Subjects -> ENGINEERING (Total: 2844 journals)
    - CHEMICAL ENGINEERING (247 journals)
    - CIVIL ENGINEERING (248 journals)
    - ELECTRICAL ENGINEERING (176 journals)
    - ENGINEERING (1448 journals)
    - ENGINEERING MECHANICS AND MATERIALS (451 journals)
    - HYDRAULIC ENGINEERING (62 journals)
    - INDUSTRIAL ENGINEERING (97 journals)
    - MECHANICAL ENGINEERING (115 journals)

ENGINEERING (1448 journals)            First | 1 2 3 4 5 6 7 8     

Showing 1201 - 1205 of 1205 Journals sorted alphabetically
Purinergic Signalling     Hybrid Journal   (Followers: 1)
Quaderns d’Història de l’Enginyeria     Open Access  
Quality and Reliability Engineering International     Hybrid Journal   (Followers: 15)
Quality Engineering     Hybrid Journal   (Followers: 12)
Quantum Engineering     Hybrid Journal  
R&D Journal     Open Access   (Followers: 1)
Radiochimica Acta     Hybrid Journal   (Followers: 5)
Rare Metals     Hybrid Journal   (Followers: 3)
Reactive and Functional Polymers     Hybrid Journal   (Followers: 5)
Recent Patents on Engineering     Hybrid Journal   (Followers: 3)
Recent Patents on Nanotechnology     Hybrid Journal   (Followers: 2)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Redes de Ingeniería     Open Access  
Regional Maritime University Journal     Full-text available via subscription   (Followers: 3)
Regular and Chaotic Dynamics     Hybrid Journal  
Rem : Revista Escola de Minas     Open Access  
Remote Sensing     Open Access   (Followers: 54)
Remote Sensing Letters     Hybrid Journal   (Followers: 46)
Requirements Engineering     Hybrid Journal   (Followers: 3)
Research Ideas and Outcomes     Open Access   (Followers: 1)
Research in Engineering Design     Hybrid Journal   (Followers: 10)
Research Journal of Nanoscience and Nanotechnology     Open Access   (Followers: 18)
Resonance     Hybrid Journal   (Followers: 29)
Respuestas     Open Access  
Results in Engineering     Open Access  
Review of Symbolic Logic     Full-text available via subscription   (Followers: 2)
Reviews in Advanced Sciences and Engineering     Partially Free   (Followers: 1)
Revista AIDIS de Ingeniería y Ciencias Ambientales. Investigación, desarrollo y práctica     Open Access  
Revista Brasileira de Engenharia Agrícola e Ambiental     Open Access   (Followers: 1)
Revista Brasileira de Inovação     Open Access  
Revista Campus     Open Access  
Revista Ciencia y Tecnología     Open Access  
Revista Ciencia y Tecnología     Open Access  
Revista Ciencia y Tecnología El Higo     Open Access   (Followers: 2)
Revista Científica de la UCSA     Open Access  
Revista Colombiana fe Technologias de Avanzada (RCTA)     Open Access   (Followers: 3)
Revista Cubana de Ingeniería     Open Access  
Revista de Ciências Exatas Aplicadas e Tecnológicas da Universidade de Passo Fundo : CIATEC-UPF     Open Access  
Revista de Ciências Exatas e Tecnologia     Open Access   (Followers: 1)
Revista de Ingeniería     Open Access  
Revista de Ingenieria Sismica     Open Access  
Revista de Investigación     Open Access  
Revista de Investigación, Desarrollo e Innovación     Open Access  
Revista de Investigaciones en Energía, Medio Ambiente y Tecnología     Open Access  
Revista de la Universidad del Zulia     Open Access  
Revista EIA     Open Access   (Followers: 1)
Revista Facultad de Ingeniería     Open Access   (Followers: 1)
Revista Facultad de Ingenieria - Universidad de Tarapaca     Open Access   (Followers: 1)
Revista Facultad de Ingeniería Universidad de Antioquia     Open Access   (Followers: 1)
Revista Fatec Zona Sul : REFAS     Open Access  
Revista Iberoamericana de Automática e Informática Industrial RIAI     Open Access  
Revista Informador Técnico     Open Access   (Followers: 1)
Revista Ingenieria de Construcción     Open Access   (Followers: 1)
Revista Interdisciplinar de Pesquisa em Engenharia     Open Access   (Followers: 1)
Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería     Open Access  
Revista Logos Ciencia & Tecnología     Open Access   (Followers: 1)
Revista Técnica de la Facultad de Ingeniería : Universidad del Zulia     Open Access   (Followers: 1)
Revista Tecnología en Marcha     Open Access  
Revista Tecnológica     Open Access   (Followers: 1)
Revista UIS Ingenierías     Open Access  
Revue de Métallurgie     Full-text available via subscription  
RUDN Journal of Engineering Researches     Open Access   (Followers: 1)
Russian Engineering Research     Hybrid Journal  
Russian Journal of Non-Ferrous Metals     Hybrid Journal   (Followers: 21)
Russian Microelectronics     Hybrid Journal   (Followers: 1)
Sadhana     Open Access   (Followers: 10)
Safety Science     Hybrid Journal   (Followers: 28)
Scholedge International Journal of Multidisciplinary & Allied Studies     Open Access   (Followers: 3)
Science & Technique     Open Access   (Followers: 1)
Science and Education : Scientific Publication of BMSTU     Open Access   (Followers: 1)
Science and Engineering Ethics     Hybrid Journal   (Followers: 9)
Science and Technology     Open Access   (Followers: 2)
Science and Technology Indonesia     Open Access   (Followers: 1)
Science China Technological Sciences     Hybrid Journal   (Followers: 1)
Science in Context     Hybrid Journal   (Followers: 4)
Science Journal of Volgograd State University. Technology and innovations     Open Access  
Science Progress     Full-text available via subscription   (Followers: 4)
Sciences & Technologie B : Sciences de l'ingénieur     Open Access  
Scientia cum Industria     Open Access  
Scientific Drilling     Open Access  
Scientific Journal of Control Engineering     Open Access   (Followers: 3)
Scientific Journal of Mehmet Akif Ersoy University     Open Access  
Scientific Journal of Pure and Applied Sciences     Open Access   (Followers: 1)
SCITECH Nepal     Open Access  
Sealing Technology     Full-text available via subscription   (Followers: 1)
Securitas Vialis     Hybrid Journal  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selcuk University Journal of Engineering, Science and Technology     Open Access   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 57)
Semiconductors     Hybrid Journal   (Followers: 2)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Sensor Letters     Full-text available via subscription   (Followers: 2)
Sensors     Open Access   (Followers: 23)
Separation and Purification Technology     Hybrid Journal   (Followers: 15)
Shock and Vibration     Hybrid Journal   (Followers: 26)
SIAM Journal on Applied Dynamical Systems     Hybrid Journal   (Followers: 2)
SIAM Journal on Mathematical Analysis     Hybrid Journal   (Followers: 4)
SIAM Journal on Matrix Analysis and Applications     Hybrid Journal   (Followers: 3)
SIAM Journal on Numerical Analysis     Hybrid Journal   (Followers: 7)
SIAM Journal on Optimization     Hybrid Journal   (Followers: 11)
SIAM Review     Hybrid Journal   (Followers: 7)
SILICON     Hybrid Journal  
SINERGI     Open Access  
Sistemas & Telemática     Open Access   (Followers: 2)
Sleep and Biological Rhythms     Hybrid Journal   (Followers: 9)
Small     Hybrid Journal   (Followers: 16)
Smart Grid     Open Access   (Followers: 1)
SN Applied Sciences     Hybrid Journal   (Followers: 1)
Sociología y Tecnociencia     Open Access  
Soft Computing     Hybrid Journal   (Followers: 9)
Soil Dynamics and Earthquake Engineering     Hybrid Journal   (Followers: 15)
Solar RRL     Hybrid Journal  
Soldagem & Inspeção     Open Access  
SourceOCDE Developpement urbain, rural et regional     Full-text available via subscription   (Followers: 1)
SourceOCDE Energie     Full-text available via subscription  
SourceOECD Energy     Full-text available via subscription  
SourceOECD Science and Technology Statistics - SourceOCDE Base de donnees des sciences et de la technologie     Full-text available via subscription  
SourceOECD Transport     Full-text available via subscription   (Followers: 2)
SourceOECD Urban, Rural and Regional Development     Full-text available via subscription  
South African Computer Journal     Full-text available via subscription  
South African Journal of Agricultural Extension     Open Access   (Followers: 4)
South African Journal of Science     Open Access   (Followers: 4)
Sports Engineering     Hybrid Journal   (Followers: 2)
Stahlbau     Hybrid Journal   (Followers: 2)
Steel in Translation     Hybrid Journal   (Followers: 1)
Steel Research International     Hybrid Journal   (Followers: 24)
Stochastic Analysis and Applications     Hybrid Journal   (Followers: 2)
Stochastic Processes and their Applications     Hybrid Journal   (Followers: 5)
Stochastics and Dynamics     Hybrid Journal  
Strain     Hybrid Journal   (Followers: 2)
Strategic Planning for Energy and the Environment     Hybrid Journal   (Followers: 4)
Studies in Engineering and Technology     Open Access  
Studies in Interface Science     Full-text available via subscription  
Studies in Logic and Practical Reasoning     Full-text available via subscription  
Studies in Surface Science and Catalysis     Full-text available via subscription   (Followers: 1)
Sud-Sciences et Technologies     Open Access   (Followers: 1)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Surface Engineering     Hybrid Journal   (Followers: 1)
Surface Review and Letters     Hybrid Journal   (Followers: 1)
Surface Science Reports     Full-text available via subscription   (Followers: 20)
Surfaces and Interfaces     Hybrid Journal  
Survey Review     Hybrid Journal   (Followers: 6)
Surveying and Land Information Science     Full-text available via subscription   (Followers: 1)
Surveys in Operations Research and Management Science     Hybrid Journal   (Followers: 3)
Sustainability Science     Open Access   (Followers: 9)
Sustainability Science and Engineering     Full-text available via subscription   (Followers: 3)
Sustainable Management of Sediment Resources     Full-text available via subscription  
Swiss Journal of Geosciences     Hybrid Journal   (Followers: 1)
Symmetry     Open Access   (Followers: 1)
Synthesis Lectures on Algorithms and Software in Engineering     Full-text available via subscription   (Followers: 3)
Synthesis Lectures on Antennas     Full-text available via subscription   (Followers: 5)
Synthesis Lectures on Biomedical Engineering     Full-text available via subscription  
Synthesis Lectures on Computational Electromagnetics     Full-text available via subscription   (Followers: 4)
Synthesis Lectures on Energy and the Environment: Technology, Science, and Society     Full-text available via subscription   (Followers: 1)
Synthesis Lectures on Engineering     Full-text available via subscription  
Synthesis Lectures on Global Engineering     Full-text available via subscription  
Synthesis Lectures on Professionalism and Career Advancement for Scientists and Engineers     Full-text available via subscription   (Followers: 2)
Synthetic Metals     Hybrid Journal   (Followers: 4)
Systems Engineering     Hybrid Journal   (Followers: 7)
Systems Engineering - Theory & Practice     Full-text available via subscription  
Systems Engineering Procedia     Open Access  
Systems Research Forum     Hybrid Journal   (Followers: 1)
Systems Science & Control Engineering     Open Access   (Followers: 8)
Tableros     Open Access   (Followers: 2)
Tapuya : Latin American Science, Technology and Society     Open Access   (Followers: 1)
Technical Tips Online     Full-text available via subscription   (Followers: 1)
Technological Engineering     Open Access   (Followers: 1)
Technologies     Open Access   (Followers: 2)
TECHNOLOGY     Hybrid Journal   (Followers: 1)
Technology and Economics of Smart Grids and Sustainable Energy     Hybrid Journal  
Technology and Innovation     Full-text available via subscription   (Followers: 4)
Technology in Society     Hybrid Journal   (Followers: 7)
Technometrics     Full-text available via subscription   (Followers: 9)
Tecnología y Ciencia     Open Access  
Tecnología y Sociedad     Open Access   (Followers: 1)
TecnoLógicas     Open Access  
Tecnura     Open Access   (Followers: 1)
Tekhné     Open Access   (Followers: 1)
Tekniikan Waiheita     Open Access  
Teknologi dan Kejuruan : Jurnal Teknologi, Kejuruan, dan Pengajarannya     Open Access  
Telecommunications Policy     Hybrid Journal   (Followers: 9)
Textile Science and Technology     Full-text available via subscription   (Followers: 4)
Thalassas : An International Journal of Marine Sciences     Hybrid Journal  
The Engineer     Partially Free  
The Journal of Supercomputing     Hybrid Journal   (Followers: 1)
The Scientific World Journal     Open Access  
Theoretical and Computational Fluid Dynamics     Hybrid Journal   (Followers: 17)
Theoretical Issues in Ergonomics Science     Hybrid Journal   (Followers: 7)
Thermal Engineering     Full-text available via subscription   (Followers: 10)
Tikrit Journal of Engineering Science     Open Access  
tm - Technisches Messen     Hybrid Journal   (Followers: 2)
Topics in Catalysis     Hybrid Journal   (Followers: 1)
Traffic Injury Prevention     Hybrid Journal   (Followers: 75)
Transactions of the Indian National Academy of Engineering     Hybrid Journal   (Followers: 2)
Transactions of the VŠB – Technical University of Ostrava, Safety Engineering Series     Open Access   (Followers: 1)
Transactions of Tianjin University     Full-text available via subscription  
Transport and Aerospace Engineering     Open Access   (Followers: 13)
Transport and Telecommunication     Open Access   (Followers: 4)
Transport World Africa     Full-text available via subscription   (Followers: 2)

  First | 1 2 3 4 5 6 7 8     

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: 34  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 0361-1981
Published by TRB Homepage  [1 journal]
  • Using Artificial Potential Field Theory for a Cooperative Control Model in
           a Connected and Automated Vehicles Environment
    • Authors: Ziwei Yi, Linheng Li, Xu Qu, Yang Hong, Peipei Mao, Bin Ran
      Abstract: Transportation Research Record, Ahead of Print.
      Artificial potential field (APF) theory has been extensively applied in traffic path planning as an efficient method to avoid collision. However, studies in collision avoidance based on APF theory only considered the movement of single vehicle. In this paper, a vehicle cooperative control model for avoiding collision in the connected and autonomous vehicles (CAVs) environment is presented, using APF theory. The proposed model not merely guarantees the travel safety of vehicles in avoiding collision, but also promotes driving comfort and improves traffic efficiency. To verify the cooperative control model, simulations of four scenarios are designed and compared with the human driving environment. Five indicators are selected to evaluate the results, that is, time–space diagram, time mean speed (TMS), the rate of large deceleration time (large deceleration is that deceleration larger than –2 m/s2), the inverse time-to-collision ([math]), and lane-changing times. According to the simulation results, the cooperative control model could alleviate the capacity drop and increase the TMS to improve traffic efficiency, reduce the rate of the large deceleration time to promote driving comfort, and decrease [math] to promote safety in small and large input flow rates. The results reveal the proposed model is significantly superior to the human driving environment whether in free or congested situations, except for the lane-change times, which are slightly larger.
      Citation: Transportation Research Record
      PubDate: 2020-07-14T06:13:30Z
      DOI: 10.1177/0361198120933271
       
  • Vehicle and Pedestrian Level of Service in Street Designs with Elements of
           Shared Space
    • Authors: Ioannis Kaparias, Rui Wang
      Abstract: Transportation Research Record, Ahead of Print.
      Inspired by developments in urban planning, the concept of “shared space” has recently emerged as a way of creating a better public realm. This is achieved through a range of streetscape treatments aimed at asserting the function of streets as places by facilitating pedestrian movement and lowering vehicle traffic volumes and speeds. The characteristics of streets with elements of shared space point to the conjecture that traffic conditions and road user perceptions may be different to those on streets designed according to more conventional principles, and this is likely to have an impact on the quality of service. The aim of this paper is, therefore, to perform an analysis in relation to level of service (LOS) and to investigate how this may change as a result of the implementation of street layouts with elements of shared space. Using video data from the Exhibition Road site in London during periods before and after its conversion from a conventional dual carriageway to a layout featuring several elements of shared space, changes in relation to LOS for both vehicle traffic and pedestrians are investigated, by applying the corresponding methods from the 2010 Highway Capacity Manual. The results suggest that streets with elements of shared space provide a much improved pedestrian experience, as expressed by higher LOS ratings, but without compromising the quality of vehicle traffic flow, which, in fact, also sees slight improvements.
      Citation: Transportation Research Record
      PubDate: 2020-07-14T06:13:10Z
      DOI: 10.1177/0361198120933627
       
  • Study of Road Autonomous Delivery Robots and their Potential Effects on
           Freight Efficiency and Travel
    • Authors: Dylan Jennings, Miguel Figliozzi
      Abstract: Transportation Research Record, Ahead of Print.
      Road autonomous mobile robots have attracted the attention of delivery companies and policy makers owing to their potential to reduce costs and increase urban freight efficiency. Established delivery companies and new startups are investing in technologies that reduce delivery times, increase delivery drivers’ productivity, or both. In this context, the adoption of road automatic (or autonomous) delivery robots (RADRs) has a growing appeal. Several RADRs are currently being tested in the United States. The key novel contributions of this research are: (a) an analysis of the characteristics and regulation of RADRs in the U.S. and (b) a study of the relative travel, time, and cost efficiencies that RADRs can bring about when compared to traditional van deliveries. The results show that RADRs can provide substantial cost savings in many scenarios, but in all cases at the expense of substantially higher vehicle miles per customer served. Unlike sidewalk autonomous delivery robots (SADRs), it is possible the RADRs will contribute significantly to additional vehicle miles per customer served.
      Citation: Transportation Research Record
      PubDate: 2020-07-14T06:12:51Z
      DOI: 10.1177/0361198120933633
       
