Using SHRP2
           Naturalistic Driving Data

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      Authors: Anik Das, Md Nasim Khan, Mohamed M. Ahmed
      Abstract: Transportation Research Record, Ahead of Print.
      Changing lane is a complex driving maneuver and could have a significant effect on traffic safety. Therefore, developing accurate and timely lane change detection systems could assist drivers to perform and complete this complicated driving task safely. This study proposes reliable lane change detection models based on deep learning (DL) and including features from vehicle kinematics, machine vision, roadway geometries, and driver demographics using the trajectory-level SHRP2 Naturalistic Driving Study and Roadway Information Database. A cutting-edge technique named “DeepInsight” was applied to transform numeric lane change data into image data. The generated image data sets were trained, validated, and tested using a novel DL architecture called ResNet-18, considering six categories of features. To balance the lane change database, two data balancing methods—the synthetic minority oversampling technique (SMOTE) and random majority under sampling (RMUS)—were considered and tested with various sampling ratios. In addition, wrapper-based Boruta and eXtreme gradient boosting (XGBoost) algorithms were used to extract relevant features in each category. A recall of 82% and overall accuracy of 77.9% were found using a ratio of 1:1 for the model based on vehicle kinematic features suggesting that the developed model could be used in the absence of other data. However, the best detection performance was observed using the same ratio for a reduced model based on XGBoost, which produced a recall and overall accuracy of 98.8% and 95%, respectively, considering all the features. The proposed detection system could be effectively leveraged to monitor lane change behavior and provide appropriate control strategies in a connected vehicle (CV) environment.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T08:40:15Z
      DOI: 10.1177/03611981221103229
       
  • Identifying Hospital Deserts in Texas Before and During the COVID-19
           Outbreak

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      Authors: Junfeng Jiao, Nathaniel Degen, Amin Azimian
      Abstract: Transportation Research Record, Ahead of Print.
      In this study, we proposed a GIS-based approach to analyzing hospital visitors from January to June 2019 and January to June 2020 with the goal of revealing significant changes in the visitor demographics. The target dates were chosen to observe the effect of the first wave of COVID-19 on the visitor count in hospitals. The results indicated that American Indian and Pacific Islander groups were the only ones that sometimes showed no shift in visitor levels between the studied years. For 19 of the 28 hospitals in Austin, TX, the average distance traveled to those hospitals from home increased in 2020 compared with 2019. A hospital desert index was devised to identify the areas in which the demand for hospitals is greater than the current hospital supply. The hospital desert index considers the travel time, location, bed supply, and population. The cities located along the outskirts of metropolitan regions and rural towns showed more hospital deserts than dense city centers.
      Citation: Transportation Research Record
      PubDate: 2022-07-08T08:39:03Z
      DOI: 10.1177/03611981221095745
       
  • Understanding Adoption Intent and Behavioral Response to Shared Electric
           Bicycles: A Survey in Ningbo, China

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      Authors: Wenhao Li, Yongjiang Yang, Long Cheng, Xianghe Meng, Fan Zhang, Yanjie Ji
      Abstract: Transportation Research Record, Ahead of Print.
      As a new form of shared mobility similar to bike-sharing, there is an increasing trend of people starting to use shared electric bicycles (SEB) for travel in China. Understanding the psychosocial factors that affect residents’ intention to use SEB is essential for the implementation of policies to develop sustainable transportation. Most research focuses on bike-sharing, while research on SEB is relatively rare. As such, this study proposes a theoretical framework based on the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to explore the mechanisms that influence the acceptance of and intention to use SEB. Drawing on this, it further addresses the moderating role of group heterogeneity and the residual effect of bike-sharing. An online survey of 313 SEB users in China was conducted in 2021. The results are constructed by structural equation modeling (SEM) and multiple-indicator multiple-cause (MIMIC) model. The results show that the research model can well explain people’s intention to use SEB. Perceived usefulness, attitude, subjective norm, and perceived behavioral control have direct positive effects on the intention to use SEB. However, there is group heterogeneity between social-economic attributes and latent variables. Moreover, satisfaction with bike-sharing could moderate the relationship between perceived usefulness and intention toward SEB. Based on the findings, some policy insights from users, government, and enterprises are proposed to guide the development of SEB.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:42:19Z
      DOI: 10.1177/03611981221103874
       
  • Multiple Drone Routing Problem for On-Demand Hyperlocal Market

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      Authors: Murugaiyan Pachayappan
      Abstract: Transportation Research Record, Ahead of Print.
      Deploying drones for rapid pickup and delivery for on-demand customers in the hyperlocal market is unexplored in literature and demands attention. Maximizing customer pickup and deliveries with a limited drone flight endurance is essential but is hard to achieve in practice because of many service requests by on-demand customers. It mandates that drones cover extra mileage to visit docking stations in between services for recharge. Optimally allocating the services on available flight endurance and minimizing the docking station visits to complete all scheduled services is a predominant requirement for effective drone operations in a hyperlocal market. This problem is formulated as a mixed-integer linear programming model, and a heuristic algorithm is proposed to attempt various practical size problems, with near-optimal solutions reported. The paper offers valuable insights for practitioners and future researchers wishing to analyze the performance of drone operations and determine the appropriate number of drones required for the hyperlocal market based on service demand.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:35:49Z
      DOI: 10.1177/03611981221103872
       
  • Longitudinal Analysis of COVID-19 Impacts on Mobility: An Early Snapshot
           of the Emerging Changes in Travel Behavior

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      Authors: Grant Matson, Sean McElroy, Yongsung Lee, Giovanni Circella
      Abstract: Transportation Research Record, Ahead of Print.
      The COVID-19 pandemic has caused a huge disruption worldwide with direct and indirect effects on travel behavior. In response to extensive community spread and potential risk of infection, during the early stage of the pandemic many state and local governments implemented non-pharmaceutical interventions that restricted non-essential travel for residents. This study evaluates the impacts of the pandemic on mobility by analyzing micro panel data (N = 1,274) collected in the United States via online surveys in two periods, before and during the early phase of the pandemic. The panel makes it possible to observe initial trends in travel behavior change, adoption of online shopping, active travel, and use of shared mobility services. This analysis intends to document a high-level overview of the initial impacts to spur future research to dive deeper into these topics. With the analysis of the panel data, substantial shifts are found from physical commutes to teleworking, more adoption of e-shopping and home delivery services, more frequent trips by walking and biking for leisure purposes, and changes in ridehailing use with substantial variations across socioeconomic groups. The social and environmental implications of these findings are discussed and suggestions for effective policy and directions for future research are made in the conclusion.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:33:56Z
      DOI: 10.1177/03611981221090241
       
  • Transit Usage in Social Shocks: A Case Study of Station-Level Metro
           Ridership in Anti-Extradition Protests in Hong Kong

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      Authors: Ho-Yin Chan, Hanxi Ma, Jiangping Zhou
      Abstract: Transportation Research Record, Ahead of Print.
      As a form of social movement aiming to effect social change, protests could bring about unintended impacts on all walks of life. In other words, the cost of protests can be incurred by those who might not be protesters. The protests triggered by an extradition bill in Hong Kong since 2019 are no exception. This paper focuses on the impacts on the ridership of the metro system on protest days. It synthesizes and hypothesizes factors influencing the distribution of the ridership changes and conducts an empirical study in the context of Hong Kong to study the possible influences and spatial dependence. It is found that, across metro stations, political orientation (percentage of votes to pro-democracy camp in the 2019 Election of District Councils), law enforcement (permission from the police to protest), land use type (especially for commercial and open space), population age and income, as well as transit/road network characteristics and intermodal connectivity, significantly influence the ridership of metro stations during protest days. In addition, the mixed regressive spatial autoregressive model has higher explanatory power than the ordinary least square model, suggesting the need for a spatial lag and error specification. The results could also have significant implications for policy and planning for operating metro services and managing metro stations before, during, and after social shocks.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:31:54Z
      DOI: 10.1177/03611981221103587
       
  • Investigation of Inlaid Pavement Marker Performance and Safety
           Effectiveness

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      Authors: Carmine Dwyer, Scott Himes
      Abstract: Transportation Research Record, Ahead of Print.
      The objectives of this study were to assess inlaid pavement marker (IPM) performance and estimate their safety effectiveness in St. Louis, Missouri. IPM performance was evaluated through a count of marker presence and a feedback survey from participants who viewed dry and wet night videos of IPM sections in the St Louis area. The safety effectiveness of IPMs was evaluated using a rigorous state-of-the-art empirical Bayes (EB) before–after crash analysis. The marker presence assessment, unfortunately, did not provide any conclusive trends in IPM performance. Newer IPM sections had higher percentages of missing markers than older sections, and there were too many unknown variables to determine the source of the unexpected differences. The unanimous conclusion of the nighttime video visibility survey was that drivers and passengers traveling on a wet night feel that IPMs are very important to the visibility of the roadway’s lane lines. For the EB analysis, installation and reference site data were used to examine the effects for specific crash types, including total, fatal and injury, wet pavement, nighttime, nighttime wet pavement, lane departure, wet pavement lane departure, and nighttime lane departure. Based on the aggregate results, IPMs, when installed with pavement resurfacing, significantly reduce all crash types examined.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:29:34Z
      DOI: 10.1177/03611981221103244
       
  • LRFD Approach for Load Rating U.S. Army-Owned Bridges That Require
           Engineering Judgment

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      Authors: Monica A. McCluskey, Joshua W. Muller
      Abstract: Transportation Research Record, Ahead of Print.
      As part of their 2020 Biennial Inspection Program, the U.S. Army is conducting a load rating effort for its bridges located at military installations throughout the United States. To date, 201 structures at 26 army bases are being evaluated for both civilian and military vehicles. Seventy-two of these structures are reinforced concrete bridges with unknown reinforcement which must therefore be rated using engineering judgment. The American Association of State Highway and Transportation Officials’ (AASHTO) Manual for Bridge Evaluation provides guidance for these structures when the live loads are civilian vehicles. For army-owned bridges, however, an allowable military load classification must also be determined. A procedure called “correlation classification” is currently used to determine the proper military load classification for a particular bridge. The current procedure, however, is based on the allowable stress method. To allow the use of load resistance factor design (LRFD), a new correlation equation and methodology using LRFD principles was developed. The methodology, however, requires the load rater to incorporate knowledge about the bridge into the load rating process. For older bridges with lighter design vehicles, and low the average daily traffic bridges, the correlation concept was also used to determine if a posting was required for state legal and emergency vehicles. This exercise demonstrated that the current correlation equation can be successfully modified to incorporate LRFD principles and applied to determine the military load classification for reinforced concrete structures that require engineering judgment. The application of the new correlation equation is illustrated with two examples: a reinforced concrete beam bridge and a box culvert.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:26:14Z
      DOI: 10.1177/03611981221103241
       
  • Developing Statewide Safety Performance Functions for Commercial Trucks
           Transporting Hazardous Materials on Interstate Rural Roads in Wyoming

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      Authors: Sherif M. Gaweesh, Irfan U. Ahmed, Mohamed M. Ahmed, Shaun S. Wulff
      Abstract: Transportation Research Record, Ahead of Print.
      Truck crashes in Wyoming are considered a major issue. Nearly 26% of crashes on rural interstate roads involve hazardous materials (HAZMAT) trucks. Wyoming has a high rate of activities related to the energy industry, as it is considered among the top energy producing states in the U.S.A., and mainly relies on the trucking industry for transportation. A crash involving a HAZMAT shipment might have a catastrophic impact because of the nature of the HAZMAT shipment. Therefore, it is crucial to identify the traffic safety performance of HAZMAT trucks, so suitable countermeasures can be identified to reduce the frequency and severity of these crashes. This study aims to develop safety performance functions (SPFs) for crashes involving HAZMAT utilizing traditional negative binomial (NB) models, as well as variations of the NB model, namely, NB-1 and NB-P. The results indicate that HAZMAT truck crashes are associated with vehicle miles traveled, truck percentage, horizontal and vertical characteristics of road geometry, pavement type, and speed limit. The findings from this study show that the NB-P models outperformed the traditional NB models based on likelihood ratio tests, information criteria, and prediction measures. Relevant insights are made on traditional countermeasures, such as road geometry, warning signs, slippery road surface warnings, and climbing lanes, as well as non-traditional countermeasures including updating variable speed limit (VSL) algorithms, adding variable message signs, and integrating roadway geometry information into connected vehicle applications in Wyoming. These could be considered to assist stakeholders and emergency management agencies in better decision making toward safer operations of HAZMAT trucks.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:22:39Z
      DOI: 10.1177/03611981221103231
       
  • Evolution of Driver Fatigue Detection Techniques—A Review From 2007
           to 2021

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      Authors: Mukesh Kumar Kamti, Rauf Iqbal
      Abstract: Transportation Research Record, Ahead of Print.
      Driver fatigue is the most important factor in the increase in the frequency of traffic accidents and fatalities every year. Fatigue impairs driving performance through a lack of concentration and slower reaction time. Therefore, a fatigue detection system is very important for safe driving. This paper presents a systematic literature review of the research conducted over the last 15 years to provide information about the evolution of various driver fatigue detection (DFD) systems with the advancement of technologies. In the domain of DFD, researchers have used different approaches such as physiological, behavioral, vehicular, and mixed. Findings from the study indicate that physiological and behavior-based techniques are widely used by the authors, whereas vehicular features are very scarcely used. Analysis of papers shows that researchers are more likely to utilize a combination of physiological and behavior-based approaches to identify driving fatigue or drowsiness. The outcome of this literature review could help practitioners to improve existing fatigue detection technologies by application of the different approaches for fatigue identification and measurement.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:18:15Z
      DOI: 10.1177/03611981221096118
       