  • Application of Dynamic Adaptive Planning and Risk-Adjusted Decision Trees
           to Capture the Value of Flexibility in Resilience and Transportation
           Planning
    • Authors: Prerna Singh, Baabak Ashuri, Adjo Amekudzi-Kennedy
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation infrastructure around the world is under pressure to perform with ever-changing climate scenarios, unpredictable disasters, and stress on resources stemming from rapid urbanization and population growth. Current approaches to developing resilience applied to the transportation system focus primarily on engineering resilience and do not explicitly deal with deep uncertainties arising from climate change. This paper reviews adaptation, a critical aspect of a resilient system in an uncertain and changing environment, as applied in the transportation resilience literature. It compares and contrasts the status of adaptive resiliency in transportation with that in other fields to highlight gaps and research opportunities. The paper then presents Dynamic Adaptive Planning (DAP) as a method for dealing more effectively with deep uncertainty in decision making and offers an approach that combines economic analysis with DAP to enhance decision making under external uncertainties, such as natural disasters, with financial constraints. It presents a case study of the San Francisco–Oakland Bridge to demonstrate the economic benefits of DAP. This paper provides transportation practitioners with guidance on the application of DAP and insight into the economic benefits of such an approach to decision making in various settings including emergency response planning, long-range planning, maintenance and renewal planning, and operations planning. The paper also identifies areas for possible future research combining financial theory with DAP as important in developing more robust decision-making frameworks for handling deep uncertainty.
      Citation: Transportation Research Record
      PubDate: 2020-07-14T02:38:09Z
      DOI: 10.1177/0361198120929012
       
  • Crash Modification Functions for Passing Relief Lanes on Two-Lane Rural
           Roads
    • Authors: Bhagwant Persaud, Alireza Jafari Anarkooli, Shahram Almasi, Craig Lyon
      Abstract: Transportation Research Record, Ahead of Print.
      Passing relief lanes on two-lane rural roads provide passing opportunities that would otherwise be scarce where there are extensive no-passing zones, high opposing traffic volumes, or both. This paper addresses the safety effects of installing a passing lane or lengthening an existing one. It stands to reason that the effect of installing a passing lane will depend on the actual length of that lane. By extension, it is also reasonable to expect that the safety effects of lengthening an existing one will depend not only on the amount of the lengthening, but also on the original length. Yet, knowledge that can be applied to estimate these two sets of effects in a design process is lacking. The crash modification factors (CMFs) in the Highway Safety Manual (HSM) and in the CMF Clearinghouse for installing a passing lane are all single-valued, of the order of 0.75. And neither source provides CMFs for lengthening an existing passing lane. This paper seeks to address these voids by developing continuous crash modification functions (CMFunctions) for both sets of design decisions using Michigan, U.S., and Ontario, Canada, crash, geometric, and traffic data for passing lane and reference sections. Generalized linear modeling and full Bayes Markov Chain Monte Carlo (FB MCMC) simulation are used to develop cross-section regression models from which crash modification functions are derived and compared. The results are consistent with those from credible before-after studies, so are recommended for implementation in practice, in particular for HSM applications.
      Citation: Transportation Research Record
      PubDate: 2020-07-14T02:38:09Z
      DOI: 10.1177/0361198120930719
       
  • Impact of Electric and Hybrid Vehicles on Highway Trust Fund in Alabama
    • Authors: Dan Xu, Huaguo Zhou, Chennan Xue, Jeffrey LaMondia
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this paper is to help state agencies better understand the impact of electric and hybrid vehicles on the Highway Trust Fund and to develop a method for estimating proper annual registration fees for electric vehicles (EVs). In this study, a comprehensive literature review was conducted to summarize the background on electric and hybrid vehicles, current national and state policies and incentives, the trend of EV market in the U.S., and registration fees on electric and hybrid vehicles. As electric and hybrid vehicles do not contribute to fuel excise tax revenue, to compensate the lost tax revenues, some states charge additional annual registration fees to EV owners. To help the legislators determine the proper annual fees, a method was developed to assess the additional registration fees for EVs and plug-in hybrid electric vehicles (PHEVs) in Alabama. The collected data include number of registered electric and hybrid vehicles, fuel tax per gallon, and annual average mileage traveled by electric and hybrid vehicles in Alabama. The results of this study served as a key reference in the Rebuild Alabama Act that proposed an annual registration fee of $200 and $100 for EVs and PHEVs, respectively, which is effective since January 2020. The method in this study can be applied to other states for developing policies on registration fees for EVs and PHEVs to offset the fuel excise tax revenue loss.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T09:16:30Z
      DOI: 10.1177/0361198120932901
       
  • Machine Learning Approach to Forecast Work Zone Mobility using Probe
           Vehicle Data
    • Authors: Mohsen Kamyab, Stephen Remias, Erfan Najmi, Sanaz Rabinia, Jonathan M. Waddell
      Abstract: Transportation Research Record, Ahead of Print.
      The aim of deploying intelligent transportation systems (ITS) is often to help engineers and operators identify traffic congestion. The future of ITS-based traffic management is the prediction of traffic conditions using ubiquitous data sources. There are currently well-developed prediction models for recurrent traffic congestion such as during peak hour. However, there is a need to predict traffic congestion resulting from non-recurring events such as highway lane closures. As agencies begin to understand the value of collecting work zone data, rich data sets will emerge consisting of historical work zone information. In the era of big data, rich mobility data sources are becoming available that enable the application of machine learning to predict mobility for work zones. The purpose of this study is to utilize historical lane closure information with supervised machine learning algorithms to forecast spatio-temporal mobility for future lane closures. Various traffic data sources were collected from 1,160 work zones on Michigan interstates between 2014 and 2017. This study uses probe vehicle data to retrieve a mobility profile for these historical observations, and uses these profiles to apply random forest, XGBoost, and artificial neural network (ANN) classification algorithms. The mobility prediction results showed that the ANN model outperformed the other models by reaching up to 85% accuracy. The objective of this research was to show that machine learning algorithms can be used to capture patterns for non-recurrent traffic congestion even when hourly traffic volume is not available.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:28Z
      DOI: 10.1177/0361198120927401
       
  • Utilizing an Analytical Hierarchy Process with Stochastic Return On
           Investment to Justify Connected Vehicle-Based Deployment Decisions
    • Authors: Mahmoud Arafat, Shahadat Iqbal, Mohammed Hadi
      Abstract: Transportation Research Record, Ahead of Print.
      With the increasing interest in connected vehicles (CV), it becomes all the more important to support decisions by transportation agencies to invest in Connected Vehicle to Infrastructure (V2I) applications. This paper presents a method that can be used to justify the investment in CV-based safety applications considering the availability of existing solutions. The method utilizes a combination of stochastic return on investment (ROI) analysis and a multi-criteria decision-analysis (MCDA) procedure to account for uncertainties, to consider effects that cannot be converted to dollar values, and to account for stakeholder priorities. The stochastic ROI analysis is applied using Monte Carlo simulations and included as part of the selection criteria in the MCDA method using the Analytical Hierarchy Process (AHP). This paper applies the method to support the deployment of CV-based applications to address transportation safety concerns on urban arterials. These applications can be categorized as CV-based support of signalized intersection safety, CV-based support of unsignalized intersection safety, and CV-based hazard warning applications. The results of the Monte Carlo simulation analysis for a project case study indicated the cost-effectiveness of these applications. The results of the AHP analysis indicate that utilizing V2I applications is 41.3% more favorable than utilizing the investigated existing solutions to address safety concern on the arterial facility that is the subject of the case study.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:27Z
      DOI: 10.1177/0361198120929686
       
  • Indirect and Direct Design Methods for Design of Reinforced Concrete Pipe
    • Authors: Josh Beakley, Steven J. DelloRusso, Margarita Takou
      Abstract: Transportation Research Record, Ahead of Print.
      There are currently two acceptable methods by which concrete pipe may be designed per the AASHTO Bridge Design Specifications: the direct design method and the indirect design method. The evaluation of applied load is similar for both methods, however, evaluation of the pipe’s capacity to resist applied load differs between the two methods. The indirect design method uses physical three edge bearing (TEB) testing at the production facility based on a relationship between the forces in the pipe wall in the installed condition compared with forces in the pipe wall from the TEB test. The direct design method follows the conventional design procedure for concrete members where demand versus capacity is determined using load and resistance factors to account for variability in applied loads and resistant capacity of the structure. Because of advances in computer technology, the direct method has become easier to apply than it was in the past. However, the indirect method, which has been used for approximately 70 years, has demonstrated conservatism and is a proven design method. Comparison of similar installations using the two methods has resulted in disagreements with respect to the minimum required reinforcement, however, both methods are adequately conservative, and each may have its place depending on the size and strength of the pipe. This paper presents the fundamental differences between the two design methods and offers some guidance on when to use each of them.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:27Z
      DOI: 10.1177/0361198120930231
       
  • Determining Skid Resistance Needs on Horizontal Curves for Different
           Levels of Precipitation
    • Authors: Srinivas R. Geedipally, Subasish Das, Michael P. Pratt, Dominique Lord
      Abstract: Transportation Research Record, Ahead of Print.
      Horizontal curves are a major cause of crashes that lead to fatal and serious injuries. Much research has been conducted on the safety implications of geometric and traffic characteristics of curves. Variables describing curve geometry and speed have been incorporated into safety prediction methodologies. However, relatively less research has been conducted on the effects of pavement friction and weather data on safety. The objective of this study is to develop a methodology for determining the pavement friction needs for different levels of precipitation. To accomplish the study objective, rural two-lane, four-lane undivided, and four-lane divided horizontal curve data from Texas were used. Safety prediction models were developed that included traffic and geometric characteristics, skid number, and annual precipitation rate. These models were then used to develop the guidelines for assessing the safety performance of a curve of interest by accounting for curve geometry, pavement skid resistance, and exposure to the wet-weather conditions that are most relevant for considerations of skid resistance. For conducting a planning-level analysis to identify candidate sites for pavement friction treatments, researchers developed thresholds based on the combined effect of skid number and annual precipitation variables. Researchers also provided skid number thresholds for high-priority sites for two example locations that experience significantly different levels of annual precipitation.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:26Z
      DOI: 10.1177/0361198120929334
       
  • Predicting Compliance with Speed Limits using Speed Limit Credibility
           Perception and Risk Perception Data
    • Authors: Yao Yao, Oliver Carsten, Daryl Hibberd
      Abstract: Transportation Research Record, Ahead of Print.
      The link between attitudes and behavior shows that driving behavior can be predicted by personal characteristics and individual attitudes, as has been shown in previous research. This study aimed to predict the level of compliance with speed limits by individual drivers by using attitudes data including speed limit credibility perception and risk perception on eight rural single carriageway layouts. This study investigated how the road layout and roadside environment affect speed limit credibility perception and risk perception, and investigated which machine learning algorithm can be used to predict driving behavior based on experimental evidence. This study was carried out in a well-controlled experimental design by using a questionnaire and a driving simulator. The simulated road environment only considered rural single carriageway which has higher risk factors than other road types. The results show that a boosted decision tree algorithm can establish a driving behavior model based on drivers’ credibility perception and risk perception. This result can be used to predict driving behavior in advance for in-vehicle warning system design.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:26Z
      DOI: 10.1177/0361198120929696
       
  • Safety Effects of Horizontal Curve Reliability Index
    • Authors: Scott Himes, Eric Donnell
      Abstract: Transportation Research Record, Ahead of Print.
      Recent advancements in analytical processes have used probabilistic approaches to examine the efficacy of the point mass model (and other Green Book models) to develop reliability-based approaches for geometric design. However, there has been minimal research establishing the link between reliability measures and substantive safety (expressed through crash frequency). The objective of this paper is to use empirical data supporting the calculation of reliability index for existing horizontal curves and to estimate the relationship between reliability index and crash frequency. Other horizontal curve-related characteristics that may have an impact on crash frequency on horizontal curves for rural two-lane highways and rural freeway facilities are controlled for in the evaluation. The safety analysis showed that the wet pavement reliability index was significantly associated with crash frequency for total curve-related crashes, single-vehicle run-off-road crashes, rollover crashes, truck-related crashes, and weather-related crashes. The relationship was strongest for the reliability index in its continuous form, meaning that the effect is continuous across the range of wet pavement reliability that was observed.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:25Z
      DOI: 10.1177/0361198120930715
       
  • Estimating the Earnings from Peer-to-Peer Carsharing for Vehicle Owners on
           the Turo Platform using Anonymized Data
    • Authors: Joseph P. Schwieterman, C. Scott Smith
      Abstract: Transportation Research Record, Ahead of Print.
      Peer-to-peer carsharing, in which “hosts” (i.e., vehicle owners) make their vehicles available for a fee, has grown markedly in recent years. Little is known about how activity in this sector is distributed across communities with different socioeconomic or demographic profiles, or about the income it provides to hosts. To offer insights into these issues, this study evaluates anonymized data of trips made on Turo, one of the country's largest peer-to-peer carsharing platforms, in Illinois. It shows that usage is heaviest in higher-density neighborhoods with above-average unemployment and rental housing rates, with a particularly large concentration on Chicago's near north, south, and west sides, as well as zip codes with sizable minority populations. Most transactions are financially remunerative to hosts who would own their vehicle regardless of their decision to share. When maintenance and other expenses are taken into account (while nonmonetary costs such as the host's time are excluded), 94.9% of trips cover their marginal cost to the host. The returns from sharing sports utility vehicles (SUVs) tend to be higher than those for sedans and minivans. A low-income family making $40,000 annually will increase household income by 6% by sharing a vehicle 90 days annually.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:24Z
      DOI: 10.1177/0361198120928341
       
  • Exploring Instrumentation and Sensor Technologies for Highway Design and
           Construction Projects
    • Authors: Christofer M. Harper, Daniel Tran, Edward Jaselskis
      Abstract: Transportation Research Record, Ahead of Print.
      With the infusion of emerging technologies into highway construction practices, state departments of transportation (DOTs) can make better informed decisions that positively influence cost, schedule, quality, and safety. DOTs are increasingly using instrumentation and sensor technologies for delivering highway projects across the U.S.A. Instrumentation devices and sensors include such technologies as remote sensing, real-time kinematics, global positioning systems, digital handheld devices, ground penetrating radar, and intelligent compaction/thermal profiling. These technologies are becoming commonplace in highway construction because of their capabilities to improve the construction process by making activities more efficient and more productive. However, the practices in using instrumentation and sensor technologies for highway construction vary among state DOTs. Therefore, this study investigates how DOTs employ the use of instrumentation and sensor technologies for highway construction. This study engaged a research methodology that included an extensive literature review, survey questionnaire, and case studies of state DOTs. Results show that 31 state DOTs use instrumentation and sensor technologies for monitoring work progress, conducting quality control and quality assurance, performing construction inspections, identifying optimal conditions and recording the placement of work, and locating utilities. The main barriers to using instrumentation and sensor technologies include analyzing the large amount of data, verifying the accuracy of the data, ensuring staff have the skills and knowledge to use the technologies efficiently, and assisting smaller contractors to gain the knowledge to use these technologies. The findings from this study provide recommendations and strategies for DOTs to implement instrumentation and sensor technologies effectively for highway construction.
      Citation: Transportation Research Record
      PubDate: 2020-07-13T02:43:24Z
      DOI: 10.1177/0361198120930718
       
  • Computer Vision for Rapid Updating of the Highway Asset Inventory
    • Authors: Tom Strain, R. Eddie Wilson, Roger Littleworth
      Abstract: Transportation Research Record, Ahead of Print.
      In this paper, a decision support system is proposed to assist an analyst in updating the highway roadside asset inventory. The feasibility of the system is tested with assets along an 8 km section of the A27 highway on the south coast of England, UK. Survey data from a vehicle equipped with a single forward-facing camera and a GPS-enabled inertial measurement unit, aerial imagery of the highway, and the asset inventory are fused to develop the system. The camera on the vehicle is calibrated so that assets may be automatically located within the survey images. The assets are then classified by a state-of-the-art convolutional neural network. Therefore, those assets recorded correctly in the inventory and those needing further manual inspection are automatically identified. Three different asset types are considered (traffic signs, matrix signs, and reference marker posts), and overall 91% of the assets in a withheld test set are verified automatically. Thus the analyst is presented with a much smaller set of assets for which the inventory is incorrect and which require further inspection. We therefore demonstrate the value in fusing multiple data sources to develop decision support systems for transportation asset monitoring.
      Citation: Transportation Research Record
      PubDate: 2020-07-10T03:24:26Z
      DOI: 10.1177/0361198120928348
       
  • K-Prototypes Segmentation Analysis on Large-Scale Ridesourcing Trip Data
    • Authors: Jason Soria, Ying Chen, Amanda Stathopoulos
      Abstract: Transportation Research Record, Ahead of Print.
      Shared mobility-on-demand services are expanding rapidly in cities around the world. As a prominent example, app-based ridesourcing is becoming an integral part of many urban transportation ecosystems. Despite the centrality, limited public availability of detailed temporal and spatial data on ridesourcing trips has limited research on how new services interact with traditional mobility options and how they affect travel in cities. Improving data-sharing agreements are opening unprecedented opportunities for research in this area. This study examined emerging patterns of mobility using recently released City of Chicago public ridesourcing data. The detailed spatio-temporal ridesourcing data were matched with weather, transit, and taxi data to gain a deeper understanding of ridesourcing’s role in Chicago’s mobility system. The goal was to investigate the systematic variations in patronage of ridehailing. K-prototypes was utilized to detect user segments owing to its ability to accept mixed variable data types. An extension of the K-means algorithm, its output was a classification of the data into several clusters called prototypes. Six ridesourcing prototypes were identified and discussed based on significant differences in relation to adverse weather conditions, competition with alternative modes, location and timing of use, and tendency for ridesplitting. The paper discusses the implications of the identified clusters related to affordability, equity, and competition with transit.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T04:12:13Z
      DOI: 10.1177/0361198120929338
       