  • Evaluation of the Interlayer Bond Strength of Micro-Surfacing Mixes

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      Authors: Ahmad Al-Hosainat, Munir D. Nazzal, Sk Abu Talha, Sang-Soo Kim, Ala Abbas, Louay Mohammad, Eric Biehl, Perry Ricciardi
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents the results of the first study to evaluate the effects of the tack coat and micro-surfacing mix properties on the interlayer bond strength between the micro-surfacing layer(s) and existing pavement surface. Several factors were investigated, which included the type of tack coat material, tack coat application rate, and the residual binder content of the micro-surfacing mix. To this end, a total of 14 field micro-surfacing test sections were installed on Ohio State Route 03 in Wayne County, Ohio. While the first seven sections were constructed with a single micro-surfacing layer, the other seven sections had double micro-surfacing layers. Five tack coat application rates and two residual binder contents were evaluated. The testing plan involved obtaining core samples from the constructed sections 1 week, 4 months, and 12 months after construction. The obtained field cores were tested in the laboratory using two types of pull-off tests and a torque bond strength test. The results of bond strength tests on obtained field cores and the statistical analysis performed on these results indicated that sections with no tack coat had significantly lower bond strength than those with tack coat with at least 0.05 gallons per square yard (gsy) total application (0.0083 gsy residual application rate). Furthermore, results indicated that the use of 0.75% lower residual asphalt binder content in micro-surfacing mixes resulted in significantly lower bond strength between the micro-surfacing and existing pavement. The tack coat material properties had some effect on the interlayer bond strength; however, this effect was statistically insignificant.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:11:26Z
      DOI: 10.1177/03611981221094284
       
  • Computationally Efficient Modeling of Lightweight Expeditionary Airfield
           Surfacing Systems at Large Length Scales

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      Authors: R. P. Kinser, M. E. Barkey, T. W. Rushing, A. R. Cisko, L. Garcia, P. G. Allison, J. B. Jordon
      Abstract: Transportation Research Record, Ahead of Print.
      Expeditionary airfield matting systems are lightweight, portable surfaces that enable the rapid deployment of infrastructure to support aircraft operations. Individual matting components are assembled via interlocking joints to construct arrays that serve as temporary aircraft operating surfaces. The paper outlines the homogenization of the AM2 portable airfield matting system and its interlocking mechanisms to permit computationally efficient analyses toward understanding mechanisms that influence the global behavior of these arrays and underlying subgrade during aircraft maneuvers. An equivalent orthotropic two-dimensional continuum was developed from finite element analysis of a detailed three-dimensional model and its flexural behavior was validated against experimental data and solid finite element models. Interlocking joints were characterized using node-to-node connector elements based on subscale finite element studies. Both components were implemented into a full-scale model representative of a typical test section, and responses to static high tire pressure aircraft loads were analyzed over a soil foundation representing a California bearing ratio of 6%, yielding promising agreement with experimental data. Results of this study reveal an inherent coupling between load transfer, mat deflection, and near-surface subgrade stress with dependence on tire location, mat core shear flexibility, and joint stiffness.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:08:46Z
      DOI: 10.1177/03611981221101620
       
  • Recurrent Neural Networks for Pavement Performance Forecasting: Review and
           Model Performance Comparison

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      Authors: Micah Mers, Zhongyu Yang, Yung-An Hsieh, Yichang (James) Tsai
      Abstract: Transportation Research Record, Ahead of Print.
      Accurate pavement performance forecasting is critical in supporting transportation agencies’ predictive maintenance strategies: programs that prolong pavement service life while using fewer resources. However, because of the complex nature of pavement deterioration, high accuracy for long-term and project-level pavement performance forecasting is challenging to traditional models. Therefore, researchers have taken advantage of machine learning (ML) technology to create more sophisticated models in recent years. However, there are no extant studies that compare different ML models on a singular, real-world, large-scale, and comprehensive pavement data set to evaluate their capability for pavement performance forecasting. Thus, the goal of this study is to critically evaluate ML models, such as multiple linear regression (MLR), fully connected neural network (FCNN), recurrent neural network (RNN), gated recurrent unit (GRU), long short-term memory (LSTM), and a hybrid LSTM-FCNN model, on Florida’s statewide, 31 year historical pavement data set. The results demonstrate that the RNN, GRU, LSTM, and LSTM-FCNN models perform significantly better than MLR and FCNN for predicting time-series pavement condition, with the LSTM-FCNN model performing the best. This result provides a valuable demonstration and recommendation to transportation agencies and researchers that RNN-based ML models are a promising direction to improve the accuracy of pavement performance forecasting.
      Citation: Transportation Research Record
      PubDate: 2022-07-02T09:05:39Z
      DOI: 10.1177/03611981221100521
       
  • Measured Effect of Low-Height Solid Safety Barriers on Heavy Truck Noise

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      Authors: Benjamin R. Sperry, Judith L. Rochat, Karel L. Cubick, Issam Khoury
      Abstract: Transportation Research Record, Ahead of Print.
      Low-height solid safety barriers (SSBs) are constructed along highways where an adequate clear zone cannot be provided between the highway and an important roadside feature. Where a roadside SSB is a permanent installation, it is possible that it also provides noise reduction benefits. Highway traffic noise sources that could be shielded by a low-height SSB include tire–pavement noise and any other noise originating close to the pavement surface, such as a low exhaust on a heavy truck. This paper reports the findings of a study examining how heavy truck noise is shielded by low-height roadside SSBs. Measurements of the maximum sound level (Lmax) of individual heavy truck pass-by events at two representative locations in Ohio were obtained at a position where a low-height SSB was present as well as at a nearby unshielded position. The results indicated that a perceptible reduction in the pass-by event Lmax (between 3 and 5 dBA) was realized for locations behind the SSBs. Variations in the measured noise reduction were associated with the line-of-sight shielding between various truck noise sources and the receiver positions. For events in which the exhaust source was shielded by the SSB, the measured noise reductions were higher at the site with the 42-in. tall SSB, although there was no difference for the site with the shorter (32-in.) SSB. It is recommended that analysts consider the potential for noise reduction associated with low-height SSBs in locations where such barriers are expected to be permanent.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T06:27:54Z
      DOI: 10.1177/03611981221106175
       
  • Rerounding of Deflected Thermoplastic Conduit in Well-Graded Aggregate
           Backfill

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      Authors: Kevin White, Shad Sargand, Issam Khoury
      Abstract: Transportation Research Record, Ahead of Print.
      Rerounding is a technique for remediating excess deflection in thermoplastic pipe using a pneumatic device vibrating along the vertical axis and pushing against the inside crown and invert to restore the original pipe shape and redistribute the surrounding backfill. Since the process has not been evaluated on high density polyethylene (HDPE) pipe outside of a few reports, and the method is routinely used by contractors to remediate deflected thermoplastic pipes, the Ohio Department of Transportation (ODOT) wanted to evaluate the technology as a lower-cost and less disruptive alternative to the removal and reinstallation of deflected pipes. Three 36-in. HDPE pipes were installed in a well-graded crushed stone aggregate, sand, or AASHTO #57 open-graded aggregate (ODOT Structural Backfill, Types 1, 2, and 3, respectively), and two 18-in. pipes were installed in Types 2 and 3 Structural Backfill. Pipes were intentionally installed with substantial deflection (10% or more) and then rerounded. The pipe conditions were measured and monitored by collecting profiles, measuring vertical deflections and monitoring soil pressures, backfill characteristics, and the depth of pipe corrugation before and after rerounding. This paper focuses on Test Pipe 1 installed in Type 1 Structural Backfill, which was the most resistant to rerounding. Pressure data were consistent with the redistribution of backfill particles, particularly fines.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T06:25:01Z
      DOI: 10.1177/03611981221105077
       
  • Assessing and Comparing Data Imputation Techniques for Item Nonresponse in
           Household Travel Surveys

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      Authors: Alikasim Budhwani, Tina Lin, Devin Feng, Chris Bachmann
      Abstract: Transportation Research Record, Ahead of Print.
      This research provides a comparative assessment of data imputation techniques for item nonresponse in household travel surveys. Using the Transportation Tomorrow Survey (TTS) data for the Region of Waterloo in Ontario, Canada, a series of synthetic datasets are generated with varying amounts of missing data, while preserving the respective proportions of missing items and missing item combinations in the original survey data. Then, the performances of six different imputation techniques are compared. The six different imputation techniques include two simple imputation techniques (mode and hot-deck), three discriminative models (logistic regression, multi-layered perceptron, support vector machines) and one generative model (autoencoder). This assessment compares these techniques, as well as the impact of the proportion of item nonresponse in the dataset through their repeated application to multiple synthetic datasets. Results show that the machine/deep learning techniques (both generative and discriminative) not previously applied to household travel survey data outperform their simple imputation counterparts. Overall, the accuracy of travel household survey data imputation is shown to depend on many factors, including the technique employed, the dimensionality of the missing item, and the hypertuning of the technique (if applicable), but not on the amount of missing data in these experiments. This research should prove beneficial to practitioners who often confront item nonresponse in their household travel survey data by providing evidence and recommendations to support the selection and implementation of a data imputation technique. The research methodology also provides a repeatable procedure for future researchers to test data imputation techniques on their own datasets.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T06:22:01Z
      DOI: 10.1177/03611981221104802
       
  • Data-Driven Detection and Assessment for Urban Railway Transit Driver
           Fatigue in Real Work Conditions

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      Authors: Yubo Jiao, Xiaoyu Chen, Zhiqiang Sun, Liping Fu, Chaozhe Jiang, Chao Wen, Xiaoming Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Fatigue among urban railway transit (URT) drivers affects their performance and is a contributing factor in many railway accidents and incidents. This paper attempts to develop a robust fatigue detection system for URT drivers. An experimental study was conducted in actual work conditions, involving 198 professional URT drivers, to provide authentic and representative data. Fatigue scores based on the Karolinska Sleepiness Scale were used as the ground truth, and heart rate variability (HRV) data were collected using wearable photoplethysmography (PPG) sensors under actual working conditions. An extensive statistical analysis found that continuous working hours were a major factor in driver fatigue. HRV features were able to differentiate various fatigue levels. Four classifiers (k-nearest neighbors, Naive Bayes, support vector machines, and random forests) were trained to detect fatigue in real time for binary and three-class fatigue classifications, respectively. For the binary classification, the best performance was achieved by the random forest classifier using the corrected feature set as input with an accuracy of 92.5%. However, the accuracy dropped by 8 to 27 percentage points for the three-class classification. Moreover, the research found that the corrected feature set circumventing inter-individual variability in HRV could improve the performance of fatigue classifiers. The findings from this research could contribute to developing a robust and real-time URT driver fatigue detection system and improve current URT operational safety regulations.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T06:19:41Z
      DOI: 10.1177/03611981221104689
       
  • Curling of Cast-in-Situ Short Slabs on Lean Concrete Base: Measured Versus
           Theoretical Analysis

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      Authors: Sridhar Reddy Kasu, Sandesh Patel, Anush K Chandrappa, Amaranatha Reddy Muppireddy
      Abstract: Transportation Research Record, Ahead of Print.
      Cast-in-situ short paneled concrete pavements (CiSPCP) are a class of innovative concrete pavements, which are being considered as a sustainable replacement for jointed plain concrete pavement. However, there is a lack of understanding of various aspects of CiSPCP such as joint spacing, long-term joint performance, dominant stresses, failure criteria, and curling behavior. In this study, the curling behavior of CiSPCP test sections with different slab sizes and thicknesses on National Highway (NH)-18 (old NH-33) were investigated during the summer of 2019 and the winter of 2020. The vertical displacements at mid-slab (longitudinally and diagonally to the slab), the effect of slab size and thickness on curling with seasonal variation were considered, along with a comparison of measured curling using theoretical analysis. The measured displacements at the edge of slabs were smaller compared with those at the center of the slab. Interestingly, the occurrence of maximum slab curl was not in tandem with the maximum temperature gradient (TG). The time lag for the response was around 2 to 4.5 h of the occurrence of a maximum TG. This observation was very significant because temperature stresses have a profound effect on stresses in concrete pavement. However, this field observation has indicated that the lag in the development of maximum TG may also lead to a lag in the development of stresses. Further, it was found that the theoretical method overestimates the curling compared with the field-measured displacements, which can be mainly attributed to the lag.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T06:17:19Z
      DOI: 10.1177/03611981221104459
       
  • Simulation and Criticality Assessment of Urban Rail and Interdependent
           Infrastructure Networks

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      Authors: Xian Bin Wee, Manuel Herrera, Georgios M. Hadjidemetriou, Ajith Kumar Parlikad
      Abstract: Transportation Research Record, Ahead of Print.
      The role of urban infrastructure is becoming increasingly interdependent, resulting in new sources of vulnerability. Infrastructural asset failure can propagate between rail transportation and other infrastructure networks. There remains a lack of academic research focusing on the dynamic simulation of city-wide infrastructure using real-life data to quantify and cross-compare the criticality of assets. This paper aims to bridge this gap by developing a modeling methodology for interdependent urban infrastructure using complex network theory, which serves as a basis for investigating asset criticality and failure propagation. This modeling framework comprises the distribution of resource supply and demand, the topological representation and skeletonization of the infrastructure network, as well as modeling the propagation of asset failures. The framework is thereafter applied to a case study of the exposure of Greater London’s rail transportation network to failures from electricity infrastructure, selected as a representative example of interdependent infrastructures within a large-scale urban metropolitan area. Two time-based criticality metrics are also proposed to measure the topological extent of infrastructural failures and economic impacts resulting from the failure propagation of given initial failure scenarios. The results of the case study demonstrate that these proposed criticality metrics are effective in capturing the dynamics of failure propagation, and that topological metrics in criticality assessment do not always reflect the resulting economic damages of infrastructural failures.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T06:14:19Z
      DOI: 10.1177/03611981221103594
       