  • Integrating Economic and Utility Concepts for a Comprehensive Bridge
           Valuation Model
    • Authors: Trinh Hoang, Zhe Han, Zhanmin Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Current approaches in bridge valuation mostly focus on engineering construction costs while neglecting other values generated by the bridge's functionality and utilization, along with other indirect economic values of a bridge. Such limitations prevent public agencies from capturing the true asset value of their bridges to make informed management decisions. The objective of this paper is to develop a comprehensive bridge asset valuation methodology that is based on the utility theory concept to better represent the asset value of a bridge. Various factors featuring the bridge asset value are characterized and considered in the model including physical condition, safety, mobility, average annual daily traffic (AADT), direct time savings, and so on. These factors are categorized into economic value and utility-based value and quantified with specific performance measures. The applicability of the proposed methodology is demonstrated through a case study using five real-world bridges in Austin, Texas. The results show that the integrated, comprehensive model is able to effectively evaluate the overall asset value of a bridge. Finally, the paper discusses how public agencies can take advantage of the evaluation results to better understand bridge asset value and make more insightful decisions in bridge management practice.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T04:12:12Z
      DOI: 10.1177/0361198120926509
       
  • How Travel Purpose Interacts with Predictors of Individual Driving
           Behavior in Greater Montreal
    • Authors: James DeWeese, Ahmed El-Geneidy
      Abstract: Transportation Research Record, Ahead of Print.
      Rising transport emissions represent a significant challenge for policy makers. Two principal options exist to reduce emissions: make driving less polluting or reduce driving overall. Though cities have a role to play in both approaches, the levers that may influence the latter more squarely align with municipal competences concerning the urban form. This paper aims to refine our understanding of the relationship between urban form, public transport systems, and driving behavior by exploring whether accessibility—the ease of reaching desired destinations—exerts a different influence on people’s decision to drive on weekdays and total distance driven depending on travel purpose. We relied on disaggregate data from the 2013 Montreal Origin–Destination Survey and employed a two-step “hurdle” approach with multilevel logistic and linear models. We found both local and regional accessibility displayed statistically significant negative correlations with driving mode choice and vehicle distance driven by drivers. Concerning the decision to drive, regional accessibility, defined by transit-accessible jobs, appeared to possess a stronger relationship than local, as measured by Walk Score across all purposes. When considering total kilometers driven, however, the relative impact of both types of accessibility varied. Overall, and for work and school driving, regional accessibility correlated with the greatest declines in distance driven. For healthcare and discretionary travel, local accessibility correlated with a larger decline in total driving distance. Our findings also highlight the potentially profound impact of other explanatory factors, particularly car ownership, suggesting additional policy approaches for municipal decision makers to reduce vehicle kilometers traveled.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T04:12:11Z
      DOI: 10.1177/0361198120926505
       
  • Relationship between Overconfidence and Risky Behavior among Ship Crew
    • Authors: Ying Wang, Xin Shi, Dong Xu
      Abstract: Transportation Research Record, Ahead of Print.
      Human factors are a primary cause of maritime accidents. This paper explores the relationship between risky behavior and overconfidence among members of a ship crew. Data on confidence and risky behaviors were collected through experiments carried out on a navigation simulator and an associated questionnaire. Contingency table analysis and chi-square test were then performed to clarify the relationships between these variables. The results indicated that both overconfidence and underconfidence were potential causes of risky behaviors among crew members; the type of risky behavior undertaken was also found to be related to both overconfidence and underconfidence. Levels of confidence varied with individual characteristics such as age and sailing experience. The major findings were as follows. Crew members aged 25 years or younger were more likely to be overconfident; crew members with less sailing experience were more likely to be either highly overconfident or underconfident; highly overconfident and underconfident crew members were more prone to involvement in collisions; skill-based risky behaviors were most associated with underconfidence; rule-based risky behaviors were more likely to be exhibited by highly overconfident or underconfident crew members; knowledge-based risky behavior was primarily observed in highly overconfident crew members. This paper fills a current research gap by identifying the individual characteristics that induce risky behaviors, which will be beneficial in enabling the maritime sector to develop targeted interventions to prevent maritime accidents.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T04:12:11Z
      DOI: 10.1177/0361198120930008
       
  • Frequentist and Bayesian Approaches for Understanding Route Choice of
           Drivers under Stop-and-Go Traffic
    • Authors: Neeraj Saxena, Ruiyang Wang, Vinayak V. Dixit, S. Travis Waller
      Abstract: Transportation Research Record, Ahead of Print.
      Driving in congested traffic is a nuisance that not only results in longer travel times, but also triggers frustration and impatience among drivers. A few studies have modeled the effects of congested traffic in the resulting route choice behavior of car drivers. The studies used frequentist models such as discrete choice models to analyze large samples. However, these studies did not compare the inferences obtained from the frequentist and Bayesian approaches, particularly for datasets which are not sufficiently large. It has been shown by researchers that Bayesian models perform well, especially when the sample size is small. Thus, this paper develops and compares a multinomial logit (frequentist) and a Naïve Bayes (Bayesian) model on a mid-sized dataset of size around 100 participants which was obtained from a driving simulator experiment to understand driver’s route choice under stop-and-go traffic. The results show that the prediction power of the Naïve Bayes model is much higher than the multinomial logit model (MNL). The Naïve Bayes model is also found to perform better than machine learning algorithms like the decision tree model. The findings from this study will be useful to researchers and practitioners as they should test both the approaches and select the appropriate model, particularly in the case of seemingly large datasets.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T04:12:10Z
      DOI: 10.1177/0361198120929332
       
  • Distraction of Connected Vehicle Human–Machine Interface for Truck
           Drivers
    • Authors: Guangchuan Yang, Mohamed M. Ahmed, Biraj Subedi
      Abstract: Transportation Research Record, Ahead of Print.
      Connected vehicle (CV) technology aims to improve drivers’ situational awareness through audible and visual warnings, commonly displayed on a human–machine interface (HMI), thus reducing the likelihood of crashes caused by human error. Nevertheless, the presence of an in-vehicle CV HMI may pose an increasing threat to driver distraction, particularly for truck drivers and under high workload driving conditions. With this concern, this research investigated the effects of a HMI developed by the Wyoming Department of Transportation CV Pilot on truck drivers’ cognitive distraction and driving behavior through a driving simulator experiment. Revealed preference survey and vehicle dynamics data were employed to assess the cognitive distractions of the Pilot’s HMI. Simulation results indicated that when CV warnings were displayed on the HMI, they did not introduce significant effects on participants’ longitudinal and lateral control of the vehicle. Nevertheless, from the revealed preference survey, it was found that approximately 27% of the participants indicated that the CV HMI tended to introduce additional visual workload for them, particularly when approaching an active freeway work zone under reduced visibility condition. In this regard, this research pointed out that the design of CV warnings and HMI displays needs to incorporate drivers’ ability to recognize and react safely to the received CV warnings to minimize the cognitive distractions introduced by the CV HMI.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T04:12:08Z
      DOI: 10.1177/0361198120929692
       
  • Automated Train Identification and Train Position Monitoring at New York
           City Transit
    • Authors: Shay Lehmann, Alla Reddy, Chan Samsundar, Tuan Huynh
      Abstract: Transportation Research Record, Ahead of Print.
      Like any legacy subway system that first opened in the early 1900s, the New York City subway system operates using technology that dates from many different eras. Although some of this technology may be outdated, efforts to modernize are often hindered by budgetary limits, competing priorities, and managing the tradeoff between short-term service disruptions and long-term service improvements. At New York City Transit (NYCT), the locations of all trains on all lines are not visible to any one person in any one place and, for much of the system, train locations can only be seen at field towers for the handful of interlockings in its operational jurisdiction as result of the legacy signal system, which may come as a surprise to many daily commuters or personnel at newer metros. In 2019, developers at NYCT gained full access to the legacy signal system’s underlying track circuit occupancy data and developed an algorithm to automatically track trains and match these data with schedules and manual dispatchers’ logs in real time. This data-driven solution enables real-time train identification and tracking long before a full system modernization could be completed. This information is being provided to select personnel as part of a pilot program via several different tools with the aim of improving service management and reporting.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T02:25:00Z
      DOI: 10.1177/0361198120932562
       
  • Evidence from Highway Drivers in Greece Showing Toll Avoidance and Utility
           of Alternative Routes
    • Authors: Ioannis Politis, Michalis Kyriakoglou, Georgios Georgiadis, Panagiotis Papaioannou
      Abstract: Transportation Research Record, Ahead of Print.
      Road tolling plays a significant role on highways’ financial sustainability since it consists the major revenue source. This paper aims to examine the factors that affect the drivers’ route choice and urge them to avoid toll roads when an alternative toll-free route is available. The paper presents the results of a case study that is dealing with the issue of toll avoidance at the last non-privatized highway of Greece, the Egnatia Odos (EO) road. Data from a combined revealed and stated preference survey were collected and binary choice models were built for car and truck drivers so as to determine the utility of alternative routes. The results show that travel cost and toll fees are critical route choice criteria for car drivers, while travel time is a key decision factor for truck drivers. The high safety standards for the toll route were appreciated by both categories of drivers. Additional trip and personal characteristics, such as gender, trip frequency, type of transported cargo, and total trip length also affect drivers’ choices. The elasticity of travel time and cost was estimated to shed light on drivers’ sensitiveness to the route attributes and it was found that truck drivers’ choices are greatly influenced by their working time schedules. These findings highlight the key factors that influence the utility of toll roads and therefore could assist highway authorities and concessionaires in developing successful toll pricing policies which will not act as a deterrent to the use of highways.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T02:24:20Z
      DOI: 10.1177/0361198120933265
       
  • Resilience of Urban Street Network Configurations under Low Demands
    • Authors: Zhengyao Yu, Vikash V. Gayah
      Abstract: Transportation Research Record, Ahead of Print.
      Urban street networks are subject to a variety of random disruptions. The impact of movement restrictions (e.g., one-way or left-turn restrictions) on the ability of a network to overcome these disruptions—that is, its resilience—has not been thoroughly studied. To address this gap, this paper investigates the resilience of one-way and two-way square grid street networks with and without left turns under light traffic conditions. Networks are studied using a simplified routing algorithm that can be examined analytically and a microsimulation that describes detailed vehicle dynamics. In the simplified method, routing choices are enumerated for all possible origin–destination (OD) combinations to identify how the removal of a link affects operations, both when knowledge of the disruption is and is not available at the vehicle’s origin. Disruptions on two-way networks that allow left turns tend to have little impact on travel distances because of the availability of multiple shortest paths between OD pairs and the flexibility in route modification. Two-way networks that restrict left turns at intersections only have a single shortest-distance path between any OD pair and thus experience larger increases in travel distance, even when the disruption is known ahead of time. One-way networks sometimes have multiple shortest-distance routes and thus travel distances increase less than two-way network without left turns when links are disrupted. These results reveal a clear tradeoff between improved efficiency and reduced resilience for networks that have movement restrictions, and can be used as a basis to study network resilience under more congested scenarios and in more realistic network structures.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T02:24:00Z
      DOI: 10.1177/0361198120933269
       
  • Effects of Microbial Biomineralization Surface Erosion Control Treatments
           on Vegetation and Revegetation along Highways
    • Authors: Tasha M. Hodges, Bret N. Lingwall
      Abstract: Transportation Research Record, Ahead of Print.
      Microbial induced calcite precipitation (MICP) has been widely studied in laboratories to test changes to soil strength and density. Rarely studied is the biogeotechnology’s influence on real-world conditions. Consideration for the natural environment coexisting with treated soil is important, particularly vegetative responses to biochemical and physical changes from treatments. In this factorial designed study, vegetative response from one-time biochemical surficial treatments is observed in four soil growth mediums: two variants burned soil, unburned side slope construction soil, and Ottawa sand. Treatment objectives are to create a light crust that provides short-term erosion control, protects concurrently applied seeds and provides a beneficial plant environment (BPE). The crust creates a BPE through increased soil water retention and shear soil strength allowing better root and plant stability. An overly dense crust prevents root penetration and is avoided because established root systems are crucial in long-term erosion control. This study successfully created such a crust in all soil types treated. Also studied were influences of solution components on germination rates. Component influence proved highly dependent on soil type as calcium chloride inclusion was highly detrimental to seedling success in clean sand, somewhat detrimental to burned soil with ash layer, insignificant in unburned soil, and beneficial to burned soil without ash layer. These results give an indication of the complex biochemical soil reactions occurring from MICP treatment. This study gives evidence that a one-time application of a seeded biochemical solution has real-world potential as a balanced short-term and long-term erosion control technology for burned and construction soils.
      Citation: Transportation Research Record
      PubDate: 2020-07-08T02:23:41Z
      DOI: 10.1177/0361198120933625
       
  • Introducing Electrified Vehicle Dynamics in Traffic Simulation
    • Authors: Yinglong He, Michail Makridis, Konstantinos Mattas, Georgios Fontaras, Biagio Ciuffo, Hongming Xu
      Abstract: Transportation Research Record, Ahead of Print.
      Many studies have highlighted the added value of incorporating vehicle dynamics into microsimulation. Such models usually focus on simulation of conventional vehicles, failing to account for the acceleration dynamics of electrified vehicles that have different power characteristics from those of internal combustion engine vehicles (ICEV). In addition, none of them have explicitly dealt with the vehicle’s deceleration characteristics. Although it is not commonly considered critical how a vehicle decelerates, unrealistic behaviors in simulations can distort both traffic flow and emissions results. The present work builds on the lightweight microsimulation free-flow acceleration (MFC) model and proposes an extension, marking the first attempt to address these research gaps. First, a comprehensive review of dynamics-based car-following (including free-flow) models is conducted. Second, the methodology of the MFC model to capture the dynamics of electrified vehicles is described. Then, the experimental setup in different dimensions is introduced for the model validation and implementation. Finally, the results of this study indicate that: (1) the acceleration and deceleration potential curves underlying the MFC model can accurately represent real dynamics of electrified vehicles tested on the chassis dynamometer; (2) smooth transitions can be guaranteed after implementing the MFC model in microsimulation; (3) when reproducing the on-road driving trajectories, the MFC model can deliver significant reductions in root mean square error (RMSE) of speed (by ∼69%) and acceleration (by ∼50%) compared with benchmarks; (4) the MFC model can accurately predict the vehicle 0–100 km/h acceleration specifications, with RMSE 49.4% and 56.8% lower than those of the Gipps model and the intelligent driver model (IDM), respectively.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T12:00:41Z
      DOI: 10.1177/0361198120931842
       
  • Analytical Method to Approximate the Impact of Turning on the Macroscopic
           Fundamental Diagram
    • Authors: Guanhao Xu, Zhengyao Yu, Vikash V. Gayah
      Abstract: Transportation Research Record, Ahead of Print.
      Network macroscopic fundamental diagrams (MFDs) have recently been shown to exist in real-world urban traffic networks. The existence of an MFD facilitates the modeling of urban traffic network dynamics at a regional level, which can be used to identify and refine large-scale network-wide control strategies. To be useful, MFD-based modeling frameworks require an estimate of the functional form of a network’s MFD. Analytical methods have been proposed to estimate a network’s MFD by abstracting the network as a single ring-road or corridor and modeling the flow–density relationship on that simplified element. However, these existing methods cannot account for the impact of turning traffic, as only a single corridor is considered. This paper proposes a method to estimate a network’s MFD when vehicles are allowed to turn into or out of a corridor. A two-ring abstraction is first used to analyze how turning will affect vehicle travel in a more general network, and then the model is further approximated using a single ring-road or corridor. This approximation is useful as it facilitates the application of existing variational theory-based methods (the stochastic method of cuts) to estimate the flow–density relationship on the corridor, while accounting for the stochastic nature of turning. Results of the approximation compared with a more realistic simulation that includes features that cannot be captured using variational theory—such as internal origins and destinations—suggest that this approximation works to estimate a network’s MFD when turning traffic is present.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:04:45Z
      DOI: 10.1177/0361198120933274
       
  • Vendor-Independent Reliability Testing Model for Vehicle-to-Infrastructure
           Communications
    • Authors: Fatma Elzahraa Madkour, Umair Mohammad, Sameh Sorour, Mohamed Hefeida, Ahmed Abdel-Rahim
      Abstract: Transportation Research Record, Ahead of Print.
      This paper describes a vendor-independent reliability testing approach for vehicle-to-infrastructure (V2I) communications in connected vehicle traffic signal system applications. It provides an alternative to using the communication data reported by proprietary vendor-supplied interfaces. This approach was based on building a rigorously tested translation model that uses measured received signal strength indicator (RSSI) from any V2I communication equipment to predict the corresponding packet delivery ratio (PDR). This was achieved by correlating the signal strength, measured using a generic power meter, to PDR values reported in the communication interface of the equipment of different vendors. Both stationary and in-motion (10–40 mph) field data collection tests were conducted at three intersections. These tests were performed over distances of up to 500 m between the road-side units (RSUs) and the on-board units (OBUs). In each test, the RSSI values for line-of-sight packet exchange between various RSUs and OBUs was collected in the field, using both a generic power meter and vendor-specific tools. Next, the results were statistically analyzed and logistic and linear regression models that predict PDR values were developed. A case study to test and validate this new PDR prediction model was conducted at two intersections in Boise, Idaho. This prediction model will enable transportation system operators to test and validate the efficiency of connected vehicle RSU/OBU communications at signalized intersection approaches under different traffic conditions, independent of vendor-provided tools.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:04:24Z
      DOI: 10.1177/0361198120932910
       
  • Categorizing Merging and Diverging Strategies of Truck Drivers at Motorway
           Ramps and Weaving Sections using a Trajectory Dataset
    • Authors: Salil Sharma, Maaike Snelder, Lóránt Tavasszy, Hans van Lint
      Abstract: Transportation Research Record, Ahead of Print.
      Lane-changing models are essential components for microscopic simulation. Although the literature recognizes that different classes of vehicles have different ways of performing lane-change maneuvers, lane change behavior of truck drivers is an overlooked research area. We propose that truck drivers are heterogeneous in their lane change behavior too and that inter-driver differences within truck drivers exist. We explore lane changing behavior of truck drivers using a trajectory data set collected around motorway bottlenecks in the Netherlands which include on-ramp, off-ramp, and weaving sections. Finite mixture models are used to categorize truck drivers with respect to their merging and diverging maneuvers. Indicator variables include spatial, temporal, kinematic, and gap acceptance characteristics of lane-changing maneuvers. The results suggest that truck drivers can be categorized into two and three categories with respect to their merging and diverging behaviors, respectively. The majority of truck drivers show a tendency to merge or diverge at the earliest possible opportunity; this type of behavior leads to most of the lane change activity at the beginning of motorway bottlenecks, thus contributing to the raised level of turbulence. By incorporating heterogeneity within the lane-changing component, the accuracy and realism of existing microscopic simulation packages can be improved for traffic and safety-related assessments.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:04:04Z
      DOI: 10.1177/0361198120932568
       
  • Developing an Automated Technique to Calibrate the AASHTOWare Pavement ME
           Design Software
    • Authors: Shuvo Islam, Avishek Bose, Christopher A. Jones, Mustaque Hossain, Cristopher I. Vahl
      Abstract: Transportation Research Record, Ahead of Print.
      Many state highway agencies are in the process of implementing the AASHTOWare Pavement ME Design (PMED) software for routine pavement design. However, a recurring implementation challenge has been the need to locally calibrate the software to reflect an agency’s design and construction practices, materials, and climate. This study introduced a framework to automate the calibration processes of the PMED performance models. This automated technique can search PMED output files and identify relevant damages/distresses for a project on a particular date. After obtaining this damage/distress information, the technique conducts model verification with the global calibration factors. Transfer function coefficients are then automatically derived following an optimization technique and numerical measures of goodness-of-fit. An equivalence statistical testing approach is conducted to ensure predicted performance results are in agreement with the measured data. The automated technique allows users to select one of three sampling approaches: split sampling, jackknifing, or bootstrapping. Based on the sampling approach chosen, the automated technique provides the calibration coefficients or suitable ranges for the coefficients and shows the results graphically. Model bias, standard error, sum squared error, and p-value from the paired t-test are also reported to assess efficacy of the calibration process.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:03:44Z
      DOI: 10.1177/0361198120932567
       
  • Relationship between Backcalculated and Estimated Asphalt Concrete Dynamic
           
    • Authors: Nathan D. Bech, Julie M. Vandenbossche
      Abstract: Transportation Research Record, Ahead of Print.
      There are several methods for determining the stiffness of asphalt concrete in an existing pavement. The three primary methods are: dynamic modulus testing in the laboratory, predictive equations, and falling weight deflectometer (FWD) testing. Asphalt over asphalt (AC/AC) overlay design procedures allow the use of multiple methods to characterize fatigue damage in the existing asphalt concrete. Therefore, understanding the difference between these methods is critical for AC/AC overlay design. The differences between the methods for determining asphalt concrete stiffness and how these differences are related to FWD load magnitude and asphalt temperature are examined. Data from the Federal Highway Administration’s Long-Term Pavement Performance Program (LTPP) are used in this investigation. It is found that the stiffness determined through FWD testing and backcalculation is generally less than that estimated using the Witczak predictive equation and binder aging models. Furthermore, it is found that both FWD load magnitude and asphalt temperature have a significant effect on the difference between backcalculated and estimated stiffness of asphalt concrete. Backcalculated stiffness increases relative to estimated stiffness as FWD load and temperature increase. These effects must be considered when multiple methods of determining asphalt concrete stiffness are used interchangeably for overlay design.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:03:24Z
      DOI: 10.1177/0361198120932560
       
  • Estimating Pedestrian Volumes for Signalized and Stop-Controlled
           Intersections
    • Authors: Minh Le, Srinivas R. Geedipally, Kay Fitzpatrick, Raul E. Avelar
      Abstract: Transportation Research Record, Ahead of Print.
      Pedestrian fatal crashes in the U.S. have increased over the years. From 2007 to 2016, pedestrian fatalities increased 27% nationally, while all other traffic fatalities decreased 14%. On average, a pedestrian was killed every 1.5 h in traffic crashes in 2016. The Federal Highway Administration (FHWA) has been working with public agencies toward developing more data-driven approaches to identify and mitigate pedestrian safety issues. However, pedestrian exposure to risk is not readily available. The absence of pedestrian exposure data makes it challenging to identify and prioritize high-crash risk locations. Using Dallas, Texas, as a case study, researchers wanted to use exposure in relation to volumes—both vehicular and pedestrian volume—to determine pedestrian risk. Although the vehicular volume is extensively available, the pedestrian volume is seldom available. The objective of this study is to explore options for collecting or estimating pedestrian volume data, particularly at intersections with high pedestrian activity. Researchers successfully developed a direct-demand model that estimates pedestrian volumes at signalized and stop-controlled intersections. The final model showed that pedestrian volume: increases 4 times within downtown; increases 12% per school within 1 mi of intersection; increases 4.8 times per 1% increase in commercial/multi-family residential land uses within 300 ft of intersection; increases 4.7 times with presence of higher education, hospitals, or malls; and decreases 36% per 5 mph increase in the intersections’ maximum posted speed limit. This research can help advance pedestrian safety analyses by providing a method of estimating pedestrian volumes for intersections by control type, particularly when volumes are infeasible to measure.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:03:05Z
      DOI: 10.1177/0361198120932161
       
  • Low-Dimensional Model for Bike-Sharing Demand Forecasting that Explicitly
           Accounts for Weather Data
    • Authors: Guido Cantelmo, Rafał Kucharski, Constantinos Antoniou
      Abstract: Transportation Research Record, Ahead of Print.
      With the increasing availability of big, transport-related datasets, detailed data-driven mobility analysis is becoming possible. Trips with their origins, destinations, and travel times are now collected in publicly available databases, allowing for detailed demand forecasting with methods exploiting big and accurate data. In this paper, we predict the demand pattern of New York City bikes with a low-dimensional approach utilizing three-level data clustering. We use historical demand data along with temperature and precipitation to first aggregate and then decompose data to obtain meaningful clusters. The core of this approach lies in the proposed clustering technique, which reduces the dimension of the problem and, differently from other machine learning techniques, requires limited assumptions on the model or its parameters. The proposed method allows, for the given temperature and precipitation method, to obtain expected vector of movement (mean number and direction of trips) for each zone. In this paper, we synthesize more than 17 million trips into daily and zonal vectors of movement, which combined with weather data allow forecasting of the trip demand. The method allows us to predict the demand with over 75% accuracy, as shown in series of experiments in which various settings and parameterizations are validated against 25% holdout data.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:02:45Z
      DOI: 10.1177/0361198120932160
       
  • Sequenced Ordered Logit Model Considering Latent Variables for Determining
           Trip Satisfaction of Metro Passengers
    • Authors: Tara Saeidi, Mahmoud Mesbah, Meeghat Habibian
      Abstract: Transportation Research Record, Ahead of Print.
      Improving the public transportation system to compete with the private modes requires an understanding of passenger perceptions of the service quality (SQ). In the literature, various models have been developed to identify effective SQ attributes and to assess their relationship with passenger satisfaction. However, most of them either ignore the socioeconomic and trip characteristics or consider them by a market segmentation approach. Since these variables can affect passenger perceptions, it is important to include them in the model. This paper aims to capture the effect of socioeconomic and trip variables by combining them with SQ attributes in a satisfaction analysis. An ordered logit model considering SQ latent variables is calibrated to model passenger satisfaction. The measurement part of a Structural Equation Model (SEM) is applied to construct latent variable structures. The case study was on the Tehran metro. The SQ attributes were used to form five SQ latent variables: “comfort,”“information,”“cleanliness,”“service,” and “safety/security.” The results indicate that socioeconomic and trip characteristics, as well as the SQ latent variables, had a significant effect on passenger satisfaction. From the results of this study, “service” and “comfort” were found to be the most effective contributors to satisfaction levels among the SQ latent variables. Among socioeconomic and trip characteristics, gender, education, driving license, egress mode, access time, and trip origin type (i.e., work, education, etc.) were also important in passenger satisfaction.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T04:02:25Z
      DOI: 10.1177/0361198120931846
       
  • Novel Three-Stage Framework for Prioritizing and Selecting Feature
           Variables for Short-Term Metro Passenger Flow Prediction
    • Authors: Yangyang Zhao, Lu Ren, Zhenliang Ma, Xinguo Jiang
      Abstract: Transportation Research Record, Ahead of Print.
      AbstractShort-term metro passenger flow prediction is vital for the operation and management of metro systems. Most studies focus on the higher prediction accuracy with statistical and machine learning methods, but little attention has been paid to the prioritization and selection of feature variables, especially for different metro station types. This study aims to analyze the effect of feature variables on the prediction results, and then select appropriate predictor variables accordingly. A novel three-stage framework is proposed to prioritize feature variables for short-term metro passenger flow prediction, including station clustering, feature extraction, and variable prioritization. A hierarchical clustering algorithm (AHC) is developed for station clustering, the results of which are verified by the K-means and Davies-Bouldin (DB) statistical index. We then extract the temporal, spatial, and external features. Finally, the association between the variables and the prediction results is explored using tree-based models. The proposed framework is demonstrated and validated with data collected from Shanghai Metro Automatic Fare Collection (AFC) system. The results highlight that the importance of feature variables for developing models varies between stations, whereas only a few variables are found to explain most of the variation in the testing dataset; different feature variables lead to distinct differences in prediction accuracy, and simply adding more predictor variables does not necessarily lead to higher prediction accuracy. In addition, the station type and prediction type (i.e., tap-in and tap-out) have little influence on the selection of feature variables.
      Citation: Transportation Research Record
      PubDate: 2020-07-07T02:38:44Z
      DOI: 10.1177/0361198120926504
       
  • Performance of Hot and Cold Recycled Mixtures with High Reclaimed Asphalt
           Pavement Content
    • Authors: Edith Arámbula-Mercado, Santiago J. Chavarro-Muñoz, Sheng Hu, Howie Moseley
      Abstract: Transportation Research Record, Ahead of Print.
      Florida Department of Transportation yearly maintenance and rehabilitation activities include milling and resurfacing of approximately 2,000 lane miles of roadway, with an average resurfacing depth of about 2.1 in. (55 mm). These activities result in the generation and accumulation of roughly 1.8 million tons of reclaimed asphalt pavement (RAP) each year. The use of elevated quantities of RAP in asphalt pavement provides an environmentally responsible solution to the accumulated RAP surplus in some urban areas, while at the same time offering an economical pavement maintenance and rehabilitation option to local agencies facing budget constraints. The objective of this project was to compare the performance of mixtures with 60% RAP content to be used primarily on low volume roads (average daily traffic
      Citation: Transportation Research Record
      PubDate: 2020-07-06T05:46:54Z
      DOI: 10.1177/0361198120931510
       
  • Using Conditional Generative Adversarial Nets and Heat Maps with
           Simulation-Accelerated Training to Predict the Spatiotemporal Impacts of
           Highway Incidents
    • Authors: Zirui (Raymond) Huang, Ali Arian, Yuqiu (Rachael) Yuan, Yi-Chang Chiu
      Abstract: Transportation Research Record, Ahead of Print.
      An increasingly emphasized research area is the forecast of short-term traffic conditions for nonrecurring traffic dynamics caused by random highway incidents such as crashes or roadway closures. This research proposes a prediction framework which focuses on training a machine learning (ML) model to predict the speed heatmap associated with incidents. Heatmaps contain ideal information that depicts the spatiotemporal characteristics of incident-induced impacts and are suitable objects for ML models to understand and predict. Because of the sparsity of incident data in the real world, we proposed a simulation approach to rapidly expand the training dataset, thus speeding up the model training process. The conditional deep convolutional generative adversarial nets is employed to predict the speed heatmap and the mesoscopic dynamic traffic assignment model DynusT was used to generate many training data. The evaluation shows that the proposed model captures both the tonal and spatial distribution of pixel values at 80.19% similarity between the prediction and actual heatmaps. To the best of our knowledge, this is one of the first attempts in the literature to train ML to predict heatmap representation of incident-induced spatiotemporal impact, and speeding up the training via simulation.
      Citation: Transportation Research Record
      PubDate: 2020-07-05T07:05:23Z
      DOI: 10.1177/0361198120925069
       
  • Quantification of Sources of Variability of Air Pollutant Exposure
           Concentrations Among Selected Transportation Microenvironments
    • Authors: H. Christopher Frey, Disha Gadre, Sanjam Singh, Prashant Kumar
      Abstract: Transportation Research Record, Ahead of Print.
      The National Research Council has identified the lack of sufficient microenvironmental air pollution exposure data as a significant barrier to quantification of human exposure to air pollution. Transportation microenvironments, including pedestrian, transit bus, car, and bicycle, can be associated with higher exposure concentrations than many other microenvironments. Data are lacking that provide a systematic basis for comparing exposure concentrations in these transportation modes that account for key sources of variability, such as time of day, season, and types of location along a route such as bus stops and intersections. The objectives of this work are: to quantify and compare particulate matter (PM2.5), CO, and O3 exposure concentrations in selected active and passive transportation microenvironments; and to quantify the effect of season, time of day, and location with respect to variability in transportation mode exposure concentrations. Measurements were made with an instrumented backpack and were repeated for multiple days in each season to account for the effect of inter-run variability. Results include mean trends, spatial variability, and contribution to variance. Pedestrian and cycle mode exposure concentrations were approximately similar to each other and were substantially higher than for bus and car cabins for both PM2.5 and O3. Based on over 30 days of field measurements conducted over three seasons and for two times of day on weekdays, transportation mode and season were the largest contributors to variability in exposure for PM2.5 and O3, whereas location type alone and in combination with transport mode helped explain variability in CO exposures.
      Citation: Transportation Research Record
      PubDate: 2020-07-05T07:05:22Z
      DOI: 10.1177/0361198120929336
       
  • Bidirectional Spatial–Temporal Network for Traffic Prediction with
           Multisource Data
    • Authors: Tuo Sun, Chenwei Yang, Ke Han, Wanjing Ma, Fan Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Urban traffic congestion has an obvious spatial and temporal relationship and is relevant to real traffic conditions. Traffic speed is a significant parameter for reflecting congestion of road networks, which is feasible to predict. Traditional traffic forecasting methods have poor accuracy for complex urban road networks, and do not take into account weather and other multisource data. This paper proposes a convolutional neural network (CNN)-based bidirectional spatial–temporal network (CNN-BDSTN) using traffic speed and weather data by crawling electric map information. In CNN-BDSTN, the spatial dependence of traffic network is captured by CNN to compose the time-series input dataset. Bidirectional long short-term memory (LSTM) is introduced to train the convolutional time-series dataset. Compared with linear regression, autoregressive integrated moving average, extreme gradient boosting, LSTM, and CNN-LSTM, CNN-BDSTN presents its ability of spatial and temporal extension and achieves more accurately predicted results. In this case study, traffic speed data of 155 roads and weather information in Urumqi, Xinjiang, People’s Republic of China, with 1-min interval for 5 months are tested by CNN-BDSTN. The experiment results show that the accuracy of CNN-BDSTN with input of weather information is better than the scenario of no weather information, and the average predicted error is less than 5%.
      Citation: Transportation Research Record
      PubDate: 2020-07-05T07:05:20Z
      DOI: 10.1177/0361198120927393
       
  • Establishing Face and Content Validity of a Survey to Assess Users’
           Perceptions of Automated Vehicles
    • Authors: Justin Mason, Sherrilene Classen, James Wersal, Virginia P. Sisiopiku
      Abstract: Transportation Research Record, Ahead of Print.
      Fully automated vehicles hold promise for providing numerous societal benefits, including drastically reducing road fatalities. However, we know little about the adoption practices of individuals related to automated vehicles. To assess transportation users’ perceptions of automated vehicles, a 40-item survey was designed using guidance from several technology acceptance models. A focus group was used to assess face validity to ensure the items appeared credible and understandable to the layperson. Seven subject-matter experts rated items for their relevance to provide a content validity index for each item and for the overall survey. The final scale had a scale content validity index rating of 1.00, with 32 of 32 items rated greater than or equal to 0.86 and a scale content validity index of 0.96 (mean content validity index of all items), indicating acceptable content validity. The approach adopted in this study ensured the face and content validity of the survey and enhanced the items’ relevance, concision, and clarity. Future validation is required to assess scale reliability and validity. The paper provides an overview of models used for determining acceptance and adoption of technology and describes in detail the methodology used to establish face and content validity of the questionnaire survey developed for assessing adults’ perceptions of automated vehicles.
      Citation: Transportation Research Record
      PubDate: 2020-07-05T07:05:20Z
      DOI: 10.1177/0361198120930225
       
  • Deep Reinforcement Learning Agent with Varying Actions Strategy for
           Solving the Eco-Approach and Departure Problem at Signalized Intersections
           