  • Lane-Changing Trajectory Planning Model for Automated Vehicles Driving on
           a Curved Road

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      Authors: Hao Luo, Min Wang, Weiming Luo, Wenjie Lv, Da Yang
      Abstract: Transportation Research Record, Ahead of Print.
      This paper attempts to study the lane-changing trajectory planning problem of automated vehicles driving on a curved road. The existing models have the following shortcomings. First, the curvature of the curved road is assumed as a constant, while the curvature is a gradient in the real world. Second, the existing studies either do not consider the speed variations of the surrounding vehicles in lane changing or ignore the curvature difference between the target and current lanes. To overcome the shortcomings, this study puts forward a novel trajectory planning model for curved-road lane changing of automated vehicles. In the model, a new strategy of planning a straight-road lane-changing trajectory first and then modifying it to adapt the curvature variation of the curved road is adopted, and a new collision-avoidance model for curved-road lane changing is developed. The proposed model is evaluated by comparing with the existing models and CarSim simulation platform. The results indicate that the proposed model can enhance the curved-road lane-changing safety of automated vehicles, and the lane-changing trajectory planned by the proposed model can be well tracked by automated vehicles.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T06:11:03Z
      DOI: 10.1177/03611981221103242
       
  • Ridership and Operations Visualization Engine: An Integrated Transit
           Performance and Passenger Journey Visualization Engine

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      Authors: Nicholas S. Caros, Xiaotong Guo, Anson Stewart, John Attanucci, Nicholas Smith, Dimitris Nioras, Anna Gartsman, Alissa Zimmer
      Abstract: Transportation Research Record, Ahead of Print.
      Transit agencies collect a vast amount of data on vehicle positions, passenger loading and, increasingly, origin–destination flows. Collecting and synthesizing these data to support operations and planning are significant challenges and can be constrained by information silos within transit agencies. In this paper, an open-source bus performance and journey visualization dashboard, Ridership and Operations Visualization Engine, is presented, which integrates multiple disparate data sources into a flexible and iterative analysis tool. It differs from existing commercial products by including origin–destination flows along with standard performance metrics, and is designed to be adaptable and relevant to any transit agency. Two case studies are presented to demonstrate the functionality of the dashboard: planning transit priority infrastructure and evaluating network design changes. The dashboard was developed in partnership with Chicago Transit Authority and Massachusetts Bay Transportation Authority, and practical details from the installation and maintenance procedures are included for prospective users.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T05:54:51Z
      DOI: 10.1177/03611981221103232
       
  • Life-Cycle Approach to Healthy Airport Terminal Buildings:
           Spatial-Temporal Analysis of Mitigation Strategies for Addressing the
           Pollutants that Affect Climate Change and Human Health

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      Authors: Fiona Greer, Arpad Horvath, Jasenka Rakas
      Abstract: Transportation Research Record, Ahead of Print.
      The potential environmental and human health impacts associated with constructing and operating terminal buildings is explored for commercial airports in the United States. Research objectives are to quantify: (1) baseline and mitigated greenhouse gas (GHG) and criteria air pollutant (CAP) emissions; (2) operational costs; and (3) climate change damages from terminal building construction and materials, operational energy consumption, water consumption and wastewater generation, and solid waste generation. An Excel-based decision-support tool, Airport Terminal Environmental Support Tool (ATEST), has been created to allow stakeholders to conduct preliminary assessments of current baseline and potential mitigated impacts. Emissions are quantified using a life-cycle approach that accounts for cradle-to-grave effects. Climate change and human health indicators are characterized using EPA’s Tool for Reduction and Assessment of Chemical Impact (TRACI) factors. ATEST is applied to multiple case study airports— Reno/Tahoe International (RNO), Pittsburgh International (PIT), Newark Liberty International (EWR), Seattle-Tacoma International (SEA), San Francisco International (SFO), and Hartsfield-Jackson Atlanta International (ATL)—to demonstrate its scalability and capability to assess varying spatial factors. Across all airports, electricity mix and construction are significant in determining GHG and CAP emissions, respectively. A sensitivity analysis of GHG emissions for the SFO case study reveals that the electricity mix, amount of electricity consumed within the terminal, terminal gross area, and amount of compostables in the solid waste stream have the most impact on increasing annual GHG emissions. ATEST represents a crucial first step in helping stakeholders to make decisions that will lead to healthier, more sustainable airport terminals.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T05:51:51Z
      DOI: 10.1177/03611981221101896
       
  • Reducing Uncertainties in Nanoindentation Experiments for Cementitious
           Materials

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      Authors: Poornima Patil, Christopher Jones
      Abstract: Transportation Research Record, Ahead of Print.
      Limited research is available to guide the intelligent selection of test parameters such as load level, grid size, grid spacing, and sample surface roughness to design nanoindentation experiments on cementitious materials. A cohort of nanoindentation experiments on four different cement pastes utilizing varying indentation depth, load level, grid spacing, grid size, and surface roughness were performed. Results from this study indicate that a “critical indentation depth” exists for each sample such that individual indentations shallower than the critical depth demonstrate greater variability for all measured properties than deeper indentations. Most commercial nanoindentation equipment is load controlled, so careful load selection is important to ensure that the critical indentation depth is achieved. Elastic indentation properties appear to show dependence on grid spacing and grid size. Surface roughness and the polishing method profoundly influence measured properties. The study demonstrates that the choice of test parameters is influenced by the microstructural details (phases) under consideration, as well as the porosity of the sample and therefore cannot be generalized.
      Citation: Transportation Research Record
      PubDate: 2022-07-01T05:49:13Z
      DOI: 10.1177/03611981221101033
       
  • Development and Evaluation of Non-Traditional Pedestrian Timing Treatments
           for Coordinated Signalized Intersections

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      Authors: Slavica Gavric, Denis Sarazhinsky, Aleksandar Stevanovic, Nemanja Dobrota
      Abstract: Transportation Research Record, Ahead of Print.
      Pedestrian signal timings are one of the major issues to be addressed when developing signal timing plans. So far, two different treatments of pedestrian timings for coordinated systems exist. The first treatment accommodates pedestrian timing within the cycle. Therefore, it requires longer cycle lengths that usually increase the total delay on the network. In contrast, the second treatment uses shorter cycle lengths sufficient to serve vehicular demand only. The problem with the latter is that the concurrent phase is usually not long enough to serve pedestrians. Thus, with every pedestrian call, a follow-up transition process occurs, affecting cycle lengths and coordination quality. This study develops two novel pedestrian timing treatments to overcome the problems of the traditional ones. Novel pedestrian treatments utilize a cycle length optimized to cover necessary times for vehicular phases, although pedestrian timings may require longer time intervals. However, when pedestrian calls occur, their minimum safety timings are accommodated within such a shorter cycle, and thus the transition process is not required. Our study evaluates the proposed and traditional pedestrian timing treatments using a corridor of five signalized intersections in West Valley City, Utah. Various experiments were conducted in a microsimulation environment VISSIM and collected results were statistically compared. Results show the promising property of the proposed treatments, as they outperformed the traditional pedestrian timing treatments. Therefore, further investigation of these pedestrian timing treatments is warranted. Future research should investigate possibilities of implementing similar treatments to fully actuated control systems on various networks and traffic conditions.
      Citation: Transportation Research Record
      PubDate: 2022-06-30T11:05:51Z
      DOI: 10.1177/03611981221099913
       
  • On Heterogenous Sampling Rates in Origin–Destination Matrix Estimation
           Based on Trajectory Data and Link Counts

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      Authors: Fabien Leurent, Danyang Sun, Xiaoyan Xie
      Abstract: Transportation Research Record, Ahead of Print.
      Being a fundamental metric of the transportation network, the origin–destination (O-D) flow matrix is a critical input for various transportation models and studies. This paper deals with the estimation of an O-D matrix of trip flows based on two kinds of data: probe trajectory data and local traffic counts. A Bayesian assignment framework is developed for demonstrating the relationship between the link probe sampling rates and the fractional contributions from the sampling rates on different O-D pairs. The unknown O-D matrix is estimated by applying cross entropy minimization using a prior matrix from the probe trajectories, along with the Bayesian assignment rules on link sample rates as the constraints. The methodology was applied using floating car data and camera link flow counts for a numerical experiment. The results show that the method can achieve a robust estimation of O-D matrices, even using different prior matrices. The issue of the heterogeneous sampling rates can be well addressed with link count constraints, effectively correcting the unknown bias in the probe sampling. The case study using real data also proves the feasibility of mining observed trajectory data to obtain the assignment fractions and estimate the O-D matrix inversely, avoiding the conventional sophisticated process of traffic assignment modeling.
      Citation: Transportation Research Record
      PubDate: 2022-06-30T05:22:54Z
      DOI: 10.1177/03611981221103589
       
  • Improving Service Coverage and Response Times for Three-Wheeled Mobile
           Fire Units on Pari Island, Indonesia

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      Authors: Fatma Lestari, Karl Kim, Andrio Adiwibowo, Devie Fitri Octaviani, Micah Fisher, Eric Yamashita
      Abstract: Transportation Research Record, Ahead of Print.
      Improved service area coverage and response times by mobile fire response units is key to successful fire suppression and risk reduction. In this paper, the challenges of fire suppression in remote island communities are investigated. Small islands not only have limited firefighting equipment and resources but also face significant transportation problems. This study examines Pari, an island in the Pulau Seribu archipelago in Indonesia, to understand the planning and management of mobile fire units (MFUs) for improving effective response and suppression. Like other communities in developing countries, Pari Island uses small three-wheeled MFU vehicles to respond to emergencies in densely populated settlements with narrow roads and limited access. This study reviews environmental, roadway, vehicle, and operating requirements to support planning, management, and operations of MFUs. Service area coverages were estimated using geographic information system tools to investigate factors such as hose length and constraints based on the transportation infrastructure and exposure to fire hazards. Based on existing conditions, increasing hose length to 20 m would increase the coverage of the MFU service area by two times that of the existing service. The use of a 30-m hose could provide coverage to over 96% of residential structures on Pari Island. In addition to describing the analytical tools including coverage zones, receiver operating characteristic, and area under the curve metrics to support MFU planning and operations, this paper highlights other initiatives that could increase resilience against fires and other hazards threatening small island communities.
      Citation: Transportation Research Record
      PubDate: 2022-06-30T05:20:14Z
      DOI: 10.1177/03611981221101031
       
  • Analyzing Access to Health Facilities by Road Using Unconventional Data
           Sources

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      Authors: Afeefah Khazi-Syed, Maksim Pecherskiy, Holly Krambeck
      Abstract: Transportation Research Record, Ahead of Print.
      The COVID-19 pandemic has led to an urgent need in emerging economies to quickly identify vulnerable populations that do not live within access of a health facility for testing and vaccination. This access information is critical to prioritize investments in mobile and temporary clinics. To meet this need, the World Bank team sought to develop an open-source methodology that could be quickly and easily implemented by government health departments, regardless of technical and data collection capacity. The team explored use of readily available open-source and licensable data, as well as non-intensive computational methodologies. By bringing together population data from Facebook’s Data for Good program, travel-time calculations from Mapbox, road network and point-of-interest data from the OpenStreetMap (OSM), and the World Bank’s open-source GOSTNets network routing tools, we created a computational framework that supports efficient and granular analysis of road-based access to health facilities in two pilot locations—Indonesia and the Philippines. Our findings align with observed health trends in these countries and support identification of high-density areas that lack sufficient road access to health facilities. Our framework is easy to replicate, allowing health officials and infrastructure planners to incorporate access analysis in pandemic response and future health access planning.
      Citation: Transportation Research Record
      PubDate: 2022-06-30T05:04:40Z
      DOI: 10.1177/03611981221098693
       
  • Non-Destructive Testing in Quality Assurance of Concrete for Assessing
           Production Uniformity

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      Authors: Setare G. Saremi, Dimitrios G. Goulias, Anjuman Ara Akhter
      Abstract: Transportation Research Record, Ahead of Print.
      Non-destructive testing (NDT) methods can be particularly valuable in assessing concrete quality at early ages as they are associated with reduced testing time and cost. A national study focusing on the potential use of NDT in quality assurance (QA) of concrete has recommended the adoption and/or use of such testing methods when these have low level of testing variability. Thus, objective of this study was to build on such recommendation and assess the response of specific well-developed and mature NDT methods in relation to their testing variability for detecting such production defects such as honeycombing and segregation. Recognizing the extensive knowledge and experience in assessing concrete with such methods over the years, the selected NDT methods considered were: ultrasonic pulse velocity (UPV); resonant frequency analysis (RFA); and, rebound hammer. Each of these NDT methods could be used for a specific assessment within QA as identified later on within the manuscript. The results indicated that indeed UPV is able to identify the presence of such defects with acceptable accuracy and repeatability. RFA also provided acceptable testing variability and thus can be used as complementary assessment to UPV in both lab and field-cured samples. The rebound hammer, as expected, was characterized with high testing variability and thus its use could be limited to a quick and only initial forensic assessment. Overall, the use of these NDT methods in QA will provide the opportunity to test a larger portion of concrete without a significant increase in QA cost and testing time.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T07:23:47Z
      DOI: 10.1177/03611981221103871
       
  • Securely Sharing and Visualizing Connected Vehicle Analytics: THEA CV
           Pilot Performance Evaluation Dashboard