    • Authors: Saleh R. Mousa, Sherif Ishak, Ragab M. Mousa, Julius Codjoe, Mohammed Elhenawy
      Abstract: Transportation Research Record, Ahead of Print.
      Eco-approach and departure is a complex control problem wherein a driver’s actions are guided over a period of time or distance so as to optimize fuel consumption. Reinforcement learning (RL) is a machine learning paradigm that mimics human learning behavior, in which an agent attempts to solve a given control problem by interacting with the environment and developing an optimal policy. Unlike the methods implemented in previous studies for solving the eco-driving problem, RL does not require prior knowledge of the environment to be learned and processed. This paper develops a deep reinforcement learning (DRL) agent for solving the eco-approach and departure problem in the vicinity of signalized intersections for minimization of fuel consumption. The DRL algorithm utilizes a deep neural network for the RL. Novel strategies such as varying actions, prioritized experience replay, target network, and double learning were implemented to overcome the expected instabilities during the training process. The results revealed the significance of the DRL algorithm in reducing fuel consumption. Interestingly, the DRL algorithm was able to successfully learn the environment and guide vehicles through the intersection without red light running violation. On average, the DRL provided fuel savings of about 13.02% with no red light running violations.
      Citation: Transportation Research Record
      PubDate: 2020-07-04T11:33:24Z
      DOI: 10.1177/0361198120931848
       
  • Toward the Integration of Paratransit in Transportation Planning in
           African Cities
    • Authors: Virginie Boutueil, Gaele Lesteven, Luc Nemett
      Abstract: Transportation Research Record, Ahead of Print.
      This research examines the history of transportation planning in African cities and how paratransit has been taken into account in the production of planning documents. On the rise since the 1980s, paratransit today is the most common motorized transportation mode in many African cities. The dominant approach among policymakers has been to limit paratransit, in some cases even to ban it. The question this research explores is how distrust of paratransit, and underappreciation of its intrinsic qualities, have been reflected in urban transportation plans. Having selected two cities—Cape Town, South Africa and Nairobi, Kenya—we conducted an in-depth analysis of planning documents at national and local levels. South Africa has a long tradition of transportation planning, with documentation available at the national, provincial, and municipal levels. In the 1990s, paratransit was a national-level concern. It gradually became a municipal issue with the implementation of Bus Rapid Transit (BRT). In Kenya, planning has a shorter history. Development agencies (e.g., Japanese International Cooperation Agency [JICA]) have played a key role in recent planning processes and encourage the formalization of paratransit. However, planning documents contain no explicit references to “matatus.” In both cities, the focus in the documents is still mainly on developing infrastructure rather than improving mobility. While the role of paratransit is increasingly recognized, this trend is still more apparent in regulation than in planning.
      Citation: Transportation Research Record
      PubDate: 2020-07-03T08:50:19Z
      DOI: 10.1177/0361198120933270
       
  • Machine Learning Approach for Flight Departure Delay Prediction and
           Analysis
    • Authors: Ehsan Esmaeilzadeh, Seyedmirsajad Mokhtarimousavi
      Abstract: Transportation Research Record, Ahead of Print.
      The expected growth in air travel demand and the positive correlation with the economic factors highlight the significant contribution of the aviation community to the U.S. economy. On‐time operations play a key role in airline performance and passenger satisfaction. Thus, an accurate investigation of the variables that cause delays is of major importance. The application of machine learning techniques in data mining has seen explosive growth in recent years and has garnered interest from a broadening variety of research domains including aviation. This study employed a support vector machine (SVM) model to explore the non-linear relationship between flight delay outcomes. Individual flight data were gathered from 20 days in 2018 to investigate causes and patterns of air traffic delay at three major New York City airports. Considering the black box characteristic of the SVM, a sensitivity analysis was performed to assess the relationship between dependent and explanatory variables. The impacts of various explanatory variables are examined in relation to delay, weather information, airport ground operation, demand-capacity, and flow management characteristics. The variable impact analysis reveals that factors such as pushback delay, taxi-out delay, ground delay program, and demand-capacity imbalance with the probabilities of 0.506, 0.478, 0.339, and 0.338, respectively, are significantly associated with flight departure delay. These findings provide insight for better understanding of the causes of departure delays and the impacts of various explanatory factors on flight delay patterns.
      Citation: Transportation Research Record
      PubDate: 2020-07-03T03:38:45Z
      DOI: 10.1177/0361198120930014
       
  • Uncovering Deep Structure of Determinants in Large Truck Fatal Crashes
    • Authors: Subasish Das, Mouyid Islam, Anandi Dutta, Tahmida Hossain Shimu
      Abstract: Transportation Research Record, Ahead of Print.
      The number of fatalities and severe injuries in large truck-related crashes has significantly increased since 2009. According to the safety experts, the recent increase in large truck-related crashes can be explained by the significant growth in freight tonnage all over the U.S. over the past few years. This notable freight-haul growth has allowed continuous day–night movement of freight on roads and highways, exposing the trucks to a greater number of potential crashes or near-crash scenarios. There are many ongoing research efforts that aim to identify the different factors that influence large truck crashes; however, further research with innovative approaches is still needed to better understand the relationship between crash-related factors. In this study, the project team applied taxicab correspondence analysis (TCA), a data-mining method known for dimension reduction, to large truck fatal crash data to investigate the complex interaction between multiple factors under a two-dimensional map. For this study, 6 years (2010–2015) of large truck fatal crash data from the Fatality Analysis Reporting System (FARS) were used. The study found five clusters of attributes that show patterns of association between different crash attributes such as two-lane undivided roadways, intersection types, posted speed limit, crash types, number of vehicles, driver impairment, and weather. The findings of this study will help the safety professionals, trucking industry, and policymakers to make decisions for safer road design, and improvement in truck driver training, and education.
      Citation: Transportation Research Record
      PubDate: 2020-07-02T10:25:55Z
      DOI: 10.1177/0361198120931507
       
  • Investigation of Thermal Sensation in a Railway Vehicle during Cooling
           Period
    • Authors: Gökhan Sevilgen, Gürcan Sayaral, Muhsin Kiliç, Halil Bayram
      Abstract: Transportation Research Record, Ahead of Print.
      The paper presents an investigation of local thermal comfort of passengers in a railway vehicle. The railway vehicle model includes five different parts called modules, and each module had different properties such as passenger capacity and seating arrangement. A virtual manikin model was developed and added to the numerical model which includes convection and radiation heat transfer between the human body and the environment. The numerical simulation was conducted according to the EN 14750-1 standard describing the thermal comfort conditions for different climatic zones. Two different cases were performed for steady-state conditions. Meanwhile, measurements were taken in a railway vehicle cabin to validate the numerical simulation, and the numerical results were in good agreement with the experimental data. It is observed that the local heat transfer characteristics of the human body have significant importance for the design of an effective heating, ventilation, and air conditioning (HVAC) system because each module had different heat transfer and air flow characteristics. It is also shown that the thermal sensation (TSENS) index helps railway vehicle HVAC researchers to determine the reasons for discomfort zones of each occupant. Another important result is that using a single air flow channel did not meet the thermal comfort demands of all passengers in this railway vehicle. Therefore, multiple air flow channel design configurations should be considered and developed for these vehicles. Local thermal comfort models allow HVAC systems to achieve better comfort conditions with energy saving. The numerical model can be used for effective module design, including seating arrangements, to achieve better thermal comfort conditions.
      Citation: Transportation Research Record
      PubDate: 2020-07-02T10:25:36Z
      DOI: 10.1177/0361198120935874
       
  • Fleet Sizing for Pooled (Automated) Vehicle Fleets
    • Authors: Milos Balac, Sebastian Hörl, Kay W. Axhausen
      Abstract: Transportation Research Record, Ahead of Print.
      This paper proposes an (automated) on-demand public transport service using different vehicle capacities to serve current car demand in cities. The service relies on space and time aggregation of passengers that have similar origins and destinations. It provides a point-to-point service with predefined pick-up and drop-off locations. In this way, detours to pick-up en-route passengers is avoided. The optimization problem that minimizes the fleet size along with limiting rebalancing distances is defined as a mixed-integer linear programming problem. Solving the problem for Zurich, Switzerland, yields, in the best case, a fleet size equal to 3.7% of the current fleet that could serve current car demand. Vehicle kilometers traveled could also be reduced by nearly 10%. Results also show that the speed of automated vehicles has a substantial effect on the necessary fleet size and free-flow speeds generally produce over-optimistic results.
      Citation: Transportation Research Record
      PubDate: 2020-07-02T03:23:26Z
      DOI: 10.1177/0361198120927388
       
  • Measuring the Applicability of Intersection-Based Older Driver Training
           Programs
    • Authors: Craig A. Schneider, Foroogh Hajiseyedjavadi, Francis Tainter, Michael Knodler, Jingyi Zhang, Matthew Romoser, Siby Samuel, Donald Fisher
      Abstract: Transportation Research Record, Ahead of Print.
      Older drivers remain overrepresented in intersection crashes. Previous evidence suggests that the primary reason for this lies with their lack of scanning for potential threat vehicles while entering stop-controlled intersections. More so, secondary glances prove critical when the conditions obscure potential threat vehicles while approaching the intersection. Currently, simulator-based older driver training programs have proven effective in increasing the frequency of secondary glances taken by older drivers up to 2 years following the training. However, both the need for a full-scale driving simulator and participant dropout rates because of simulator sickness within training programs continue to limit the applicability of these alternatives. This study used a series of micro-scenarios to train older drivers in secondary glances, thus reducing the potential for participant dropouts resulting from simulator sickness. In addition, driver immersion levels varied across multiple training platforms, ranging from low to medium. A total of 91 participants between 67 and 86 years old were assigned to one of five groups. Three groups were provided active, secondary glance training on a driving simulator (one on a low immersion simulator and two on medium immersion simulators), a fourth group was provided passive training using a PowerPoint presentation, and the last group was a control with no training. Following training, all participants were evaluated in their personal vehicles while wearing head-mounted cameras. The medium immersion group resulted in the highest percentage of secondary glances (82%), whereas the control group resulted in the lowest percentage (42%). The results provide evidence to suggest that the training programs using micro-scenarios in medium and low immersion simulators can increase the frequency of secondary glances without having high dropout rates caused by simulator sickness.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T09:24:19Z
      DOI: 10.1177/0361198120932566
       
  • Predicting Commercial Vehicle Parking Duration using Generative
           Adversarial Multiple Imputation Networks
    • Authors: Raymond Low, Zeynep Duygu Tekler, Lynette Cheah
      Abstract: Transportation Research Record, Ahead of Print.
      As the world rapidly urbanizes in pace with economic growth, the rising demand for products and services in cities is putting a strain on the existing road infrastructure, leading to traffic congestion and other negative externalities. To mitigate the impacts of freight movement within commercial areas, city planners have begun focusing their attention on the parking behaviors of commercial vehicles. Unfortunately, there is a general lack of information on such activities because of the heterogeneity of practices and the complex nature of urban goods movement. Furthermore, field surveys and observations of truck parking behavior are often faced with significant challenges, resulting in the collection of sparse and incomplete data. The objective of this study is to develop a regression model to predict the parking duration of commercial vehicles at the loading bays of retail malls and identify significant factors that contribute to this dwell time. The dataset used in this study originates from a truck parking and observation survey conducted at the loading bays of nine retail malls in Singapore, containing information about the trucks’ and drivers’ activities. However, because of the presence of incomplete fields found in the dataset, the authors propose the use of a generative adversarial multiple imputation networks algorithm to impute the incomplete fields before developing the regression model using the imputed dataset. Through the parking duration model, the activity type, parking location, and volume of goods delivered (or picked up) were identified as significant features influencing vehicle dwell time, corroborating with findings in the literature.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T09:24:00Z
      DOI: 10.1177/0361198120932166
       
  • Effect of Manual Traffic Control on Evacuation Time Estimates
    • Authors: Scott A. Parr, Nelida Herrera, Brian Wolshon, Todd Smith
      Abstract: Transportation Research Record, Ahead of Print.
      Manual traffic control (MTC) is a common intersection control strategy where trained personnel, typically police law enforcement officers, allocate intersection right-of-way to approaching vehicles. MTC is frequently used for special events and during emergencies. However, the current state-of-the-practice has shown little research that quantifies or assesses the benefits of MTC during evacuations. This paper describes research to develop microscopic traffic simulation models that were used to assess traffic processes of emergency evacuations of nuclear power plant sites involving MTC. A recently developed model to represent MTC was integrated into the simulation to quantify its impact on clearance time and other operational parameters. The results of this effort showed that in rural or less congested urban areas clearance times experienced no significant benefit from the application of MTC. Conversely, in densely populated regions clearance times increased significantly when MTC was deployed. This suggested that for congested urban areas, with closely spaced intersections, the characteristically long cycle lengths associated with MTC resulted in significant queues. These queues propagated upstream, interfering with traffic operations at neighboring intersections and bottleneck points within the network. This, in turn, triggered even more queues and, ultimately, led to localized gridlock. From the perspective of police officers, longer cycle lengths result in fewer phase changes and less lost-time at the intersection. As such, the officer is incentivized to extend green times and cycle lengths as long as possible. What the officer cannot see, however, is the effect of such actions on queue formation at upstream intersections.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T09:21:59Z
      DOI: 10.1177/0361198120932165
       
  • Process for the Encapsulation and Visualization of Dominant Demand and
           Supply Corridors
    • Authors: Jeudy Yann, Catherine Morency
      Abstract: Transportation Research Record, Ahead of Print.
      Before thinking about implementing new transportation services, it is essential to assess the performances of the available ones and to develop an objective diagnosis of the adequacy between transportation supply and demand. This paper focuses on the refinement of a spatial–temporal clustering process able to encapsulate the spatial distribution of travel demand and supply. It illustrates the potential of such process to assist in the development of an objective diagnosis of the quality of the configuration of transit services. The two tools composing this process are presented in this paper, Traclus_DL and Grille_CR. A literature review is conducted on the main concepts such as corridors and grids, which will give a better understanding of the contributions proposed in this paper. Traclus_DL is a spatial clustering algorithm for desire lines (direct line from origin to destination) developed by Bahbouh. This paper will explain how this algorithm works and will also present improvements that were implemented to facilitate its usage and to give a better representation of the reality. Grille_CR is an automated smoothing tool which facilitates the visualization and the interpretation of the results produced by Traclus-DL. This paper explains how this process can be implemented and illustrates its relevance for public transport analysis and design. The major contribution of this paper is the implementation of a tool which helps better understand the spatial configuration of the demand in transport.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T09:21:20Z
      DOI: 10.1177/0361198120931843
       
  • Review of Agency Pavement Recycling Construction Specifications
    • Authors: Benjamin F. Bowers, David E. Allain, Brian K. Diefenderfer
      Abstract: Transportation Research Record, Ahead of Print.
      Cold in-place recycling, cold central plant recycling, and full depth reclamation are cost-effective, environmentally conscious pavement rehabilitation or reconstruction techniques. Although these techniques are not new, they have not been widely adopted among state agencies. There has, however, been a recent resurgence in interest in these techniques. To date there are no national specification guidelines for these processes to assist in their widespread implementation, and those specifications that do exist often have a wide range of requirements. This paper presents the results of a review of state and local agency specifications for pavement recycling techniques and offers suggestions to help agencies achieve a better and longer-lasting product when specifying pavement recycling techniques.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T09:13:59Z
      DOI: 10.1177/0361198120931503
       
  • Improving the Durability of High Early Strength (HES) Concrete Patching
           Materials for Concrete Pavements
    • Authors: Cameron Wilson, W. Jason Weiss
      Abstract: Transportation Research Record, Ahead of Print.
      High early strength (HES) concrete patching materials are increasingly used to repair damaged pavements. The use of HES concrete enables the repaired pavement to be opened to traffic shortly after the repair has been installed; for example, opening pavements to traffic 4–6 h after the concrete is placed is becoming more common. HES concrete mixtures are typically designed with a low water-to-cement ratio and a high cement content; they contain accelerating admixtures and limited supplementary cementitious materials. As a result, these HES patches may be susceptible to self-desiccation, causing autogenous shrinkage and early age cracking. Self-desiccation can lead to reduced hydration, limited strength gain, and overestimation of strength development in maturity-based predictions. The objectives of this study are threefold. First, the paper will illustrate how self-desiccation can lead to the premature cessation of hydration and increased potential for shrinkage cracking. Second, the paper will illustrate how maturity-based predictions can be modified to account for self-desiccation. Third, internal curing is discussed as a way to mitigate self-desiccation and shrinkage ultimately improving the performance of HES concrete patching materials.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T09:13:40Z
      DOI: 10.1177/0361198120917374
       
  • Moving Beyond CAP-X to Combinations of Alternative Intersections That
           Might Be Worth Further Investigation
    • Authors: Joseph E. Hummer
      Abstract: Transportation Research Record, Ahead of Print.
      Many intersection project sites in North Carolina, and probably across the U.S., have asymmetric conditions. There is typically heavier demand from one approach than the others, right of way is more restricted in one or two quadrants than in the others, pedestrian demand is concentrated in one crosswalk, and so forth. However, the literature on alternative intersections and the software that planners and engineers use to explore suitable alternatives primarily provide symmetric and full designs. Analysts reading the FHWA guidebooks on alternative designs or looking at the menus of CAP-X or VJUST would be led to believe that their options were limited. Fortunately, in the past few years it has become apparent that there are many more intersection design options than presented in CAP-X or VJUST. The objective of this paper is to demonstrate that designers can combine pieces of the alternatives in many creative ways to find asymmetric designs that better fit whatever asymmetric conditions they are given. This paper shows some hybrid at-grade and grade-separated intersection designs that seem to have potential to increase efficiency, increase the quality of the pedestrian and bicyclist crossing experience, decrease impacts, and have other benefits. Based on these examples, it should be apparent that many interesting combinations are possible. Designers wanting to explore a hybrid cannot use the usual software to do so, but the tools to analyze a hybrid design are available if one knows where to look.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T09:13:00Z
      DOI: 10.1177/0361198120925467
       
  • Workforce Development Needs and Objectives of Today’s Transportation
           Engineering Professionals
    • Authors: Kevin N. Chang, Benjamin Lutz, Shane Brown
      Abstract: Transportation Research Record, Ahead of Print.
      Given the growing influence of technology and innovation, the skill set and knowledge required of today’s transportation engineering professional includes many different subject areas. For this reason, transportation engineers and managers alike must constantly seek out workforce development opportunities to expand either their learning or the skill set of their employees. This study examined transportation education needs from a Pacific Northwest regional perspective on two fronts. First, an assessment was initiated identifying available course training offerings and their curriculum and delivery characteristics. Second, an investigation into training needs was conducted using a mixed-method approach consisting of personal interviews and an online survey. This study concluded that although training is a highly personal decision and influenced by many different factors, those related to cost, location, and topic area ultimately drive an individual or agency to pursue such opportunities. These findings can inform both practitioners and researchers to strategically determine how future training opportunities should be developed and shaped to meet the growing demands of tomorrow’s transportation engineer.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:31Z
      DOI: 10.1177/0361198120926995
       
  • Exploring the Equity of Traditional and Ride-Hailing Taxi Services during
           Peak Hours
    • Authors: Renbin Pan, Hongtai Yang, Kun Xie, Yi Wen
      Abstract: Transportation Research Record, Ahead of Print.
      Many people criticize the inequity of traditional taxi (TT) services and believe the entry of ride-hailing taxis (RT) can address the issue. However, this has been understudied in the literature. This paper aims to estimate the equity of TT  and RT services during peak hours and to study how the entry of RT affects equity by analyzing trip data of TT and RT in New York City in 2010 and 2017 (before and after the entry of RT). First, we used the Lorenz curve and the Gini coefficient to estimate the equity of taxi services against population and employment. The results show that the equity of RT in 2017 is higher than that of TT  and the equity of TT + RT in 2017 is higher than that of 2010. Mixed geographically weighted regression (MGWR) was applied to determine whether the relationships between taxi trips and population/employment would vary across different taxi zones. The coefficient of variation (CV) of local coefficients of population/employment is used as an indicator of equity. Results show that RT services were more equitable than TT services in 2017 and that the overall taxi service in 2017 was more equitable than that of 2010.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:31Z
      DOI: 10.1177/0361198120928338
       
  • Photogrammetry-Based Method to Determine the Absolute Volume of Soil
           Specimen during Triaxial Testing
    • Authors: Sara Fayek, Xiaolong Xia, Lin Li, Xiong Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Triaxial tests are used extensively to evaluate stress-strain behavior for both saturated and unsaturated soils. A literature review indicates that all conventional triaxial test methods measure the relative volume of soil; however, between the initial measurements and the start of the triaxial tests, there are unavoidably disturbances during installation that cause deviation of soil volume from that at the initial condition. Recently image-based methods have been developed to measure the absolute volume of soil specimens. However, these methods still have a major limitation in their inability to determine top and bottom boundaries between the soil specimen, and the top and bottom caps. This paper proposes a photogrammetry-based method to overcome this limitation by developing a mathematically rigorous technique to determine the upper and lower boundaries of soil specimens during triaxial testing. The photogrammetry technique was used to determine the orientations of the camera, and the shape and location of the acrylic cell. Multiple ray-tracings and least-square optimization techniques were also applied to obtain the coordinates of any point inside the triaxial cell, and thus back-calculate the upper and lower boundaries. With these boundaries and the side surface, a triangular surface mesh was constructed and the specimen volume was then calculated in both unconfined compression tests and triaxial tests. The calculation procedures are presented in detail with validation tests performed on a cylindrical specimen to evaluate the accuracy of the method. Results indicate that the accuracy of the proposed method is up to 0.023% in unconfined compression tests and 0.061% in triaxial tests.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:29Z
      DOI: 10.1177/0361198120928339
       
  • Eighty-Five Percent Solution: Historical Look at Crowdsourcing Speed
           Limits and the Question of Safety
    • Authors: Brian D. Taylor, Yu Hong Hwang
      Abstract: Transportation Research Record, Ahead of Print.
      The “85th percentile rule” is commonly used to set speed limits in jurisdictions across the U.S. Modern interpretations of the rule are that it satisfies key conditions needed for safe roadways: it sets speed limits deemed reasonable to the typical, prudent driver, reduces the problematic variance in travel speeds among vehicles, and allows law enforcement to focus on speeding outliers. Authoritative publications regularly assert that the rule came about because early driving surveys often found that drivers moving at or below the 85th percentile of a speed on a given roadway were within one standard deviation of the mean speed for that roadway and were in the low involvement group for traffic incidents. But does this widely used rule for setting speed limits really have such a scientific pedigree' Given debates in cities around the U.S. about competing uses of street space, we examine where this rule of driver-set speed limits actually came from and whether rule developers’ rationales still hold true today. While most observers trace the rule to safety research and a 1964 report, we find that the 85th percentile rule actually emerged decades earlier amidst the nascent traffic engineering profession’s preoccupation with “traffic service” to increase vehicular throughput; and with respect to safety, the rule was explicitly intended as a starting point in speed limit setting, and not the last word.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:28Z
      DOI: 10.1177/0361198120928995
       
  • Trip Generation Rates of Land Uses in a Developing Country City
    • Authors: Tanjeeb Ahmed, Suman Kumar Mitra, Rezwana Rafiq, Sanjana Islam
      Abstract: Transportation Research Record, Ahead of Print.
      In recent decades, a major shift in the land use pattern has been observed in Dhaka, the capital city of Bangladesh. To understand and model the impact of these land use changes on transportation demand, this study aimed to determine the trip generation rates for six different land use categories adjacent to Mirpur Road in Dhaka. A total of 20 establishments consisting of six land use categories were selected for the collection of data on person trip rates and respective modal share by manual counts and intercept surveys. These data were used to develop vehicular trip generation rates for each land use category in passenger car equivalents as a uniform unit of comparison. Results showed that commercial and healthcare land uses had the highest average and peak-hour trip rates. There was also a significant variation in the share of eight transport mode categories among the trips generated by the land uses. The peak-hour trip generation rates of the study area were found to be different from the values established by the Institute of Transportation Engineers which corresponds to the fact that trip generation depends on a host of factors, such as surrounding land uses, modal share, the economic condition of a region, and so forth, rather than on a single factor inherent to the land use. The findings of this research can help to determine the trip generation impact of new establishments and consequently identify suitable locations to minimize the impact.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:28Z
      DOI: 10.1177/0361198120929327
       
  • Influence of Lane Width on Semi- Autonomous Vehicle Performance
    • Authors: Alfredo García, Francisco Javier Camacho-Torregrosa
      Abstract: Transportation Research Record, Ahead of Print.
      In the medium-term, the number of semi-autonomous vehicles is expected to rise significantly. These changes in vehicle capabilities make it necessary to analyze their interaction with road infrastructure, which has been developed for human-driven vehicles. Current systems use artificial vision, recording the oncoming road and using the center and edgeline road markings to automatically facilitate keeping the vehicle within the lane. In addition to alignment and road markings, lane width has emerged as one of the geometric parameters that might cause disengagement and therefore must be assessed. The objective of this research was to study the impact of lane width on semi-autonomous vehicle performance. The automatic lateral control of this type of vehicle was tested along 81 lanes of an urban arterial comprising diverse widths. Results showed that the semi-autonomous system tended to fail on narrow lanes. There was a maximum width below which human control was always required—referred to as the human lane width—measuring 2.5 m. A minimum width above which automatic control was always possible—the automatic lane width—was established to be 2.75 m. Finally, a lane width of 2.72 m was found to have the same probability of automatic and human lateral control, namely the critical lane width. Following a similar methodology, these parameters could be determined for other vehicles, enhancing the interaction between autonomous vehicles and road infrastructure and thus supporting rapid deployment of autonomous technology without compromising safety.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:26Z
      DOI: 10.1177/0361198120928351
       
  • Applicability of Photogrammetry for Inspection and Monitoring of Dry-Stone
           Masonry Retaining Walls
    • Authors: Alexandra Hain, Arash E. Zaghi
      Abstract: Transportation Research Record, Ahead of Print.
      Dry-stone masonry retaining walls are vulnerable to bulging and leaning because of the lack of cohesion between stones. Currently, the structural integrity of these walls is mainly assessed by qualitative judgments informed by visual inspections. Photogrammetry has the potential to increase the quality and objectivity of retaining wall inspections. This technology uses a series of images to generate a detailed 3D model of a structure. Currently, this technology is most commonly used in civil engineering applications for mapping large areas, often using aerial photographs. In this study, photogrammetry is used in two field trials to evaluate its ability to create accurate, high-resolution 3D representations of masonry retaining walls in Connecticut. The 3D models were used to document the current in-situ conditions to provide a baseline for future comparisons, as well as show cross sections of vulnerable areas, such as bulges or tilts. In one trial, data were collected on two dates to show the progression of movement of the wall. This paper gives an overview of best practices for data collection and discusses results and observations from the field trials. The generated 3D models provide an enhanced form of inspection documentation including detailed representations of geometry and colors. The contribution of this paper is to provide material facilitating the adoption of this promising technology for the inspection of masonry retaining walls and other transportation infrastructure.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:26Z
      DOI: 10.1177/0361198120929184
       
  • Exploring the Effect of Timely Reminder on Maritime Unsafe Acts
    • Authors: Dong Xu, Ying Wang
      Abstract: Transportation Research Record, Ahead of Print.
      Unsafe acts are a primary cause of maritime accidents, but timely reminders can evaluate improper behavior and provide alerts to prompt correction. This paper investigates whether timely reminders can discourage unsafe acts. First, data in relation to participants’ unsafe acts according to different psychological frames were collected on the basis of an experiment conducted on a navigation simulator. The effects of timely reminders on unsafe acts were then analyzed through the independent-samples Kruskal–Wallis test and regression analysis. The results demonstrate that the introduction of timely reminders could significantly reduce the number of unsafe acts committed by crew members during voyages. Moreover, the framing effect influenced the intervention results; under less stressful conditions, a timely reminder with the gain frame more effectively discourages unsafe acts than does a reminder with the loss frame. By contrast, under more stressful conditions, the loss frame exhibits advantages over the gain frame with respect to sending timely reminders to reduce the occurrence of unsafe acts. Compared with novices, experienced seafarers are less sensitive to the effects of timely reminders in the process of ship operation, whether with the gain frame or loss frame. After the three major challenges of functional subdivision, situational complexity, and mechanism robustness are discussed, two suggestions are proposed: an integrated system for automatically detecting unsafe acts that sends out corresponding timely reminders and an onboard organizational management mechanism.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:25Z
      DOI: 10.1177/0361198120925460
       
  • Development of a Risk Assessment Module for Bridge Management Systems in
           New Jersey
    • Authors: Graziano Fiorillo, Hani Nassif
      Abstract: Transportation Research Record, Ahead of Print.
      Bridges are critical for the mobility of our society and its economic growth. Available funds for bridge repair, maintenance, and rehabilitation are limited. The Moving Ahead for Progress in the 21st Century Act (MAP-21) introduced several new parameters for improving the management of bridge assets, such as bridge element evaluation, life-cycle analysis, and risk-based performance indicators. Risk-based methods account for the uncertainties embedded into engineering variables and long-term evaluations. The objective of this paper is to identify, assess, and quantify structural risk components to bridges using probabilistic risk methodologies and data from the National Bridge Inventory database. The aim is to simplify the implementation of risk-based ranking procedures into bridge management system packages according to the MAP-21 vision. Therefore, machine learning techniques are employed to facilitate the introduction of probabilistic risk methods into bridge management systems. The procedure is described for seven hazards that are pertinent to bridges in New Jersey: overloading, fatigue, seismic, flooding, scour, vehicle and vessel collision. Risk values are computed in monetary terms to homogenize the comparison among bridges for different hazards. The analysis is performed on 5,534 bridges, showing that seismic events and fatigue resulting from truck overloading are the most dominant hazards in New Jersey, for which about 97.0% and 29.0% of bridges show some level of risk. The main limitation of the proposed framework is the lack of accurate data from bridge inventories necessary to thoroughly perform a fully structural probabilistic analysis of bridges and to minimize engineering judgment.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:24Z
      DOI: 10.1177/0361198120929016
       
  • User-Rated Comfort and Preference of Separated Bike Lane Intersection
           Designs
    • Authors: Christopher M. Monsere, Nathan W. McNeil, Rebecca L. Sanders
      Abstract: Transportation Research Record, Ahead of Print.
      Improved bicycle infrastructure has become increasingly common in the United States as cities seek to attract new riders, including the demographic who do not feel comfortable riding with motor vehicle traffic. A key tool in designing low-stress networks is the use of separated or protected bicycle lanes, and intersections are the critical links. This paper presents an analysis of the perceived level of comfort of current and potential bicyclists from 277 survey respondents who rated 26 first-person video clips of a bicyclist riding through mixing zones, lateral shifts, bend-in, bend-out, and protected intersection designs. A total of 7,166 ratings were obtained from surveys conducted at four locations in Oregon, Minnesota, and Maryland, including urban and suburban locations. Survey respondents were categorized into four groups based on their response to attitudes and bicycling behavior by cluster analysis. Descriptive analysis and regression modeling results find that designs that minimize interactions with motor vehicles, such as fully separated signal phases and protected intersections, are rated as most comfortable (72% of respondents rated them as very comfortable or somewhat comfortable). Mean comfort drops off significantly for other designs and interactions with turning vehicles result in lower comfort ratings though there are differences for each design. Importantly, as the exposure distance, measured as the distance a person on a bicycle is exposed to traffic, increases the comfort decreases.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:22Z
      DOI: 10.1177/0361198120927694
       
  • Quantification of the Effect of Binder Source on Flexibility of Long-Term
           Aged Asphalt Concrete
    • Authors: Zehui Zhu, Punit Singhvi, Uthman Mohamed Ali, Hasan Ozer, Imad L. Al-Qadi
      Abstract: Transportation Research Record, Ahead of Print.
      Asphalt concrete (AC) aging reduces the resistance of flexible pavements to fatigue, thermal, and block cracking. Therefore, it is critical to understand the effects of AC aging on flexible pavement serviceability. Binder source has a significant effect on AC long-term aging. Therefore, it is necessary to develop a reliable, practical, and systematic method to quantify the effect of binder source on AC cracking resistance. Seven laboratory mixes were designed and produced at three asphalt binder replacement (ABR) levels using various binders, but same binder performance grade (PG). The AC mixes were tested using the Illinois Flexibility Index Test (I-FIT) under unaged and long-term aged conditions. Standard Superpave tests and temperature-frequency sweep tests, were conducted on virgin binders under various aging conditions. By comparing the binder rheological parameters and flexibility index (FI) of long-term aged AC specimens, the [math] and m-value after 40-h of aging using a pressure aging vessel (PAV) were identified as valid indicators to reflect the effects of the binder source on AC long-term flexibility. A minimum [math] of -8°C and m-value of 0.280 were proposed as the preliminary thresholds. A new parameter, [math], which is defined as the m-value of 20-h PAV-aged binder minus the m-value of a 40-h PAV-aged binder, correlates well with the aging rate of AC. A binder with a high [math] may induce an excessive drop in flexibility after long-term aging.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:22Z
      DOI: 10.1177/0361198120930717
       
  • Development of a Test Level 4, Side-Mounted, Steel Tube Bridge Rail
    • Authors: Jennifer D. Rasmussen, Scott K. Rosenbaugh, Ronald K. Faller, Robert W. Bielenberg, Joshua S. Steelman, Oscar Pena, Pascual Mauricio
      Abstract: Transportation Research Record, Ahead of Print.
      A new, side-mounted, steel beam-and-post bridge rail was designed, crash tested, and evaluated according to safety performance guidelines included in the American Association of State Highway and Transportation Officials Manual for Assessing Safety Hardware (MASH) for Test Level 4 (TL-4). The new bridge rail system was designed to be compatible with multiple bridge decks, including cast-in-place concrete slabs and prestressed box beams. Additionally, the bridge rail was designed to remain crashworthy after roadway overlays up to 3 in. thick. The bridge rail was designed and optimized based on strength, installation cost, weight per foot, and constructability. The new bridge rail consisted of three rectangular steel tube rails supported by standard steel cross section, W6 × 15 steel posts spaced at 8 ft on-center. The upper rail was a 12 × 4 × ¼ in. hollow structural section (HSS) steel tube, and the lower two rails were 8 × 6 × ¼ in. HSS steel tubes. The top mounting heights for the upper, middle, and lower rails were 39 in., 32 in., and 20 in. above the surface of the deck, respectively. A new, side-mounted, post-to-deck connection was also developed that incorporated HSS steel spacer tubes that offset the posts 6 in. from the bridge deck and aligned the face of the bridge rail with the edge of the deck. Thus, the traversable width of the bridge was maximized. Three full-scale crash tests corresponding to the MASH TL-4 testing matrix were performed on the new bridge rail. All three crash tests successfully contained and redirected the vehicles and satisfied all MASH evaluation criteria.
      Citation: Transportation Research Record
      PubDate: 2020-07-01T02:52:21Z
      DOI: 10.1177/0361198120930227
       