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      Authors: Omkar Dokur, Sisinnio Concas, Mohsen Kamrani, Achilleas Kourtellis, Vishal Kummetha
      Abstract: Transportation Research Record, Ahead of Print.
      Dashboards are increasingly being used by organizations to process and visualize complex information and to reduce data complexity for planning and reporting. Their main function is to synthesize information for rapid and smarter decision making. This paper details the development of an innovative interactive dashboard to process connected vehicle (CV) data securely, report CV application evaluation analytics, and monitor CV infrastructure system performance. We detail the methods used to process complex, high-frequency (up to 10 Hz) information generated by more than 1,000 participants’ vehicles in the Tampa Hillsborough Expressway Authority (THEA) CV Pilot deployment over the course of two and half years of operation. The dashboard provides advanced query capabilities and custom visualization via interactive maps, graphics, and dynamic reporting to help inform decision making and securely share information. Further, individual CV application warnings can be analyzed using the warning profile feature that is equipped with visual animation replay. This novel approach not only compensated for the lack of in-vehicle dashboard cameras integrated into the CV Pilot infrastructure to assess behavioral responses to the human–machine interface, but also sped up manual validation time. The dashboard allows different levels of user access with customized views to meet a variety of stakeholder types and needs. This tool has been successfully used by the THEA CV Pilot evaluation team and U.S. Department of Transportation independent evaluators to perform precursory evaluations and to automate and perform false positive assessments of vehicle-to-vehicle and vehicle-to-infrastructure safety and mobility applications.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T07:18:23Z
      DOI: 10.1177/03611981221103870
       
  • Comparison of Fully Probabilistic and Partially Probabilistic Choice Set
           Models for Mode Choice

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      Authors: Parthan Kunhikrishnan, Karthik K. Srinivasan
      Abstract: Transportation Research Record, Ahead of Print.
      Contemporary models consider choice sets to be either fully deterministic or fully probabilistic. Deterministic choice set models do not account for stochasticity in the choice set formation, whereas probabilistic choice set models fail to recognize that exclusion and inclusion can be deterministic for some alternatives and individuals and yet random for others. A more general scenario is, therefore, where some alternatives are deterministically included or excluded and others probabilistically included. This paper proposes a richer framework that combines the features of both deterministic and probabilistic choice set models and explicitly allows an alternative to be deterministically included, deterministically excluded, or probabilistically considered in the choice set. This framework is better than the conventional models in four aspects: (a) the factors influencing consideration type are explicitly and parametrically analyzed instead of assumption as 0 or 1; (b) the specification can disentangle factors that affect the inclusion outcome from the type of consideration; and (c) the specification also permits differential sensitivity to factors in conditional choice probability among those who consider an alternative deterministically versus probabilistically. The partially probabilistic choice set model, a special case of the proposed generalized framework, developed using empirical data collected from working commuters in Chennai city, is benchmarked against the fully probabilistic choice set models. The results show that the former had improved goodness-of-fit, realistic consideration probability estimates, and better predictability of mode shares than the latter. Relevant policies have been evaluated by identifying the appropriate target segments at both the consideration and choice stages using the proposed model.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T07:10:58Z
      DOI: 10.1177/03611981221103869
       
  • On the Effect of COVID-19 on Drivers’ Behavior: A Survey Study

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      Authors: Erika Lopetrone, Francesco N. Biondi
      Abstract: Transportation Research Record, Ahead of Print.
      COVID-19 had a disruptive effect on the global community. This study looks at the effects that the stringent lockdown measures enacted in March 2020 had on motorists’ driving patterns. In particular, given the greater portability of remote working associated with the drastic decline in personal mobility, it is hypothesized that these may have served as accelerators for distracted and aggressive driving. To answer these questions, an online survey was conducted in which 103 respondents were asked to report on their own and other drivers’ driving behavior. While respondents agreed they drove less frequently, they also indicated that they were not prone to more aggressive driving or engaging in potentially distracting activities whether for work or personal purposes. When asked to report on other motorists’ behavior, however, respondents indicated they had witnessed more aggressive and distracting drivers on the road after March 2020 relative to the time before the pandemic. These findings are reconciled with the existing literature on self-monitoring and self-enhancement bias, and the existing literature on the effect of comparable large-scale, disruptive events on traffic patterns is used to discuss the hypothesis on how driving patterns may change after the pandemic.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T07:08:29Z
      DOI: 10.1177/03611981221103866
       
  • Evaluation of Driving Behavior and Traffic Safety at a Shifting Movements
           Intersection

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      Authors: Ma’en Mohammad Ali Al-Omari, Mohamed Abdel-Aty
      Abstract: Transportation Research Record, Ahead of Print.
      Unconventional intersection designs have been proposed for their theoretical potential to enhance traffic safety and operation simultaneously as a result of reducing the number of conflict points and signal phases. However, this has only been achieved with a very limited range of intersection designs which have a very low number of conflict points and under certain traffic conditions. For example, restricted crossing U-turn (RCUT) intersection, which has the lowest number of conflict points among other proposed intersection designs, has operational advantages at extremely unbalanced traffic volumes. Shifting movements (SM) intersection design, which has the same number of conflict points as the RCUT intersection, has been proposed to replace the RCUT implementation at intersections with medium to high minor traffic volumes. It was proven that SM outperforms an RCUT intersection which has medium to high minor traffic volumes in average delay and throughputs. This study aimed to investigate the safety aspects of this intersection design by utilizing the driving simulator. The effectiveness of using infrastructure-to-vehicle (I2V) communication for mitigating confusion at unconventional intersections was also investigated in the study. The results indicated that RCUT and SM intersections have similar safety performance and crossing them is completed with less risk than crossing the conventional intersection. However, there is a need to improve drivers’ knowledge about the SM intersection, especially with regard to the major left-turn movement. Most participants found that using I2V communication was helpful in understanding unconventional movement patterns.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T07:06:38Z
      DOI: 10.1177/03611981221103865
       
  • Improved Practices for Temporary Work Zone Guide Signs

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      Authors: LuAnn Theiss, Laura Higgins, Gerald L. Ullman
      Abstract: Transportation Research Record, Ahead of Print.
      Freeway reconstruction projects often involve adding lanes and improving entrance and exit ramps. Sign supports for overhead guide signs are sometimes removed early in the project to make way for construction activities. In addition, roadside guide signs may need to be relocated and replaced with temporary guide signs. The Manual on Uniform Traffic Control Devices provides guidance for work zone guide signs in Part 6, stating that temporary guide signs shall have black legend and border on an orange background. But permanent guide signs follow Part 2 of the MUTCD, which prescribes white legend and border on a green background for guide signs in general. Thus, many long-term freeway work zones may have guide signs in both color schemes that change throughout the project as the construction work progresses. The constrained conditions often seen in these work zones can also result in guide signs that use a variety of fonts, font sizes, sign sizes, and placement positions. This paper describes the human factors study that was performed to assess motorist understanding of various work zone guide signage strategies. Based on the results, the researchers were able to develop recommendations for long-term work zone guide sign design and placement to improve uniformity for the traveling public.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T07:03:58Z
      DOI: 10.1177/03611981221103593
       
  • Ultrafine Particle Ground-Level Impacts During Aircraft Approach and
           Climb-out Operations at a Major Cargo Hub

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      Authors: Maryssa Loehr, Jay Turner
      Abstract: Transportation Research Record, Ahead of Print.
      Ultrafine particles (UFP) contribute to adverse health outcomes such as asthma, obstructive pulmonary disease, cardiovascular disease, and lung cancer. Recent research draws attention to elevated ambient UFP number concentrations near airports. In this study, high time-resolution UFP measurements were conducted along public roads near Mohammad Ali International Airport (SDF; Louisville, KY) which is a commercial passenger airport and a major air cargo hub. Short-duration (∼3 h) measurements with two instrumented vehicles were designed and executed to capitalize on the distinct features of the air cargo hub including periods of high flight activity (and either all landings or all take-offs) at night and early morning when the atmospheric mixing layer depth is shallow. We present preliminary measurements for quantifying individual aircraft contributions and showcase the complexities involved in interpreting these data. For example, during periods with high arrivals frequency, UFP plumes from multiple aircraft on approach are superposed and it is challenging to apportion impacts to individual aircraft. Ground-level impacts for individual aircraft on climb-out are difficult to discern because the planes rapidly ascend above the atmospheric mixed layer height and take different flight paths soon after take-off. Elevated UFP concentrations are observed downwind of the airport, in some cases admixed with approach/climb-out emissions. Although from these data UFP concentrations are difficult to associate with specific aircraft characteristics, UFP concentrations are elevated downwind of the airport. These impacts decrease with increasing distance from the airport yet are clearly discernible at least 3 km downwind.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T07:00:59Z
      DOI: 10.1177/03611981221103590
       
  • Moving Beyond the Vision Zero Slogan

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      Authors: Ge Shi, Vannesa Methoxha, Carol Atkinson-Palombo, Norman Garrick
      Abstract: Transportation Research Record, Ahead of Print.
      Safe System is a holistic way of managing traffic safety based on all components within that system including road environments, speed regimes, vehicle safety, and post-crash intervention. The ultimate goal is to achieve zero road death and serious injury. Safe System was pioneered in the Netherlands and Sweden in the 1990s and gradually began to influence traffic safety management in other countries, including the U.S. Our research shows that since the adoption of Safe System in the Netherlands and Sweden, the risk of fatality has decreased at a rate far outpacing that in the U.S. The improvements have been particularly impressive when it comes to pedestrians and bicyclists who now have fatality risks that are as low as that of people in cars. Our paper outlines details of the Dutch and Swedish approach to Safe System that is associated with their tremendous success in reducing traffic fatality. The synthesis suggests that to embrace the Safe System approach, we need a paradigm shift that puts safety and quality of life at the forefront of our thinking about transportation planning, design, and implementation. We argue that there is a need for a broader dissemination, understanding, and adoption of the underlying principles of Sustainable Safety, and recommend that universities improve engineering and planning education with more Sustainable Safety thinking. We also argue for greater coordination between federal, state, and municipal agencies, and a move away from victim blaming toward the achievable goal of zero road deaths through the adoption of Sustainable Safety approaches.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:59:18Z
      DOI: 10.1177/03611981221103245
       
  • Measuring the Impact of Airspace Restrictions on Air Traffic Flow Using
           Four-Dimensional System Fundamental Diagrams for Urban Air Mobility

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      Authors: Christopher Cummings, Hani S. Mahmassani
      Abstract: Transportation Research Record, Ahead of Print.
      To ease urban congestion, advanced air mobility (AAM) proposes the use of small aerial vehicles at low altitudes for uses such as package delivery and passenger services. In a developed state, an AAM service is predicted to involve thousands of trips daily, creating much higher densities of aircraft than currently exist in any airspace. Airspace structures have been proposed to help manage the high-density aircraft traffic. One such airspace structure is tube airspace, in which vehicles fly along predefined paths at specified altitudes. Tube airspaces have the advantage of aligning vehicle trajectories to reduce conflicts, however, traffic flow through restricted tube airspaces is not yet well understood. This paper defines how to measure traffic flow in a restricted network of airspace. These definitions are applied to measure traffic flow in several simulated scenarios of tube airspace constructs. By analyzing and comparing the macroscopic traffic flow patterns of tube airspace, several insights about the benefits and drawbacks of tube airspace are found. The results of this paper could improve decisions about creating and managing tube airspaces, and therefore would be of interest to AAM network planners and operators. They are also of interest to aviation researchers who could use these scenarios and findings to study further AAM services in airspace.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:55:54Z
      DOI: 10.1177/03611981221103237
       
  • Evaluation of Small Uncrewed Aircraft Systems Data in Airfield Pavement
           Crack Detection and Rating

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      Authors: Md Abdullah All Sourav, Masrur Mahedi, Halil Ceylan, Sunghwan Kim, Colin Brooks, David Peshkin, Richard Dobson, Matthew Brynick
      Abstract: Transportation Research Record, Ahead of Print.
      Current practice for airport Pavement Management Program (PMP) inspection relies on visual surveys and manual interpretation of reports and sketches prepared by inspectors in the field to quantify pavement conditions using the Pavement Condition Index method set forth in ASTM D5340. In recent years, several attempts have been made, both by the industry and by airport operators, to use small Uncrewed (Unpersonned/Unmanned) Aircraft Systems (sUAS), or “drones,” to conduct various types of imaging and inspection of airport pavements. As part of a comprehensive study on the use of such sUAS to evaluate airfield pavement conditions, the objectives of this study were to assess the performance of various sUAS platforms and sensors in detecting and rating a subset of crack-based pavement distresses and to evaluate the use of a combination of different sUAS datasets to complement current methods used to support airport PMP. Two airports in Michigan were selected for sUAS data collection, and five sUAS platforms equipped with eight different sensors were flown at these airports at different altitudes to collect red, green, and blue (RGB) optical and thermal data at different resolutions. RGB orthophotos, digital elevation models, and thermal images were visually analyzed to study their usefulness in detecting and rating longitudinal and transverse cracks in flexible/asphalt pavements and longitudinal, transverse, and diagonal cracks, corner breaks, and durability cracks in rigid/concrete pavements. This study demonstrated the capability of using sUAS data in detecting and rating multiple crack-related distresses in both flexible and rigid airfield pavement systems.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:52:34Z
      DOI: 10.1177/03611981221101030
       
  • Investigation of Ground-Penetrating Radar, Impact Echo, and Infrared
           Thermography Methods to Detect Defects in Concrete Bridge Decks