  • Exploration of Hazardous Material Truck Crashes on Wyoming’s Interstate
           Roads using a Novel Hamiltonian Monte Carlo Markov Chain Bayesian
           Inference
    • Authors: Irfan U. Ahmed, Sherif M. Gaweesh, Mohamed M. Ahmed
      Abstract: Transportation Research Record, Ahead of Print.
      Crash severity of a hazardous material (HAZMAT) transporting truck increases manyfold compared with normal truck crash because of the possible exposure to dangerous substances. Crashes which involve a HAZMAT truck might result in a catastrophic incident causing horrendous damage to individuals involved in the crash. In-transit HAZMAT crashes in Wyoming caused a total damage of $3.1 million from 2015 to 2018. HAZMAT crashes on interstate roads represented 22% of the total HAZMAT crashes causing a total damage of $2.2 million, representing 71% of the cost of total damage. Previous studies in Wyoming investigated all vehicle crashes, including large truck crashes, but none has analyzed HAZMAT-related crashes or accounted for its type as a contributing factor. This study fills the gap by analyzing crash injury severity of HAZMAT-related crashes on all interstate freeways in Wyoming. Furthermore, the study introduces the No-U-Turn (NUT) Hamiltonian Monte Carlo (HMC) method of hierarchical Bayesian analysis into HAZMAT crash injury severity analysis. In recent developments, NUT HMC has been proven to be the most efficient Markov Chain Monte Carlo (MCMC) sampling method. The results showed that 30% of the unobserved heterogeneity arises from variation in summer and winter crashes which justifies the use of hierarchical model. Among the other covariates investigated, the population-averaged effects showed that number of trucks involved, hit-and-run crashes, animal-vehicle crashes, work-zone-related crashes, collision type, percentage of females involved, drivers’ drug/alcohol use, seat-belt use, crash location, roadway curves, and surface conditions significantly impact HAZMAT crash injury severity.
      Citation: Transportation Research Record
      PubDate: 2020-06-30T09:57:43Z
      DOI: 10.1177/0361198120931103
       
  • Application of a Hurdle Model with Random Effects to Explore the
           Relationship between Operational Characteristics and Safety Performance
    • Authors: Jianrong Qiu, David B. Logan, Jennifer Oxley, Christopher Lowe
      Abstract: Transportation Research Record, Ahead of Print.
      This study used the bus incident data in Victoria, Australia to establish the relationship between operational characteristics and the safety performance of bus operators. A series of count models were investigated to account for methodological challenges, including excess zeros and panel data structure. The empirical results highlighted the different effects operational characteristics had on the risk and prevalence of bus incidents. Operators of smaller size, providing non-route services and operating in regional areas had a lower risk of having any reported incidents compared with larger route operators and operators in areas of higher accessibility. In cases where at least one incident had been reported, incident frequency was higher for operators with higher fleet total travel distance, older fleets and better roadworthy performance (this factor being counterintuitive). Findings from this study provide safety regulators with evidence-driven opportunities to enhance bus safety, including improving incident reporting practices, the establishment of a comprehensive database for heavy vehicle operators, and specific efforts targeted at older fleets.
      Citation: Transportation Research Record
      PubDate: 2020-06-30T03:21:18Z
      DOI: 10.1177/0361198120928074
       
  • Novel Approach for Calibrating Freeway Highway Multi-Regimes Fundamental
           Diagram
    • Authors: Emmanuel Kidando, Alican Karaer, Boniphace Kutela, Angela E. Kitali, Ren Moses, Eren E. Ozguven, Thobias Sando
      Abstract: Transportation Research Record, Ahead of Print.
      For almost a century, several models have been developed to calibrate the pairwise relationship between traffic flow variables, that is, speed, density, and flow. Multi-regime models are well known for being superior over single-regime models in fitting the speed–density relationship. However, in modeling multi-regime models, breakpoints that separate the regimes are visually established based on the subjective judgment of data characteristics. Thus, this study proposes a data-driven approach to estimate the breakpoints of multi-regime models. It applies the Bayesian model for calibrating multi-regime models (two and three-regime models) for fitting traffic flow fundamental diagram. Furthermore, the analysis presented accounts for the random characteristics associated with the flow. To demonstrate the application of the proposed algorithm, traffic flow data from Interstate 10 (I-10) freeway in Jacksonville, Florida, were used in the analysis. The results demonstrate the potential benefit of using the proposed model in calibrating the fundamental diagram. The proposed approach can also quantify uncertainty and encode prior knowledge about the breakpoints in the model if the model developer wishes.
      Citation: Transportation Research Record
      PubDate: 2020-06-30T03:21:17Z
      DOI: 10.1177/0361198120930221
       
  • How Built Environment Impacts Online Car-Hailing Ridership
    • Authors: Hui Bi, Zhirui Ye, Chao Wang, Enhui Chen, Yiwu Li, Xiaoming Shao
      Abstract: Transportation Research Record, Ahead of Print.
      Extensive research has shown that unilateral optimization of transit systems is not effective enough to significantly increase its transport efficiency. Considering that urban land-use characteristics, including residential, work, consumption, transit, and so forth, are significantly interrelated with travel demands and travel behaviors, this paper provides a way to optimize transit system by raising awareness of the relation between ridership and built environment. This paper adopted point of interest (POI) data to investigate the effect of physical built environment on online car-hailing ridership in Chengdu, China. The study area was tessellated with several Voronoi cells; these cells were further clustered into three ridership patterns based on the time-varying characteristic of ridership. Given that some differences existed in the three ridership patterns, a separate spatial ridership model was developed to understand the factors that influence ridership patterns using geographic weighted regression (GWR) analysis. The data and results verified that the built environment had various influences on online car-hailing alighting ridership in spatial and temporal dimensions, of which the significant POI factors for determining the ridership pattern during different periods were detected. Remarkably, this study took the ridership dataset from the online car-hailing transit system, mainly because the pick-up (PU) and drop-off (DO) locations generated by this service are closest to the origin and destination of the trip, except that it is more popular recently. Therefore, the analysis of the impact of built environment on travel based on the online car-hailing dataset can be captured in greater detail, with a higher degree of accuracy.
      Citation: Transportation Research Record
      PubDate: 2020-06-27T10:04:02Z
      DOI: 10.1177/0361198120924630
       
  • Evaluation of the Moisture Dependence of Concrete Coefficient of Thermal
           Expansion and Its Impacts on Thermal Deformations and Stresses of Concrete
           Pavements
    • Authors: Angel Mateos, John Harvey, Dulce Rufino Feldman, Rongzong Wu, Julio Paniagua, Fabian Paniagua
      Abstract: Transportation Research Record, Ahead of Print.
      The coefficient of thermal expansion (CTE) is one of the material properties of concrete that has the largest impact on rigid pavement performance. Concrete CTE is typically measured in the laboratory, under saturated conditions, or estimated on the basis of the mix constituents, past experience, or both. Whichever method is used, the mechanistic-empirical design of concrete pavements traditionally assumes a constant value for this material property. This assumption has important consequences in relation to predicting thermal deformations and stresses since the CTE of concrete actually changes with the concrete’s internal moisture conditions. The experimental data presented in this study show that this assumption, together with the way CTE is measured in the laboratory, leads to systematic underestimates of thermal deformations and stresses in concrete pavements. The experimental data come from six concrete overlays of asphalt pavements that were instrumented with thermocouples, relative humidity sensors, and vibrating wire strain gauges to measure the expansion/contraction and bending of the slabs because of temperature and moisture-related actions. The apparent CTE of the overlay slabs reached values up to 65% larger than the CTE measured in the laboratory under saturated conditions. Using finite element method modeling, it was determined that thermal stresses were up to 70% larger than predicted using the saturated CTE.
      Citation: Transportation Research Record
      PubDate: 2020-06-27T10:04:01Z
      DOI: 10.1177/0361198120925463
       
  • Vehicle Trajectory Specification in Presence of Traffic Lights with Known
           or Uncertain Switching Times
    • Authors: Panagiotis Typaldos, Ioanna Kalogianni, Kyriakos Simon Mountakis, Ioannis Papamichail, Markos Papageorgiou
      Abstract: Transportation Research Record, Ahead of Print.
      The main purpose of this work is to generate optimal trajectories for vehicles crossing a signalized junction, with traffic signals operated in either fixed-time or real-time (adaptive) mode. In the latter case, the next switching time is decided in real time based on the prevailing traffic conditions and is therefore uncertain in advance. The GLOSA (Green Light Optimal Speed Advisory) problem is addressed by using traffic lights information and calculating a trajectory and velocity profile for the vehicle based on the vehicle’s initial state (position and speed) and a fixed final destination state. At first, an appropriate optimal control problem is formulated and solved analytically via Pontryagin’s minimum principle (PMP) for the case of known switching times. Subsequently, for the case of real-time signals, availability of a time-window of possible signal switching times, along with the corresponding probability distribution, is assumed, and the problem is cast in the format of a stochastic optimal control problem and is solved numerically using stochastic dynamic programming (SDP) techniques. Application results, for various driving scenarios, of the deterministic approach, which considers the case of known switching times, and a comprehensive comparison of the stochastic GLOSA approach with a sub-optimal approach are presented. In particular, it is demonstrated that the proposed SDP approach achieves better average performance compared with the sub-optimal approach because of the better (probabilistic) information on the traffic light switching time.
      Citation: Transportation Research Record
      PubDate: 2020-06-27T10:04:00Z
      DOI: 10.1177/0361198120922996
       
  • Incorporating Demographic Proportions into Crash Count Models by
           Quasi-Induced Exposure Method
    • Authors: Sadia Sharmin, John N. Ivan, Shanshan Zhao, Kai Wang, Md Julfiker Hossain, Nalini Ravishanker, Eric Jackson
      Abstract: Transportation Research Record, Ahead of Print.
      Quasi-induced exposure (QIE) is an effective technique for estimating the exposure of a specific driving or vehicle population when real exposure data are not available. Typically crash prediction models are carried out at the site level, that is, segment or intersection. Driving population characteristics are generally not available at this level, however, and thus are omitted from count models. Because of the sparsity of traffic crashes, estimating driving population distributions at the site level using crash data at individual sites is challenging. This study proposes a technique to obtain demographic proportions to incorporate in the count models as an exposure at each site by aggregating similar adjacent sites until significant demographic proportions are obtained. Information on driver gender, age, and vehicle type are obtained by QIE using five years (2010–2014) of crash data; and road inventories are obtained for 1,264 urban four-lane divided highway segments in California. Count models including only site level factors were compared with models including both crash level and site level factors. The latter outperformed the former in relation to mean prediction bias and mean absolute deviation statistics on holdout sample predictions. Results indicate that teen drivers are more crash prone in total and in fatal plus injury severity crashes. For senior drivers, crash risk increases with the increase in severity level. The presence of vehicles other than passenger cars and trucks reduces total and property damage only crash counts. Female drivers are associated with higher total and fatal plus injury crash counts.
      Citation: Transportation Research Record
      PubDate: 2020-06-27T10:03:59Z
      DOI: 10.1177/0361198120930230
       
  • Assessing and Extending Track Quality Index for Novel Measurement
           Techniques in Railway Systems
    • Authors: Tzu-Hao Yan, Francesco Corman
      Abstract: Transportation Research Record, Ahead of Print.
      A systematic maintenance process is essential to keeping railway systems safe and reliable. However, performing such maintenance is costly and often results in system disruption. There is a tradeoff between system safety and budgetary constraints; understanding the condition of the track infrastructure is essential to find the balance between needs and costs for decisions about when to perform maintenance. In this study, the track quality index (TQI), which is commonly used to evaluate the status of tracks and to decide maintenance interventions, is reviewed, including 12 TQIs for superstructure and six for substructure. A literature review indicates that TQIs for sleepers and subgrade have not yet been developed. The differences between TQIs are compared using a set of hypothetical raw data. Their capabilities for identifying track irregularities are also investigated based on the EN 13848 regulations. To classify TQI characteristics in a systematic way, this study proposes four concepts: accuracy, sensitivity, data required, and specificity. Accuracy indicates a TQI’s capability of detecting defects; sensitivity indicates how TQIs change according to variations in the defects; specificity relates to the amount of parameters considered, and the ability to pinpoint root causes or global consequences of defects. The results suggest a tradeoff between the four concepts, where high sensitivity can increase the ability to detect the smallest defects but may be affected by bias; more parameters considered may indicate low accuracy when detecting a single type of defect. Therefore, this study suggests railway regulators use multiple TQIs with complementary characteristics for classifying track status.
      Citation: Transportation Research Record
      PubDate: 2020-06-26T05:53:55Z
      DOI: 10.1177/0361198120923661
       
  • Experimental Findings with VISSIM and TransModeler for Evaluating
           Environmental and Safety Impacts using Micro-Simulations
    • Authors: Zhijin Song, Huizi Wang, Jian Sun, Ye Tian
      Abstract: Transportation Research Record, Ahead of Print.
      Micro-simulation packages provide an efficient and systematic approach to depicting traffic dynamics. Nonetheless, many of these models used by the micro-simulation packages are only calibrated with respect to observed traffic indicators such as average speed, traffic count, and so forth, while omitting non-traffic indicators. This paper aims to investigate the performance of VISSIM and TransModeler when depicting non-traffic indicators such as fuel consumption, emissions, and safety. A model was first calibrated for traffic indicators based on Next Generation SIMulation (NGSIM) trajectories. Results indicated that after calibration, simulation accuracy was still unsatisfactory with regard to energy consumption and emission measurements, with errors of up to 38.23% in VISSIM. In assessing safety, the relative error of VISSIM increased from 12.36% to 59.92% after calibration. The error in TransModeler increased to almost 100%. Furthermore, this study explored the simulation accuracy of VISSIM and TransModeler under different traffic conditions and discovered that the models’ accuracies were relatively high when simulating stop-and-go traffic. We also explored the causes of these observed differences through a regression model. This study presents practical insight into the deficiencies of micro-simulation related research, and based on error analysis, provides a theoretical reference for optimizing simulation accuracy from a novel perspective.
      Citation: Transportation Research Record
      PubDate: 2020-06-26T05:53:53Z
      DOI: 10.1177/0361198120925077
       
  • Micro Level Speed Choice Behavior on a Rural Highway in an Heterogeneous
           Traffic Environment: Latent Class Modeling Approach
    • Authors: S. M. Sohel Mahmud, Luis Ferreira, Md. Shamsul Hoque, Ahmad Tavassoli
      Abstract: Transportation Research Record, Ahead of Print.
      The modeling of driver speed choice behavior on a rural highway with heterogeneous traffic environment in a developing country is reported. The study explores the application of a latent class model as an alternative methodological approach, to relate factors such as road geometry, roadside environment, traffic mix and operational characteristics with speed choice at the micro level. In the conventional analysis based on lane-based homogeneous traffic environments, the impact of exogenous variables is kept constant across road segments; whereas those impacts might vary across different segments for different conditions. To check this possible variation, the study compares latent class linear regression with ordinary least square, as well as the random parameter linear regression model. The proposed models were estimated using data collected from two sections of a major national highway in Bangladesh. The entire roadway section was divided into several small segments and the critical segment length was estimated based on several sensitivity tests. The small segmental level exogenous variables were considered for the model building and estimation. The results obtained could be used to understand better the speed choice factors of drivers in the non-lane-based traffic environments of developing countries. Law enforcement agencies, traffic operation and maintenance officials, as well as roadway design and planning authorities, could gainfully use the findings of this study to inform more responsive speed management strategies.
      Citation: Transportation Research Record
      PubDate: 2020-06-25T03:57:12Z
      DOI: 10.1177/0361198120926994
       
  • Link Cost Function and Link Capacity for Mixed Traffic Networks
    • Authors: Aathira K. Das, Bhargava Rama Chilukuri
      Abstract: Transportation Research Record, Ahead of Print.
      Link cost function and link capacity are critical factors in traffic assignment modeling. Popular link cost functions like the Bureau of Public Roads (BPR) function have well-known drawbacks and are not suitable for mixed traffic conditions where a variety of vehicle classes use the road in a non-lane-based movement. Similarly, capacity is generally considered as a constant value. However, in mixed traffic conditions, capacity is not constant, but a function of vehicle class composition. Toward addressing these issues, this paper proposes a link cost function in relation to link travel time and link capacity in relation to vehicular traffic flow for mixed traffic conditions. The functions are developed based on the kinematic wave model, which is popularly used for estimating traffic dynamics on the roads. The developed link cost function and link capacity use field measurable parameters that incorporate mixed traffic features. The functions are validated against empirical data obtained from 12 signal cycles from two different signalized intersections in Chennai, India, representing different scenarios of mixed traffic, and it was found that the results match well with the empirical data.
      Citation: Transportation Research Record
      PubDate: 2020-06-25T03:57:10Z
      DOI: 10.1177/0361198120926454
       
  • Exploring the Causes of Social Exclusion Related to Mobility for
           Non-Motorized Households
    • Authors: Dominic Villeneuve, Vincent Kaufmann
      Abstract: Transportation Research Record, Ahead of Print.
      Using a lexicometric and qualitative data analysis of 57 semi-directed interviews with members of non-motorized households in the urban areas of Quebec City (Canada) and Strasbourg (France), this paper attempts to show whether living in a carless household in a car-dependent environment fosters feelings of social exclusion and if so, what the contributing factors are. Overall, a majority of respondents said they experienced feelings of social exclusion. Several factors were identified. The lack of consideration of non-motorized households in transportation planning processes and mobility policymaking appear to be important factors. In addition, many respondents perceived that they were not on an equal footing with drivers when it came to policy decisions. Motorized individuals with whom they interacted with, for example, in the workplace, also sometimes negatively judged and misunderstood their carless colleagues. Some also felt excluded from the job market, whereas others perceived exclusion from late evening social functions because of limited public transit schedules. Finally, not being able to get to certain places was often cited as a negative factor.
      Citation: Transportation Research Record
      PubDate: 2020-06-25T01:52:16Z
      DOI: 10.1177/0361198120926167
       