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      Authors: Zachary W. Coleman, Anton K. Schindler
      Abstract: Transportation Research Record, Ahead of Print.
      A reinforced concrete bridge deck is often at risk of many forms of deterioration which affect its service life and maintenance cost. Nondestructive test (NDT) methods have seen increasing use by departments of transportation to locate deterioration in bridge decks before their condition rating becomes critically low and to help plan bridge deck preservation activities. Nonetheless, uncertainty in what forms of bridge deck deterioration each NDT method can identify has posed challenges in best deploying NDT methods for deck condition assessments. Thus, in this study, a full-scale 18 ft by 31 ft reinforced concrete bridge was constructed with defects in the deck simulating reinforcing steel corrosion, delaminations, concrete deterioration, voids, and poorly constructed concrete. The deck was evaluated with ground-penetrating radar, infrared thermography, and impact-echo nondestructive technologies to evaluate their potential for defect detection. Receiver operator characteristic analysis was implemented to quantify the capability of a given NDT method to detect a particular defect. Conclusions concerning which forms of concrete bridge deck deterioration each NDT method can detect were developed. It was found that of the three NDT methods considered, impact-echo testing was the most effective to evaluate the condition of bridge decks. Impact echo was able to detect both shallow and deep delaminations as thin as 0.01 in., shallow corrosion-induced delaminations, concrete deterioration, and some of the shallow voids; however, it was unable to detect deep voids, poorly constructed concrete, and mildly deteriorated concrete.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:41:54Z
      DOI: 10.1177/03611981221101027
       
  • Blowover Risk Assessment for Tractor-Trailer Trucks in High Winds Using a
           Blowover and Statistical Model

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      Authors: Adarsha Neupane, Noriaki Ohara, Kathy Ahlenius
      Abstract: Transportation Research Record, Ahead of Print.
      Tractor-trailer blowover crashes caused by strong winds are a major concern for the safety of their operators and others sharing the road. These crashes also trigger highway closures resulting in considerable economic impact. This study presents a blowover model based on stability forces that integrates the wind field, road geometry, and vehicle specifications to provide a critical vehicle speed for blowovers. A high-frequency sonic anemometer was deployed at the study area which witnessed three blowover crashes during the study period. The results showed that the critical vehicle speed from the model dipped below the posted speed limit at the time of blowovers for all three blowover crashes. The risk of a blowover crash was quantified as an exceedance probability of the fitted distribution to the temporal critical vehicle speed variations based on the high-frequency wind data within every 15-min time window. This framework, when applied to a stretch of road, was able to demonstrate the ability to identify the instances and the locations of higher blowover risk using wind measurements from the more prevalent mechanical anemometers.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:38:13Z
      DOI: 10.1177/03611981221100533
       
  • Dynamic Surrogate Trip-Level Energy Model for Electric Bus Transit System
           Optimization

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      Authors: Ahmed Foda, Moataz Mohamed, Mohamed Bakr
      Abstract: Transportation Research Record, Ahead of Print.
      The introduction of electric mobility solutions mitigates transportion-related greenhouse gas emissions. Transit buses are considered a promising candidate for electrification. This study contributes to the growing literature on battery-electric buses (BEBs) and aims to quantify the optimal allocation of BEB infrastructure and charging schedules. A generic model for the charging capacity and scheduling of the BEB network is developed. The proposed model proposes an algorithm for the calculation of trip-level BEB energy consumption based on a surrogate model-based space mapping algorithm. Instead of using vehicle simulators or constant values for the energy consumption rate for each trip, the input space mapping has been applied to a simple coarse model to build an accurate surrogate model. The proposed algorithm is tested on the bus transit network in Belleville City in Canada considering BEBs using both Flash and Opportunity charging. The results show the efficiency of the proposed model and highlight the impact on the optimization results of calculating the trip-level energy consumption compared with the traditional methods.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:36:55Z
      DOI: 10.1177/03611981221100242
       
  • Joint Model of Transit Usage Frequency and In-Vehicle Safety Perception
           During the COVID-19 Pandemic

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      Authors: Sk. Md. Mashrur, Brenden Lavoie, Kaili Wang, Patrick Loa, Khandker Nurul Habib
      Abstract: Transportation Research Record, Ahead of Print.
      Social distancing strategies and strict hygiene adherence during the pandemic have added an extra dimension to the safety requirements of transit usage. Thus, travelers’ altered safety perceptions, which can affect transit usage, need to be assessed for effective policy decisions for the post-pandemic period. This study examined the interaction between in-vehicle safety perception and transit usage using an integrated approach by jointly modeling them, considering the fear of virus infection. A multivariate ordered probit model was developed for the investigation using a dataset collected through a web-based travel survey conducted in the Greater Toronto Area, Canada. The results reveal that, along with socioeconomic attributes, many pandemic-related variables and latent attitudinal factors affect the propensity to use transit. It is observed that those having a better safety perception of the bus are more inclined to use transit more frequently than others. Apart from safety perception, those who were more cautious, over the age of 34, and shifted to working from home during the pandemic had an adverse propensity to use transit. However, a higher propensity toward transit usage was observed for pre-pandemic transit users and for those who had a higher level of satisfaction with transit attributes during the pandemic. A similar tendency was also observed for fully vaccinated residents.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:33:54Z
      DOI: 10.1177/03611981221100241
       
  • Influence of Demographic Disparities on Seat Belt Compliance in an Urban
           Area (Washington, DC)

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      Authors: Stephen A. Arhin, Babin Manandhar, Melissa Anderson
      Abstract: Transportation Research Record, Ahead of Print.
      This study evaluated the potential influence of demographic factors on seat belt compliance rates in an urban area. Washington D.C., which is the capital of the United States, is an urban area with mixed and diverse population. The city (and all states) conducts seat belt compliance surveys annually as a requirement of the National Highway Traffic Safety Administration (NHTSA). This article used compliance rates obtained from the field for 2014 through 2020 and matched those with demographic data for the same timeframe. The demographic data for the city was obtained from the United States Census Bureau. Demographic variables including race, educational and income levels for the eight wards in Washington D.C. we extracted for analysis. Overall, seat belt compliance usage in Washington ranged from 93% to 95.7% between 2014 and 2020. Approximately 42.3% of its population are Caucasian while 43.9% are African Americans with the remaining being Asian, Hispanics and other races. In addition, seat belt usage was reported by ward. Using single factor analysis of variance, it was determined that compliance rates in the wards were not statistically influenced by race, educational level, or income level at 5% level of significance. However, when comparing yearly seatbelt compliance from 2014 to 2020, the compliance rates of 2014 versus 2019, and 2014 versus 2020 were determined to be statistically different. Seat belt use should be encouraged for everyone in all jurisdictions. The analysis shows that, in this urban area, the three demographic variables do not have any influence on the compliance rates.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:26:53Z
      DOI: 10.1177/03611981221099514
       
  • Structural Performance of an Asphalt Pavement Containing Cold Central
           Plant Recycling and Full-Depth Reclamation

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      Authors: Brian K. Diefenderfer, Gerardo Flintsch, Wenjing Xue, Fabrizio Meroni, Ilker Boz, David Timm
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement recycling techniques are often perceived as only applicable to lower traffic volume roadways. However, recent studies have shown their potential for long service lives in higher traffic volume applications. This study documented the response of an asphalt pavement section, constructed using full-depth reclamation (FDR) and cold central plant recycling (CCPR), on a portion of I-64 in Virginia reconstructed between 2016 and 2019. The pavement section was instrumented and the response was compared with a similarly instrumented pavement section (Section S12) placed at the National Center for Asphalt Technology (NCAT) Test Track in 2012. Previous studies have shown that Section S12 is a long-life pavement and it carried 30 million equivalent single axle loads (ESALs) while showing no evidence of deterioration at the pavement surface or from installed instrumentation. The results from the I-64 Segment II project showed that it had much lower horizontal strain values at the bottom of the asphalt layers but slightly higher vertical pressure values on top of the subgrade when compared with NCAT Section S12. Despite the slightly higher values (about 1 pounds per square inch [psi] difference), the vertical pressure on top of the subgrade was very low for both pavement sections. The study confirmed that a recycled pavement section could be constructed and result in low strain and pressure values and is expected to have a long service life in a high traffic volume environment.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:25:33Z
      DOI: 10.1177/03611981221099511
       
  • Structural Considerations and Implications Related to Foundation Movements
           in AASHTO LRFD

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      Authors: Naresh C. Samtani, John M. Kulicki
      Abstract: Transportation Research Record, Ahead of Print.
      In the United States, highway bridge design practice is based on the LRFD method developed by AASHTO. In AASHTO LRFD, which is based on the concept of limit states, the effect of foundation movements on structural elements is expressed as a force effect rather than a geotechnical resistance. In fact, all design codes worldwide recognize this observation by including a representation of structural effects of foundation movements as a force. AASHTO LRFD uses the designation “SE” for the geotechnical demands to be considered. An associated load factor, γSE, is specified for each load combination where SE is applicable. The product of γSE and SE is the factored demand, or factored force. The structural effect of foundation movements is manifested in the form of additional force effects such as induced torques, moments, and shears in a bridge structure that can lead to adverse consequences such as cracking. In AASHTO LRFD, the SE load factor occurs in four out of the five load combinations for Strength Limit State and three out of the four load combinations for Service Limit State. This paper presents a study that explores the structural considerations and implications related to use of SE load factor and the effects of foundation movements in AASHTO LRFD.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:23:33Z
      DOI: 10.1177/03611981221099016
       
  • Enhancement of Highway Conditions during Winter Weather Operations through
           Coupling Raised Pavement Markers with Rumble Strips

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      Authors: Md Al-Amin, Vivek Turkar, Mike Rung, Raissa Douglas Ferron
      Abstract: Transportation Research Record, Ahead of Print.
      The use of snowplows in northern Texas frequently results in the loss of retroreflective raised pavement markers (RPMs). The loss of RPMs is not only costly but also creates unsafe driving conditions during inclement weather. Pavement sections in many regions across the state of Texas often use a centerline rumble strip for safety. Traditionally, these rumble strips have precluded the use of metal-encased RPMs (i.e., snowplowable RPMs). This paper is focused on determining the efficacy of inserting commercially available RPMs into the trough regions of the rumble strips, and thus enabling the rumble strips to be multifunctional by not only providing a sound warning to drivers passing over the centerline but also giving nighttime lane delineation visibility to drivers by preventing the loss of RPMs because of snowplows. Field screening studies on small roadway segments and pilot implementation in a couple of highway segments in northern Texas were conducted. The studies reveal that embedding RPMs in existing rumble strips can be a viable approach for centerline delineation of highways that mitigates the issues of dislodgement of RPMs as a result of snowplow operations.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:19:34Z
      DOI: 10.1177/03611981221098658
       
  • Road Grade Estimation Based on Power Demand Difference of Heavy-Duty
           Diesel Trucks for Emission Estimation

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      Authors: Xin Wang, Guohua Song, Yizheng Wu, Zhiqiang Zhai
      Abstract: Transportation Research Record, Ahead of Print.
      Road grades have significant impacts on the emissions of heavy-duty diesel trucks (HDDTs), even in the same operating mode. Existing gradient identification methods are time-consuming and difficult to conduct for entire road networks; moreover, few previous studies have considered uncertainty of HDDT emissions caused by various road grades. In this study, an estimation method for road grade was developed based on second-by-second field operating data, with noise reduction performed using the Kalman filter. The consistency and symmetry of the road grade calculated by the proposed method were then analyzed. Finally, differences in emission rate and emission factor for carbon dioxide (CO2), carbon monoxide (CO), total hydrocarbon (THC), and nitrogen oxides (NOx) under various grades were compared. The results indicated that the grade recognition results of each truck were consistent, with an average grade difference of 0.153%. Based on symmetry analysis of the estimation results in opposite directions, the two opposite road grades were found to have a strong negative correlation, and the average error of the grade was 0.125%. Pollutant results showed the emission rate of CO was most affected by grade, followed by NOx, and THC was the least affected. The emission factors of CO2, CO, THC, and NOx were found to increase by 32.4% to 82.8%, 75.6% to 198.4%, 19.9% to 39.9%, and 73.1% to 186.3%, respectively at 1.0%, 2.0%, and 3.0% gradients compared with 0.0% gradient. This study can improve the estimation accuracy for HDDT emissions, especially in areas with undulating terrain such as mountains and hills.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:17:33Z
      DOI: 10.1177/03611981221098400
       
  • Heterogeneity Analysis of Operating Mode Distribution for Modeling Energy
           Consumption of Light-Duty Vehicles

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      Authors: Leqi Zhang, Guohua Song, Zeyu Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      The use of vehicle operating mode (OpMode) distribution is widely accepted for estimating energy consumption and emissions in the Motor Vehicle Emission Simulator (MOVES) model. However, the heterogeneity of driving behavior may lead to errors when using the default OpMode distribution. To improve the accuracy of energy consumption estimations, it is necessary to recognize the heterogeneity in OpMode distribution among different driving behaviors. With this aim, this paper designs a speed-specific indicator of energy efficiency reflecting driving behavior based on the speed-specific vehicle-specific power (VSP) distribution. The paper uses field data from 26,082 drivers recorded second by second during workdays. It also discusses the intra-heterogeneity and inter-heterogeneity of driving behavior based on unsupervised algorithm clustering. The findings of this paper are as follows. (1) The speed-specific VSP distribution clearly reflects the differences in energy efficiency of individuals’ driving behavior. (2) The energy efficiency indicator reflects the multidimensional inter-heterogeneity and intra-heterogeneity of driving behavior. (3) Drivers’ varied driving behavior causes heterogeneity in energy efficiency at different speeds, possibly causing an error of 6.34% in the emissions estimations. (4) Drivers of electric vehicles (EVs) and hybrid electric vehicles (HEVs) show more aggressive driving behaviors than drivers of conventional vehicles (CVs), which may cause an energy estimation error of over 6% for EVs and HEVs. Thus, the OpMode distribution of EVs, HEVs, and CVs should be modeled separately for on-road energy estimations.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:12:53Z
      DOI: 10.1177/03611981221098397
       
  • Understanding the Relationships Among E-scooter Ridership, Transit Desert
           Index, and Health-Related Factors

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      Authors: Junfeng Jiao, Nathaniel Degen, Amin Azimian
      Abstract: Transportation Research Record, Ahead of Print.
      This study aims to analyze electric scooter (e-scooter) markets in transit deserts and oases in the U.S. The four cities of Austin, Chicago, Portland, and Minneapolis were selected as case studies to determine the prevalence of e-scooter rides as related to locations with limited public transportation options. A t-test was performed to analyze the difference in the number of e-scooter rides between the transit deserts and transit oases. Overall, the arithmetic means of the e-scooter rides between the transit deserts and transit oases were not significantly different in Austin, Chicago, and Portland. The results confirm that the transit index score was among the top three predictors of trips in Austin, Minneapolis, and Portland. In Chicago, health-related characteristics such as crude prevalence of arthritis, diabetes, and obesity were found to be the most important predictors of trips in Chicago.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:09:53Z
      DOI: 10.1177/03611981221097094
       
  • Capitalizing on Drone Videos to Calibrate Simulation Models for Signalized
           Intersections and Roundabouts

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      Authors: M. Shoaib Samandar, Gyounghoon Chun, Guangchuan Yang, Thomas Chase, Nagui M. Rouphail, George F. List
      Abstract: Transportation Research Record, Ahead of Print.
      Simulation is an indispensable tool for the assessment of highway-related capital investments and operational changes. Model calibration, a challenging task in any simulation study, is a crucial step. The model’s robustness, accuracy, and quality are directly dependent on it. Many parameters exist, and field observations are often lacking to aid in their correct specification. Recently, videos from drones have created a uniquely powerful way to aid this process. Observations of the inputs (demand), outputs (vehicles processed), processing rates (e.g., saturation flow rates), and performance results (times in system, queue dynamics, and delays) are all available simultaneously. For signalized intersections, only the signal timing events are missing, and those data can be obtained from signal timing logs. This paper illustrates how modeling teams can use drone data to calibrate model parameters pertaining to intersection operation. It shows how saturation flow rates can be adjusted for signalized intersections so that queue dynamics and delays can be matched. For roundabouts, it illustrates how critical gaps and move-up times can be adjusted to match field observations of performance. Three real-world settings with associated drone data are used as case study examples.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:06:10Z
      DOI: 10.1177/03611981221096120
       
  • Examination of Recent Pedestrian Safety Patterns at Intersections through
           Crash Data Analysis

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      Authors: Dania Ammar, Yueru Xu, Bochen Jia, Shan Bao
      Abstract: Transportation Research Record, Ahead of Print.
      Pedestrians are the most vulnerable road users and are at risk of severe consequences when involved in traffic accidents. The purpose of this research is to determine the factors that have significant impacts on the increasing likelihood of pedestrians being seriously injured or killed when involved in a collision with a single vehicle at an intersection over a recent 6-year period. Both 2013–2015 General Estimates System (GES) and 2016–2018 Crash Report Sampling System (CRSS) crash data were used in the analysis. Logistic regression models for the two crash datasets showed that there were four common significant variables affecting pedestrians’ injury levels. The following pairwise comparisons of these common significant factors using the Wald chi-square statistic test showed similar log-odds with few exceptions, suggesting that these affecting factors share similar effects from 2013 through 2018. In both datasets, results showed that a high likelihood of pedestrians’ severe injuries was associated with pedestrians older than 25, dark lighting conditions, light trucks and buses, and vehicles’ straight maneuver. Furthermore, the GES data distinguished further factors imposing higher threats on pedestrians as being drivers’ 19–25 age group, speeding, pedestrians’ roadway crossings maneuvers, and rain conditions. Crashes that occurred at intersections with more than two lanes or during summertime had significantly higher odds of resulting in severe injuries for pedestrians than crashes at two-lane intersections or during wintertime, respectively, in the CRSS dataset. Results of this study contribute to a better understanding of the recent changes in pedestrian safety at intersections and potential countermeasure design suggestions.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:04:07Z
      DOI: 10.1177/03611981221095513
       
  • Application of Autonomous Vehicles for Automated Roadside Safety
           Assessment

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      Authors: Dmitry Manasreh, Munir D. Nazzal, Sk Abu Talha, Eshaan Khanapuri, Rajnikant Sharma, Donghoon Kim
      Abstract: Transportation Research Record, Ahead of Print.
      Road edge drop-off has well known impacts on the safety of the traveling public and roadway service life. Continuous inspection of roadsides is therefore needed to monitor their condition. Autonomous vehicles (AVs) are increasing in number and have the potential to be used for road and roadside condition data collection. This study explored the use of AVs to assess road edge drop-off. To this end, the ability and accuracy of a research grade autonomous vehicle platform built on a passenger car was used to determine road edge drop-off. Data were collected for the roadside along a state highway in Ohio using the different sensors of the vehicle platform, including a Light Detection and Ranging (lidar) sensor. A 160-m (525-ft) long section of the highway was selected and surveyed using a high accuracy stationary terrestrial laser scanner to obtain the topographic map of the highway and its sides. The lidar data were analyzed using fully automated deep learning methods to determine the edge drop-off severity along the selected section. The analyzed lidar data were compared with those obtained using the high accuracy stationary terrestrial laser scanner. The results of this study showed that the autonomous vehicle platform can be used successfully to assess the road edge drop-off with excellent accuracy, particularly when using end-to-end deep learning methods for analyzing the collected data.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T06:03:08Z
      DOI: 10.1177/03611981221095090
       
  • Deep Learning Model for Crash Injury Severity Analysis Using Shapley
           Additive Explanation Values

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      Authors: Yashu Kang, Aemal J. Khattak
      Abstract: Transportation Research Record, Ahead of Print.
      Analysis of traffic crash and associated data provides insights and assists with identification of cause-and-effect relationships with crash probabilities and outcomes. This study utilized eight years of police-reported Nebraska crash data using a deep neural network (DNN) to model crash injury severity outcomes. Prediction performances and model interpretability were examined. The developed DNN excelled in prediction accuracy, precision, and recall but was computationally intensive compared with a baseline multinomial logistic regression model. While the lack of interpretability power of deep learning models limits their usage, the adoption of SHapley Additive exPlanation (SHAP) values was an improvement. Conclusions drawn from the DNN model are generally consistent with the estimated baseline model. For instance, the variable total number of pedestrians was found significant in both scenarios of the multinomial logit model indicating a strong relationship with more severe crash injury outcomes. It was also found important in all three sets of parameters in DNN. SHAP values also allow in-depth analysis of prediction results on a single observation, such as the variable crash type (same direction sideswipe) contributing to classifying a single observation as property damage only. These findings are beneficial for making more informed transportation safety-related decisions.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T05:50:48Z
      DOI: 10.1177/03611981221095087
       
  • Six Decades of Roadside Encroachment Modeling

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      Authors: Malcolm H. Ray, Christine E. Carrigan
      Abstract: Transportation Research Record, Ahead of Print.
      A vehicle encroaches whenever it leaves the lanes of the traveled way and enters the roadside or median. Leaving the traveled way may result in rolling over on roadside terrain or striking a fixed object, so understanding the nature of vehicle encroachments is an important aspect of roadside design. A variety of efforts over the last 60 years have resulted in the collection of data that have been used to model encroachments. This paper summarizes these prior studies, compares the results, and presents recommendations for the best available encroachment models for use in the design of roadsides and medians.
      Citation: Transportation Research Record
      PubDate: 2022-06-25T05:50:29Z
      DOI: 10.1177/03611981221101026
       
  • Evaluation of Steel Bridge Details for Susceptibility to
           Constraint-induced Fracture

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      Authors: Domenic A. Coletti, Anthony P. Ream, Brandon W. Chavel
      Abstract: Transportation Research Record, Ahead of Print.
      Historically, reports of significant problems associated with details featuring intersecting welds in steel bridges have been rare. However, there have been several notable cases involving constraint-induced fracture (CIF). CIF is a particular concern since it can occur in a brittle fashion, suddenly and without warning (different from other types of problems, such as corrosion or fatigue crack growth, for example). CIF generally occurs in details that feature a high degree of constraint (leading to a high level of stress triaxiality), in combination with high levels of tensile stress (particularly from residual stresses) and the presence of a notch-like or crack-like planar discontinuity approximately perpendicular to the primary flow of tensile stress. Details subject to a high degree of constraint often feature the intersection of two or three welded structural elements. The distinction between “intersecting welds” and “constraint resulting from the intersection of welded structural elements” is important. This paper summarizes the findings and recommendations of a recently completed report reflecting the current state of knowledge about CIF in steel bridges. The report is based on a review of previous research, industry practices, and the input of a panel of steel bridge industry experts. It provides a review of the fundamental principles of CIF and presents a general procedure for evaluating steel bridge details for susceptibility to CIF, including examples of assessments of commonly used steel bridge details.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:23:47Z
      DOI: 10.1177/03611981221103228
       
  • Learning-Based Model for Evaluating the Impact of Neighborhood Design on
           Travel Behavior

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      Authors: Abdul Rahman Masoud, Ahmed Osman Idris, Gordon Lovegrove
      Abstract: Transportation Research Record, Ahead of Print.
      This research developed an agent-based model that evaluates the impact of neighborhood design on travel behavior while accounting for habit formation, social interactions, various levels of information provision, and awareness of transport and land use system changes. The developed model employs a framework that integrates random utility maximization theory with reinforcement learning concepts to account for the bounded rationality and knowledge learning process. Moreover, the model utilizes the diffusions of innovations theory to simulate how agents propagate information across family members and co-workers. It also adds a time dimension to the modal shift process, which could be used to indicate the relative duration to reap the full benefits of proposed scenarios. The model was applied to a neighborhood in Kelowna, British Columbia, Canada, to assess the impact on travel behavior of the SMARTer growth principles. The results showed that retrofitting non-motorized networks has more impact on modal shift than retrofitting road networks. This implies that infrastructure investments related to providing more accessibility for non-motorized users may be more socially and sustainably profitable than investments in policies targeting auto users. In addition, the results revealed that land use policies led to higher modal shift to non-motorized modes compared to retrofitting the transportation network, which highlights the importance of integrating land use and transportation planning. Similarly, the results demonstrated that transportation demand management policies can provide a positive stimulus to commuters to maintain familiarity with active transportation (AT) modes, which led in the presented case study to an increase in AT modal share.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:21:47Z
      DOI: 10.1177/03611981221102154
       
  • Developing a Disaster Chain Method to Evaluate Transportation Systems: A
           Pilot Study of Predicting Debris Blockages in Disaster-Response Road
           Systems

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      Authors: Siao-Syun Ke, Chih-Hao Hsu
      Abstract: Transportation Research Record, Ahead of Print.
      Suitable transportation systems are vital for the functioning of urban areas. Such systems connect all major locations, including residential and commercial locations, in these areas. The effectiveness of the response of an urban area to an earthquake depends on the road system in the area. A feasible and efficient approach to evaluating the capacity of road systems to allow safe and efficient emergency transportation for affected residents in the aftermath of an earthquake should be developed. Ground transportation systems are vulnerable to earthquakes. For example, ground motion in the 1994 Northridge, 1995 Kobe, 1999 Chi-Chi, and 2018 Hokkaido earthquakes caused severe damage to urban roads and bridges. Moreover, for areas with a high building density that are prone to high-intensity earthquakes, it is important to be able to estimate the risk of road blockage caused by collapsed buildings. In the present study, a disaster impact chain was established to evaluate the probability and effects of buildings collapsing in an earthquake. This chain was used as the basis for a road blockage model and for the formulation of suitable procedures and methods for earthquake response. The results of this study indicate that buildings in strong-motion zones are severely damaged by high-intensity earthquakes. Falling debris from these buildings can lead to the blockage of rescue roads, delaying the transport of injured individuals to hospital after an earthquake. The results of this study can aid authorities in making decisions related to transportation system management during earthquake disasters.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:20:08Z
      DOI: 10.1177/03611981221102152
       
  • Minimizing the Effects of Urban Mobility-on-Demand Pick-Up and Drop-Off
           Stops: A Microscopic Simulation Approach

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      Authors: Philipp N. Stueger, Fabian Fehn, Klaus Bogenberger
      Abstract: Transportation Research Record, Ahead of Print.
      Short-term disruptions can have a long-lasting negative effect on traffic flow exceeding the duration of the disruption itself. This is especially the case when traffic demand approaches the network’s capacity. On-demand ride-sourcing services like ride-hailing and ride-pooling do not only have an impact on the overall kilometers driven in a network, but also conduct frequent stopping maneuvers to let passengers board and alight. As further growth of such services is expected, municipalities will need to find ways to organize and, if needed, regulate such activities. This paper proposes, evaluates, and discusses two possible methods that can be part of a holistic strategy to mitigate the impacts of frequent mobility-on-demand curbside stops in an urban environment. The first method adapts the positions of stops at an intersection according to real-time signal timings without adding another variable to the already quite complex traffic signal optimization. The second method discusses a temporary reduction of the number of allowed stopping maneuvers on saturated street sections or in other sensitive areas. Both methods are evaluated using microscopic traffic simulation and result in significant reductions of average vehicle delay as well as standard deviation thereof in all investigated traffic demand scenarios. These results indicate that the proposed methods can help to preserve a stable traffic state in situations close to the capacity limit, which is to the benefit of all stakeholders involved.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:18:37Z
      DOI: 10.1177/03611981221101894
       
  • Evaluating Cost Savings from Truck Caravanning

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      Authors: Vasileios Liatsos, Dimitrios Giampouranis, Mihalis Golias, Sabyasachee Mishra, John Hourdos, Razi Nalim, Mark T. Frohlich, Clayton Nicholas
      Abstract: Transportation Research Record, Ahead of Print.
      Truck platooning and related autonomous vehicle coordination concepts have been proposed as sustainable ways to increase profits and improve service quality. Recently the concept of truck caravanning, a hybrid truck platooning with only one truck driver required per platoon, has been proposed in the literature. This paper describes the research effort in developing a model that can estimate the cost savings of truck caravanning. The motivation of the proposed model is to investigate if substantial monetary savings exist to justify the initial capital investment (both in equipment and infrastructure) required for the implementation of the truck caravanning concept. A linear programming model is developed and used to evaluate different size networks. Results from numerical experiments indicate that a caravan size of four trucks or greater is needed for significant cost savings to be achieved and that driver compensation is the most critical factor dictating profitability.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:16:27Z
      DOI: 10.1177/03611981221101890
       
  • Aircraft Insurance Costs Management for Sustainable General Aviation:
           Insights From General Aviation Enterprises in China

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      Authors: Qian Ma, Guojun Wang
      Abstract: Transportation Research Record, Ahead of Print.
      Little research has examined how to effectively reduce general aviation aircraft (GAA) insurance costs (premiums), even though it has grown to be a heavy financial burden adversely affecting the sustainable development of general aviation (GA). In contrast to previous research that dealt solely with airline insurance, this research studies the insurance cost management issue of GAA from the perspective of supply and demand. Specifically, this paper focuses on analyzing significant factors influencing GAA insurance premiums and the degree of incidence with the risk system. This empirical research is based on a unique dataset of GA enterprises in China during 2017 to 2019 and utilizes the second synthetic of gray incidence analysis (SSDGIA) model and entropy weight analysis. First, it is found that the fleet profile, loss record, and individual GA operational performance are the critical elements related to premiums. Additionally, there is an increasing dependence of premiums on direct loss performance. Second, the degree of incidence between premiums and the risk system (
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:15:08Z
      DOI: 10.1177/03611981221101616
       
  • Combined Hub Location and Service Network Design Problem: A Case Study for
           an Intermodal Rail Operator and Structural Analysis

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      Authors: Ralf Elbert, Johannes Rentschler, Jessica Schwarz
      Abstract: Transportation Research Record, Ahead of Print.
      In intermodal transportation, hubs are facilities that perform switching, sorting, connecting, and consolidating functions between many origins and destinations. Hub location problems (HLP) accordingly involve the location of hubs but include abstract network design decisions as well. In the past, the strategic location decision and the more tactical network design decision, in the form of a service network design problem (SNDP), have been considered separately. However, the SNDP is based on an existing hub network and the HLP could benefit from a more detailed network design. For this reason, this paper presents the combined hub location and service network design problem (C-HL-SNDP), which considers the strategic and tactical planning dimensions in an integrated manner. In a case study of a German intermodal operator, the paper shows that integrated modeling can be used to produce very good and realistic solutions that generate added value. The combined model with a classical HLP approach is compared and a structural analysis of the solution properties is performed. With this, it can be shown that the different consideration of economies of scale and economies of density lead to fundamentally different solutions.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:13:47Z
      DOI: 10.1177/03611981221101391
       
  • Resilience Analysis of New York City Transportation Network After Snow
           Storms

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      Authors: Reza Mirjalili, Hojjat Barati, Anil Yazici
      Abstract: Transportation Research Record, Ahead of Print.
      This study presents a quantitative analysis of the snow storm resilience of New York City (NYC) by utilizing network science-based system performance functions and publicly available datasets, that is, New York Department of Sanitation’s snow removal operation and NYC traffic speed data. Several graph theory based metrics and some heuristic metrics are utilized to calculate the temporal changes in transportation network functionality along eight snow events. The NYC transportation network is updated based on snowplow movements, and the performance indexes (PIs) for all metrics are calculated throughout the snow storm timeline. Since PI graphs rely on network topology but not the actual traffic conditions, the times that the system bounces back to “regular” conditions (i.e., time-to-recovery/resilience) are calculated based on the similarity between hourly speed distributions on NYC roads. Bhattacharyya distance and Kolmogorov–Smirnov test are used as measures for distribution similarity. Accordingly, the PI values that correspond to the recovery times are also identified. Within the limitations of the size of the snow storm sample, the findings show that less data-intensive graph theory metrics can be used to estimate the transportation network performance—an estimation that would require extensive and detailed data otherwise. Accordingly, these metrics can be used to make resilience predictions for future events through simulations on modified network topology, and help make recovery forecasts to inform local governments and businesses on when to resume regular operations.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:13:08Z
      DOI: 10.1177/03611981221101034
       
  • Toward Formalization and Monitoring of Microscopic Traffic Parameters
           Using Temporal Logic

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      Authors: Mariam Nour, Mohamed H. Zaki
      Abstract: Transportation Research Record, Ahead of Print.
      Smart mobility is transforming the way the current transportation network is envisioned. It holds the promise of a more sustainable, safer, and efficient future for commuters. Nevertheless, traffic management centers are constantly facing the challenges of ensuring that transportation system components are operating as expected and in a safe manner. As a result, research efforts on improving traffic monitoring aim to design and implement novel approaches for safety applications. In this paper, we adopt formal methods to specify and apply reason to the traffic network’s complex properties. Formal methods provide a framework to rigorously define the safe operation of the traffic network by capturing non-conforming travel behavior, exploring various possible states of vehicular traffic, and detecting any irregularities that may arise. In this work, a new approach to traffic monitoring is proposed, which uses specification-based monitoring. We develop monitors that define traffic parameters, such as conforming to speed limits and maintaining appropriate headway. A formal language known as Signal Temporal Logic is used to specify and analyze these traffic rules. The proposed framework is then applied to a calibrated micro-simulated highway network to identify whether individual vehicle trajectories violate or satisfy the proposed specifications. Statistical analysis of the outputs shows that our proposed approach is effective in differentiating between violating and conforming vehicles. This approach can be used by traffic management centers that are seeking to accommodate emerging mobility technologies that are autonomous and connected. In particular, the presented work can be valuable in studying traffic stream properties, identifying possible hazards, and providing valuable feedback for automating traffic monitoring systems.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:12:38Z
      DOI: 10.1177/03611981221100535
       
  • Effects of Oil/Asphalt Emulsion Formulation on Particle Size and Stability

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      Authors: Conglin Chen, Lanqin Lin, Tao Ma
      Abstract: Transportation Research Record, Ahead of Print.
      This investigation evaluated the factors of penetrant types, asphalt contents, and emulsifier contents on the particle sizes of emulsified penetrants, emulsified asphalt, and oil/asphalt emulsions in the emulsion formulation. The particle sizes of emulsions were obtained by laser particle size analyzer tests. The residues of emulsions obtained after the high-temperature evaporative technique were assessed through conventional binder tests such as softening point, penetration, and ductility tests. The storage stability of oil/asphalt emulsions was evaluated as well. Additionally, the molecular dynamics simulation was employed to study the interfacial interaction between materials in the emulsion system at the atomic scale. The results showed the great potential of using the commercial penetrants adopted for this study as alternatives to kerosene in emulsions with smaller particle sizes and better stability. The emulsifier content had significant effects on particle size and stability of emulsions. A higher emulsifier content had positive effects on decreasing the particle sizes and improving the stability of emulsions; however, it negatively affected the ductility of the emulsion residues. The particle sizes were noticed to be highly correlated to stability, emulsifier content, and interfacial formation energy of the emulsions.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:12:03Z
      DOI: 10.1177/03611981221100512
       
  • Accelerated Pavement Testing Validation of a Pavement Response Model Using
           Three-Dimensional Finite Element Analysis Software: Two Case Studies

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      Authors: Fawaz Kaseer, James Greene, Bouzid Choubane
      Abstract: Transportation Research Record, Ahead of Print.
      Accelerated pavement testing (APT) provides valuable information concerning the short- and long-term performance and life expectancy of pavement structures in a very short period as compared to full-scale field tests. Pavement modeling can produce early, reliable, and beneficial guidance that can be used to design and implement future APT experiments or extend the experimental results to similar materials and structures. Combining actual APT experimental data with well-calibrated models can provide complete and thorough investigations while saving agencies time and resources. The main objective of this study is to evaluate the effectiveness and accuracy of the 3D-Move Analysis Software (three-dimensional finite element software [3D FE]) in calculating pavement responses through a comparison with measured pavement responses and distresses from previous APT experiments using the Florida Department of Transportation heavy vehicle simulator (HVS). 3D-Move uses a continuum-based finite-layer approach to calculate pavement responses under various loading conditions. Results indicated that pavement responses, specifically longitudinal horizontal (tensile) strains at the bottom of the asphalt layer and transverse horizontal (tensile) strains at the surface of the asphalt layer, calculated by 3D FE are relatively similar to those measured in APT experiments. The calculated impact of the asphalt mixture properties, loading level, loading temperature, and the distance (offset) from the tire edge on pavement responses was consistent with those measured in HVS testing. Therefore, 3D FE analysis can be effectively used to compare the relative cracking performance of asphalt mixtures and aid in designing practical APT experiments and extending the results to similar asphalt mixtures and pavement structures.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T12:11:34Z
      DOI: 10.1177/03611981221099911
       
  • Pavement Maintenance Program at the Network Level: Mixed-Integer
           Programming with Multiple Objectives

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      Authors: Md Al Amin
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement network conditions deteriorate over the years of use. To keep pavement conditions at acceptable levels, highway agencies plan pavement maintenance and rehabilitation (M&R) programs and perform accordingly. Highway agencies usually face budget variability for pavement M&R activities because of limited resources, economic conditions, and changes in policies. The situation makes it difficult for highway agencies to keep an acceptable pavement condition at the network level. Therefore, it is important for highway agencies to adopt M&R policies that can maximize the network condition as well as handle the deviation of the network condition considering the available maintenance funds. In this paper, a multi-period multi-objective linear integer programming model is proposed. Two objectives, maximization of the average network condition and minimization of deviation of the network condition from an idealized network condition trend, are considered in the formulation. The model is formulated for fixed M&R budgets, as well as for variable M&R budgets. The proposed model provides an M&R program for the pavement network that helps decision makers to manage pavement maintenance programs considering budgetary constraints. A case study examining a network of 45 pavement sections is conducted. The solutions of the fixed-budget and variable-budget model are presented. In addition, the values of the system to the decision maker are discussed. Results show that the proposed model is an attractive way to manage pavement maintenance programs at the network level.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:57:58Z
      DOI: 10.1177/03611981221099910
       
  • Multiperspective Analysis of Pandemic Impacts on U.S. Import Trade: What
           Happened, and Why'

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      Authors: Daniel Smith, Paul Bingham, Daniel Hackett, Jeffrey Smith
      Abstract: Transportation Research Record, Ahead of Print.
      U.S. container ports have experienced unpresented congestion since mid-2020. The congestion is generally attributed to import surges triggered by heavy spending on consumer goods during the COVID-19 pandemic. Port congestion has been compounded by the inability of importers to retrieve, receive, and process all the inbound goods they have ordered, resulting in supply chain shortfalls and economic disruption. How can the shipping industry and government organizations predict the end of the current surge and anticipate future surges' Expected seasonal variations in import volume are associated with peak holiday shopping periods; nonseasonal import surges are signaled by other factors. The research goes beyond transportation data sources to examine broader connections between import volume and indicators of economic and retail industry conditions. The strongest and most useful relationship appears to be between retail inventory indicators and containerized import growth. From January 2018 through July 2021, there was a relatively strong negative correlation between retail inventory- and import TEU indices with a 4-month lag (corresponding roughly to the time between import orders and -arrival). In the 2020 to 2021 pandemic period the negative correlation was stronger, again with a 4-month lag. These findings suggest that observers might anticipate import surges after marked, nonseasonal drops in retail inventories, and that import surges are likely to last until target inventory levels are restored. In a broader sense, an awareness of the linkages between consumer demand, retail chain responses, and containerized import volumes could better inform port, freight transportation, and government planning and policy choices.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:55:12Z
      DOI: 10.1177/03611981221098663
       
  • Autonomous Minibus Service With Semi-on-Demand Routes in Grid Networks

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      Authors: Max T. M. Ng, Hani S. Mahmassani
      Abstract: Transportation Research Record, Ahead of Print.
      This paper investigates the potential of autonomous minibuses which take on-demand directional routes for pick-up and drop-off in a grid network of wider area with low density, followed by fixed routes in areas with greater demand. Mathematical formulation for generalized costs demonstrates its benefits, with indicators proposed to select existing bus routes for conversion with the options of zonal express and parallel routes. Simulations on modeled scenarios and case studies with bus routes in Chicago show reductions in both passenger costs and generalized costs compared with existing fixed-route bus services between suburban areas and the central business district.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:53:52Z
      DOI: 10.1177/03611981221098660
       
  • High-Resolution Fuel Consumption Model for Better Characterizations of
           High-Speed Scenarios

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      Authors: Jianchang Huang, Guohua Song, Zeyu Zhang, Yun Jiang
      Abstract: Transportation Research Record, Ahead of Print.
      A detailed and accurate fuel model fuel consumption model that reflects real-world fuel consumption is required as input for devising and executing a model policy for prospective regulatory tools. The fuel consumption model based on the vehicle-specific power (VSP) has rapidly become the primary development direction since the release of the Motor Vehicle Emissions Simulator (MOVES) model. However, fuel consumption cannot be accurately characterized under high-speed scenarios. This work develops two fuel consumption models for the light-duty (gasoline) vehicles that can better characterize fuel consumption for light-duty vehicles under high-speed scenarios. For model 1, the VSP of −5kW/ton is a crucial turning point. When VSP∈ [−30, −5] kW/ton, the fuel rate is only determined by speed. When VSP∈(−5, 30], the fuel rate will gradually increase with VSP, and the growth characteristics will vary with speed. Model 2 develops the new interpretations for VSP and forms the one-to-one correspondence between the fuel rate and the new VSP. The two models can separately improve the accuracy by 12.2% and 13.8% compared with the conventional model. The fuel factor differences become significant when speed is higher than 65 km/h, which are separately 30.66% and 28.13% higher than the conventional VSP model when the speed is 100 km/h. Further, the fuel factors of the two models for freeways are, respectively, 6.33% and 7.56% higher than the conventional VSP model, and the distinction for arterial, collector, and local street roads is not notable.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:50:51Z
      DOI: 10.1177/03611981221098401
       
  • Factors Affecting Demand Consolidation in Urban Air Taxi Operation

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      Authors: Haleh Ale-Ahmad, Hani S. Mahmassani
      Abstract: Transportation Research Record, Ahead of Print.
      Urban air taxi (UAT) is envisioned as a point-to-point, (nearly) on-demand, and per-seat operation of passenger-carrying urban air mobility (UAM) in its mature state. A high flight load factor has been identified as one of the influential components in the successful operation of UAT. However, the uncertainties in demand, aircraft technology, and concept of operations have raised doubts about the viability of UAT. This study examines the impacts of exogenous parameters, such as demand intensity, demand spread, and ground speed, in addition to design parameters, including aerial speed, maximum acceptable delay, and reservations on average load factor and rate of rejected requests. The dynamic and stochastic problem of UAT fleet operation is studied by implementing a dynamic framework that aims to provide a solution to the problem via a discrete-event simulation. The results highlight the significance of demand spread, ground speed, and maximum acceptable delay in demand consolidation. Therefore, to ensure a high aircraft load factor, the UAT operator should specify the maximum acceptable delay and reservation time window given the demand pattern and ground-based transportation in the network.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:48:41Z
      DOI: 10.1177/03611981221098396
       
  • Estimating Freeway Lane-Level Traffic State with Intelligent Connected
           Vehicles

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      Authors: Xiaobo Liu, Ziming Zhang, Tomio Miwa, Peng Cao
      Abstract: Transportation Research Record, Ahead of Print.
      This paper proposes a methodology for estimating lane-level traffic state for freeways by fusing data from intelligent connected vehicles (ICVs) with fixed detector data (FDD) and probe vehicle data (PVD). With microscopic vehicle trajectories of ICVs and their surrounding vehicles, the proposed methodology integrates a multilane traffic flow model into the data assimilation framework based on extended Kalman filter (EKF), in which traffic measurement models are formulated for ICV data, PVD, and FDD, respectively, to fit their different characteristics. Simulation experiments are conducted to test the performance of the proposed methodology with various penetration rates of ICVs, using a set of simulated ICV data based on the Next Generation SIMulation (NGSIM) data sets. The results demonstrate that by utilizing only 3% to 5% ICVs in the mixed traffic, the proposed methodology could produce an accurate estimate of lane-level traffic speed and a reasonable estimate of lane-level traffic density.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:47:14Z
      DOI: 10.1177/03611981221098395
       
  • Topological Approach for Optimizing Railroad Freight Network Restoration
           after Disruptions

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      Authors: Fei Wu, Paul M. Schonfeld, Bilal Ayyub, Myungseob Kim
      Abstract: Transportation Research Record, Ahead of Print.
      A topology-based method is proposed for optimizing the restoration sequence of damaged components in a disrupted rail freight network. Formulated as a demand-weighted average of reciprocal shortest path lengths, network efficiency is used as an indicator of overall connectivity for origin–destination (OD) pairs having freight demand. With the fixed demand matrix, a given network configuration, and a given disruption scenario, the cumulative loss of network efficiency during the restoration process is computed for each evaluated restoration sequence, using network efficiency values in intermediate network states as well as the duration of each restoration phase (i.e., restoration plus access time). This cumulative loss is treated as a measure of post-disruption network resilience, and is minimized with a simple genetic algorithm (GA) that finds the corresponding optimized restoration sequence, which also determines the optimized restoration schedule. The proposed method is demonstrated in a synthesized numerical case of a small network and a disruption scenario. The GA can find the globally optimal restoration sequence relatively fast, with its effectiveness further verified through exhaustive enumeration for three additional disruption scenarios. Sensitivity analysis results indicate that higher topological centrality and freight throughput of damaged nodes or disruption-induced isolation of some nodes are responsible for higher minimized loss of cumulative efficiency. The optimized restoration sequence tends to prioritize nodes and adjacent links with relatively high freight throughput in normal operation.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:46:04Z
      DOI: 10.1177/03611981221097397
       
  • Effects of Distance and Reliability on Value of Time in Intercity Freight
           Transportation: An Adaptive Experiment in China

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      Authors: Hao Liu, Rong Zhang, Wenliang Jian, Suxiang Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Road–rail container intermodal transportation is considered a solution to reduce the share of truck transportation in China. A modal shift from truck to intermodal alternatives requires a better understanding of freight mode choice behavior and improved estimations of the value of service attributes. This paper focuses on the effects of distance and reliability on the value of time (VOT). An adaptive experiment is conducted on potential customers of intermodal transportation in the Yangtze River Delta area, China. Multinomial logit (binary logit) and mixed logit models are estimated for eight specifications. The results show that shipper characteristics, commodity characteristics, and shipment characteristics significantly influence the mode choice behavior. Specifications with an interaction term between the logarithm of distance and transportation time perform better. The VOT of short-distance transportation is higher than that of long-distance transportation. The rate of VOT reduction decreases with increasing distance. In addition, incorporating the reliability variable in model specifications leads to a more homogeneous random parameter distribution of time and a lower VOT. This study helps intermodal operators to optimize product and design pricing strategies. Moreover, the proposed measures help to promote the modal shift from truck to road–rail container intermodal transportation.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:44:23Z
      DOI: 10.1177/03611981221097096
       
  • Performance Evaluation and Characterization of Extracted Recycled Asphalt
           Binder With Rejuvenators

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      Authors: Mahmoud Samara, Daniel Offenbacker, Yusuf Mehta, Ayman Ali, Mohamed Elshaer, Christopher Decarlo
      Abstract: Transportation Research Record, Ahead of Print.
      Rejuvenators are used in the asphalt industry to improve the performance and durability of aged binders and facilitate the use of recycled asphalt materials. The purpose of this study was to evaluate the impact of rejuvenator type and dose on the laboratory performance of asphalt binders. For this study, recycled asphalt pavement (RAP) and extracted RAP binder were obtained from an airfield reconstruction project located in Atlantic City, NJ. One petroleum-based (aromatic extract) and three organic-based (corn oil, tall oil, and modified vegetable oil) rejuvenators were evaluated in this study. Each rejuvenator was used at two different rejuvenator doses (6% and 12% by total RAP binder weight) and was aged at three different levels. Performance grade testing, frequency sweep tests, critical temperature differential (ΔTc ), and Fourier transform infrared spectroscopy (FTIR) tests were conducted. Results showed that the use of rejuvenators lowered the high and low performance grade of extracted RAP binders, in particular organic-based rejuvenators had a greater impact on the performance grade. ΔT c was also improved through the use of rejuvenators. In fact, the extracted RAP binder exceeded the high severity ΔTc threshold (−5°C), whereas the rejuvenated RAP binders improved ΔT c to values greater than the low severity threshold (−2.5°C). Similar findings were observed from the Glover-Rowe parameter as well, in which rejuvenated RAP binders improved the cracking resistance of the extracted RAP binder. When assessing the aging susceptibility, modified vegetable oil and corn oil rejuvenators showed the smallest change in performance between aging levels.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:43:44Z
      DOI: 10.1177/03611981221097091
       
  • Metro Speed Profile Optimization Considering Passenger Comfort: Model and
           Application

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      Authors: Dimitrios Roumpekas, Christina Iliopoulou, Konstantinos Kepaptsoglou
      Abstract: Transportation Research Record, Ahead of Print.
      Efficient timetable and speed profile determination are critical in improving the energy performance of railway systems. Relevant speed profile optimization models for railway systems typically aim at the minimization of energy consumption and passenger waiting times. Still, passenger comfort during the accelerations and decelerations of the train is significant for service quality, yet so far has been largely overlooked in relevant models. In this context, this study proposes a speed profile optimization model considering the effect of acceleration on passengers. Three distinct speed profiles are developed based on real-world data and used as input for the model. Subsequently, an integer linear programming model is formulated, minimizing the running time and energy consumption, and maximizing passenger comfort. The proposed model is applied to Athens (Greece) metro line 3 (blue line). Results corroborate the effectiveness of the proposed model in reducing travel times, while taking into account passenger comfort.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:41:04Z
      DOI: 10.1177/03611981221096443
       
  • Weather-Based Lane-Change Microsimulation Parameters for Safety and
           Operational Performance Evaluation of Weaving and Basic Freeway Segments

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      Authors: Anik Das, Mohamed M. Ahmed
      Abstract: Transportation Research Record, Ahead of Print.
      It is well recognized that adverse weather conditions have significant negative impacts on safety and mobility of transportation systems. Microsimulation modeling has emerged as a cost-effective tool to quantify the safety and operational effects arising from adverse weather. Developing a realistic microsimulation model necessitates adjusting driving behavior models through trajectory-level data. This study contributes a methodology to update lane-change parameters to develop weather-specific microsimulation models based on different freeway facilities, and ultimately evaluate the safety and operational performance of the roadways. Representative parameters in various weather and facility types were extracted using an automated process. As part of the comprehensive assessment of the adjusted parameters, a weaving section and a basic freeway segment on Interstate 80 in Wyoming were identified as potential candidates. The safety and operational analyses were conducted using VISSIM. Various simulation scenarios were designed based on the field traffic flow data. The safety analysis using three surrogate measures of safety including time-to-collision, deceleration rate to avoid collision, and post encroachment time revealed that adverse weather generated a higher number of conflicts than did clear weather for both facilities. The operational analysis suggested that adverse weather produced lower average speed and higher total travel time and delay than clear weather. The demonstrated methodology could be used in assessing various connected vehicle applications associated with lane change in microsimulation from safety and operational perspectives and could be adopted by transportation agencies to develop weather-based microsimulation models.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:39:44Z
      DOI: 10.1177/03611981221096111
       
  • Estimating Potential Employment Impact of the Charging Infrastructure used
           to Support Transportation Electrification in the United States

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      Authors: Yue Ke, Marianne Mintz, Yan Zhou
      Abstract: Transportation Research Record, Ahead of Print.
      Increased concern over greenhouse gas (GHG) emissions and climate change is encouraging many states, companies, and consumers to focus on zero emission vehicle technologies such as electric vehicles (EVs). A major barrier to widespread EV adoption, however, is range anxiety as there is currently insufficient electric vehicle supply equipment (EVSE) available. Although not the primary goal primary of EVSE installations, one of their side effects and a goal of President Biden’s infrastructure plans is their impact on employment, both initially as stations are developed and activated and over time and as they continue to provide charging to a growing population of EVs. This study estimates the potential employment effects of the deployment and operation of President Biden’s goal of installing 500,000 charger plugs. To do this, we develop an input-output (IO) based model called JOBS EV. Unlike existing analyses, JOBS EV includes both the employment effects caused by the front-of-meter EVSE equipment needed at a particular site and the back-of-meter or upstream equipment used to obtain power from the existing utility’s distribution network. The model results indicate that approximately 1.1 million new jobs will be created over a 10-year period. The modeling process outlined in this paper, in addition to the results presented, may be useful to stakeholders involved in transportation decarbonization efforts as another means of evaluating the costs and benefits of pursuing electrification. Further work is needed to improve the underlying IO model to better account for nascent industries, to accurately calculate local share percentages, and to capture the employment effects of the complete EVSE life cycle.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:38:04Z
      DOI: 10.1177/03611981221095750
       
  • Application of Emerging Data Sources for Pedestrian Safety Analysis in
           Charlotte, NC

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      Authors: Ian Hamilton, Kristin Kersavage, R.J. Porter, Vikash Gayah, Josie Sanchez, Keith Smith, Carol Tan, Ana Maria Eigen
      Abstract: Transportation Research Record, Ahead of Print.
      Pedestrian safety is a growing concern for transportation planners and safety engineers at both local and state levels. Continued advancements in data availability, data integration abilities, and analysis methodologies offer new opportunities to identify factors influencing pedestrian safety and to quantify their effects to inform data-driven road safety management. The main objective of this study was to spatially integrate Highway Safety Information System data with multijurisdictional and emerging datasets to analyze two measures of pedestrian safety performance in Charlotte, NC: (1) the severity of a pedestrian crash that has occurred, and (2) the probability that a pedestrian crash will occur on a given roadway segment. To accomplish the objectives, the study explored several high-priority research topics in safety data and analysis, including pedestrian exposure analysis and probe data integration. The research team developed a pedestrian count model to predict pedestrian volumes at locations without pedestrian counts and integrated speed information from probe data to supplement other roadway and contextual transportation data available from several agencies. Pedestrian exposure at a given intersection was found to be significantly influenced by demographic and socioeconomic characteristics, employment, land use, sidewalk presence, transit access, and roadway and intersection characteristics. The project team identified numerous significant factors that influenced pedestrian crash severity and probability, including outputs from the pedestrian exposure model, observed vehicle speeds, traffic volumes, intersection proximity, and other crash-related factors. The results could be used to identify locations that are more susceptible to pedestrian safety issues.
      Citation: Transportation Research Record
      PubDate: 2022-06-23T11:36:10Z
      DOI: 10.1177/03611981221093330