  • Novel Framework for the Quantification of Pavement Damages in the Overload
           Corridors
    • Authors: Ali Morovatdar, Reza S. Ashtiani, Carlos Licon, Cesar Tirado, Enad Mahmoud
      Abstract: Transportation Research Record, Ahead of Print.
      Recent traffic trends and permit issuance show significant mobility demands in the energy sectors across the nation. The increase in the axle loads and frequency of operations of over-weight (OW) trucks resulted in severe damage to transportation infrastructures. Traditionally, the damage imparted by OW vehicles has been quantified by means of the equivalent axle load factors (EALFs) concept. However, because of the nature of assumptions in the development of damage equivalency factors, the field distresses substantially deviate from the prediction models. Therefore, this study aimed to bridge this gap by developing a mechanistic framework to determine damage equivalency factors tailored toward the specific characteristics of OW vehicles operating in the OW corridors, while considering the environmental conditions and the unique features of transportation facilities in the network. To achieve this objective, initially, the authors devised a plan to collect traffic information using portable weigh-in-motion devices at two intervals for 10 representative sites in the energy corridors of Eagle Ford Shale region. Subsequently, a series of nondestructive tests were conducted in the field to determine the material properties of the pavement layers for further numerical simulations. This information was further incorporated into a 3D finite element system to calculate critical input parameters in the modified damage factor models. The proposed mechanistic approach confirmed that the modified damage factors were substantially higher compared with traditional industry-standard values. Further investigation of environmental factors and pavement profiles in this study underscored the significance of these components for accurate assessment of the damage equivalency factors.
      Citation: Transportation Research Record
      PubDate: 2020-06-25T01:51:56Z
      DOI: 10.1177/0361198120925807
       
  • Empirical Analysis of Long-Run Elasticities and Asymmetric Effects of
           Transit Demand Determinants
    • Authors: Lisa Li, Dena Kasraian, Amer Shalaby
      Abstract: Transportation Research Record, Ahead of Print.
      The effects of transit ridership determinants can be quantified as demand elasticities which are often used to inform transit planning and policy making. This study seeks to determine the impacts of transit service supply, fare, and gas prices on ridership by quantifying the short-run and long-run demand elasticities, as well as test whether transit ridership exhibits an asymmetric response to the rise and fall of these factors using a panel data of 99 Canadian transit agencies over the period of 2002–2016. The results of the dynamic panel model show the effects of transit service and fare to be greater in the long run. The short-run fare elasticity was found to be –0.24 while the long-run elasticity was –1.1. Furthermore, the demand elasticity with respect to service levels was also found to be inelastic (0.28) in the short run but elastic (1.3) in the long run. The cross-elasticity of gas prices was estimated to be 0.17. The existence of asymmetry was analyzed using decomposition techniques to separately estimate the coefficients for the rise and fall in each of the determinants. The equality of these coefficients was tested against each other and it was found that ridership responded more to an increase in transit supply than a decrease. The importance of these results to policy making are then discussed.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T12:45:44Z
      DOI: 10.1177/0361198120925465
       
  • Development and Testing of a Test Level 4 Concrete Bridge Rail and Deck
           Overhang
    • Authors: Scott K. Rosenbaugh, Jennifer D. Rasmussen, Ronald K. Faller
      Abstract: Transportation Research Record, Ahead of Print.
      A Manual for Assessing Safety Hardware (MASH)-compliant Test Level 4 (TL-4) concrete bridge rail was optimized to satisfy MASH TL-4 design loads, maximize vehicle stability, minimize installation costs, and mitigate the potential for deck damage by minimizing loads transfer to the deck. Additionally, the bridge rail was designed with a 39 in. installation height so that it would remain crashworthy after future roadway overlays up to 3 in. thick. The barrier had a front face with a 3-degree slope from vertical to promote vehicle stability during impacts while also providing some slope to allow for slipforming installations. Yield line theory was utilized to design both interior and end regions of the barrier. Further, minimum deck strengths were determined and a deck overhang design procedure was provided for users desiring to modify their existing deck details. Finally, MASH Test 4-12 was conducted on the new bridge rail to evaluate its safety performance criteria, damage to the barrier and a critical deck configuration, and its working width. In test 4CBR-1, the 22,198 lb single-unit truck impacted the concrete bridge rail at a speed of 57.6 mph and an angle of 16 degrees. The single-unit truck was successfully contained and redirected, and all safety performance criteria were within acceptable limits as defined in MASH. Therefore, test 4CBR-1 was determined to be acceptable according to MASH Test 4-12. Conclusions and recommendations for implementation are provided.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T06:11:26Z
      DOI: 10.1177/0361198120924406
       
  • Methodology for Determination of the Structural Layer Coefficient of
           Unbound Base Materials in Florida
    • Authors: Hyunchul Hwang, Dennis R. Hiltunen
      Abstract: Transportation Research Record, Ahead of Print.
      The main goal of this study was to assess methodologies for the determination of base structural layer coefficients (SLCs) in Florida base materials. The aim was to streamline the traditional empirical and observationally based technique for determining layer coefficients either by an accelerated loading process or by the computer simulation of pavement performance. The paper describes a methodology in which the structural numbers (SN) of two paired test sections are used to backcalculate the unknown SLC. The SNs are determined from the AASHTO performance equation using a prediction of pavement performance from the University of Florida top-down cracking (TDC) model. The paper presents a positive application of the methodology for two test sections in Louisiana and two sections in Florida.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T06:10:56Z
      DOI: 10.1177/0361198120924662
       
  • Practice Friendly Metric for Identification of Critical Links in Road
           Networks
    • Authors: Amirmasoud Almotahari, Anil Yazici
      Abstract: Transportation Research Record, Ahead of Print.
      Despite the important planning value of transportation link criticality, the existing methodologies are mostly in the academic domain, and require in-depth technical skills and extensive data. The most common approach to identify critical links in transportation networks is to remove each link iteratively, conduct traffic assignment, and assess the criticality of each link based on the consequences of its removal. Since conducting multiple traffic assignment is costly for large networks, the authors of this paper recently introduced the link criticality index (LCI). The LCI utilizes the iterations in the Frank–Wolfe solution of the user equilibrium (UE) problem to provide link criticality ranking within a single traffic assignment. The LCI was shown to provide balanced rankings with respect to alternative routes as well as the link flows. However, the LCI is not practice-friendly because of the technical knowledge and data needed to run traffic assignments. Accordingly, this paper introduces a practice friendly link criticality index (PF-LCI). PF-LCI relaxes some of the technical requirements and uses some expert knowledge input data to provide “top” link criticality rankings that are consistent with the LCI. PF-LCI utilizes the network flow instances at different times of day instead of iterations of UE assignment solution. Expert knowledge input is sought for the major origin–destination pairs (ODs) and the viable routes between the selected ODs. The method is implemented on a small sample network and the Sioux Falls network to test PF-LCI’s capabilities. Results show that PF-LCI produces accurate rankings for the top critical links that are most relevant to practitioners’ concerns.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T06:06:16Z
      DOI: 10.1177/0361198120925475
       
  • Predicting Long-Term Coefficient of Thermal Expansion of Paving Concrete
    • Authors: Gauhar Sabih, Rafiqul A. Tarefder
      Abstract: Transportation Research Record, Ahead of Print.
      The coefficient of thermal expansion (CTE) of concrete is an important parameter that affects the design and performance analysis of concrete pavements. Higher CTE value results in increased curling and related stresses. A 28-day CTE value is used for designing rigid pavements. Though previous studies have revealed that coarse aggregate mineralogy has substantial effects on the CTE value of paving concrete, it is not known yet how CTE value changes with the age of concrete in the long-term. In this study, seven concrete mixes with different coarse aggregate mineralogy are tested in the laboratory and data is analyzed to examine CTE. Results show that limestone has the lowest CTE values compared with other coarse aggregates. Concrete CTE increases from 6.4% to 12.6% as it ages. This increase in CTE may result in increased thermal distresses as concrete pavement ages. Therefore, a single value of 28-day CTE should not be used in the design of concrete pavements. In this study, a prediction model is developed to determine aged CTE incorporating mixture volumetrics and concrete strength properties. The same can be incorporated in Pavement Mechanistic Empirical (ME) Design software to better predict the rigid pavement performance.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T06:05:37Z
      DOI: 10.1177/0361198120931852
       
  • Using Stochastic Variation of Cyclic Green Distributions to Populate SAE
           J2735 Message Confidence Values along a Signalized Corridor
    • Authors: Jijo Mathew, Howell Li, Darcy M. Bullock
      Abstract: Transportation Research Record, Ahead of Print.
      The communication between connected vehicles and traffic signal controllers is defined in SAE Surface Vehicle Standard J2735. SAE J2735 defines traffic signal status messages and a series of 16 confidence levels for traffic signal transitions. This paper discusses a statistical method for tabulating traffic signal data by phase and time of day and populating the SAE J2735 messages. Graphical representations of the red–green and green–yellow transitions are presented from six intersections along a 4-mile corridor for five different time-of-day timing plans. The case study provided illustrates the importance of characterizing the stochastic variation of traffic signals to identify locations, phases, and time-of-day periods when traffic indications operate with high predictability. Specific cases, such as low vehicle demand and occasional actuation of pedestrian phases are highlighted as situations that may reduce the predictability of traffic signal change intervals. The results from this study also open up discussion among transportation professionals on the importance of consistent tabulation of confidence values for both beginning and end of green signal states. We believe this paper will initiate dialog on how to consistently tabulate important data elements transmitted in SAE J2735 and perhaps refine those definitions. The paper concludes by highlighting the importance of traffic engineers and connected vehicle developers to work together to develop shared visions on traffic signal change characteristics so that the in-vehicle use cases and human–machine interface meet user expectations.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T04:17:32Z
      DOI: 10.1177/0361198120929337
       
  • Predicting the Future Capacity and Dimensions of Container Ships
    • Authors: Javier Garrido, Sergi Saurí, África Marrero, Ümit Gül, Carles Rúa
      Abstract: Transportation Research Record, Ahead of Print.
      Since the introduction of the container ship, there has been an impressive increase in its use to take advantage of economies of scale. In the last two decades, the capacity of vessels has trebled. Currently, vessels of 23,000 TEU (20-ft equivalent unit) sail the seas. With the exponential growth experienced in this sector, the question arises if it is possible to reach a peak capacity, as has occurred with bulk cargo vessels and, recently, aircraft. This paper aims to predict the possible size and dimensions of a new generation of mega container ships. Based on economies of scale, port infrastructure, demand, environmental trends, and naval design criteria, the limit to ship size has been estimated. The results suggest that additional increases in ship size are still possible. The aim of this study is to help port authorities to understand the needs of the shipping container industry and to calculate the expansion and investment necessary.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T04:17:31Z
      DOI: 10.1177/0361198120927395
       
  • Computational Fluid Dynamics as a Tool to Estimate Hydraulic Conductivity
           of Permeable Asphalts
    • Authors: Veronica Fedele, Nicola Berloco, Pasquale Colonna, Ashton Hertrich, Paolo Intini, Vittorio Ranieri, John J. Sansalone
      Abstract: Transportation Research Record, Ahead of Print.
      Hydraulic conductivity (k) is critical for designing permeable pavements for safety and environmental reasons. A novel approach for estimating k is through computational fluid dynamics (CFD) applied to permeable asphalt (PA). Specimens of PA are examined in this study to evaluate CFD applicability. Tortuosity, effective porosity, pore size distribution, and specific surface area were determined based on three-dimensional specimen structures reconstructed using x-ray tomography analyses. Using CFD, estimates of k were determined and compared with physical measurements and also with the results obtained from the semi-empirical modified Kozeny-Carman model (KCM). The comparison shows that the numerical simulations with CFD can be a reasonable tool for estimating k and for examining transport of water through PA. Within the constraints of this study, results infer that CFD can provide more representative results for low k in comparison with KCM. For higher k, CFD and KCM results were reasonably comparable.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T04:17:30Z
      DOI: 10.1177/0361198120927390
       
  • Studying Car-Following Dynamics on the Basis of the HighD Dataset
    • Authors: Valentina Kurtc
      Abstract: Transportation Research Record, Ahead of Print.
      A large-scale naturalistic vehicle trajectory dataset from German highways, highD, was used to investigate the car-following behavior of individual drivers. These data include trajectories of 110,000 vehicles recorded for a duration of 16.5 h. Solving a nonlinear optimization problem, the intelligent driver model and the optimal velocity model with two leaders in interaction were calibrated by minimizing the deviations between the observed and simulated gaps when following the prescribed leading vehicle. The obtained calibration errors ranged between 5.2% and 6.9%, which were slightly lower than previous findings. This was explained by the shorter highD trajectories, predominantly free-flow traffic, and the good precision metrics of this dataset. The optimal velocity model with multivehicle anticipation resulted in lower calibration errors. This confirmed that natural drivers take into account several leading vehicles ahead. The ratio between interdriver and intradriver variability was investigated by performing global and platoon calibrations. Intradriver variation accounted for a larger portion of the calibration errors than interdriver variation. We analyzed the acceleration time-series of the natural highD and artificial drivers using simulations of two car-following models. A new cumulative measure, proportional to the energy of the follower’s position time-series curve, was calculated both for natural and modeled drivers. Human drivers had higher energy and demonstrated more acceleration fluctuations, sometimes behaving irrationally. In contrast, artificial drivers followed the logical rules incorporated in the model, resulting in a smoother acceleration profile. This led to less fuel consumption and gas emissions.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T04:16:53Z
      DOI: 10.1177/0361198120925063
       
  • Understanding the Role of Cycling to Urban Transit Stations through a
           Simultaneous Access Mode and Station Choice Model
    • Authors: Danique Ton, Sanmay Shelat, Sandra Nijënstein, Lotte Rijsman, Niels van Oort, Serge Hoogendoorn
      Abstract: Transportation Research Record, Ahead of Print.
      Governments worldwide are aiming to increase sustainable mode use to increase sustainability, livability, and accessibility. Integration of bicycle and transit can increase catchment areas of transit compared with walking and thus provide better competition to non-sustainable modes. To achieve this, effective measures have to be designed that require a better understanding of the factors influencing access mode and station choice. At the national/regional level this has been thoroughly studied, but there is a knowledge gap at the urban level. This study aims to investigate which factors influence the joint decision for tram access mode and tram station choice. The joint investigation can identify trade-offs between the access and transit journeys. Furthermore, the effect of each factor on the bicycle catchment area is investigated. Using data from tram travelers in The Hague, Netherlands, a joint simultaneous discrete choice model is estimated. Generally, walking is preferred to cycling. The findings of this study suggest that access distance is one of the main factors for explaining the choice, where walking distance is weighted 2.1 times cycling distance. Frequent cyclists are more likely also to cycle to the tram station, whereas frequent tram users are less inclined to cycle. Bicycle parking facilities increase the cycling catchment area by 234 m. The transit journey time has the largest impact on the catchment area of cyclists. Improvements to the system, such as fewer stops, higher frequency (like light rail transit), or both, therefore would result in a much longer accepted cycling distance.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T04:16:52Z
      DOI: 10.1177/0361198120925076
       
  • Investigation of Moisture Damage in Open Graded Asphalt Friction Course
           Mixtures with Basic Oxygen Furnace Steel Slag as Coarse Aggregate under
           Acidic and Neutral pH Environments
    • Authors: Santanu Pathak, Rajan Choudhary, Abhinay Kumar
      Abstract: Transportation Research Record, Ahead of Print.
      Open graded asphalt friction courses (OGAFCs) are specialty asphalt mixtures used to improve skid resistance and surface drainage. OGAFCs have additional benefits of reduced splash and spray, and lower tire–pavement interaction noise. Prolonged exposure to rainwater and load transfer through stone-on-stone contact in OGAFCs demands aggregates that are strong and hydrophobic. Rainwater acidity is expected to affect the aggregate–asphalt bond and thus moisture damage performance of OGAFC. This paper investigates the effect of rainwater acidity on moisture sensitivity of OGAFC mixtures with different aggregate types (natural aggregate, basic oxygen furnace (BOF) steel slag, and combinations of both) and modified binder types. For the first time, the present research reports the moisture damage potential of BOF OGAFC mixtures under different moisture conditioning environments created by varying the pH of contact water. With different combinations of BOF slag and natural aggregates (100:0, 25:75, 50:50, 75:25, and 0:100), and binders (polymer and crumb rubber modified), OGAFC mixtures were characterized for moisture damage through tensile strength ratio, wet Cantabro abrasion loss, and modified boiling water tests. Functional aspects of OGAFC mixtures subjected to moisture conditioning under different pH environments were also evaluated through permeability testing. Results showed that an acidic environment exacerbated the moisture damage, however, OGAFC mixtures containing BOF slag showed better performance than the control mixture (with natural aggregates only). Inclusion of BOF slag in OGAFC mixtures enhanced resistance to moisture damage under both pH environments. OGAFC mixes with 100% BOF slag content performed the best considering all moisture damage tests under both conditioning environments.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T04:16:52Z
      DOI: 10.1177/0361198120925459
       
  • Investigating Market Potentials and Operational Scenarios of Virtual
           Coupling Railway Signaling
    • Authors: Joelle Aoun, Egidio Quaglietta, Rob M. P. Goverde
      Abstract: Transportation Research Record, Ahead of Print.
      The new concept of virtual coupling (VC) envisages autonomous trains running in radio-connected platoons to significantly improve railway capacity and address the forecasted increase in railway demand. Such a concept will introduce radical changes to current train services, technologies, and procedures, which calls for a deeper understanding of the possible modes of operation and the impacts on the entire railway business. This paper investigates market potentials and operational scenarios of VC for different segments of the railway market: high-speed, main-line, regional, urban, and freight trains. The research builds on the Delphi method, with an extensive survey to collect expert opinions about benefits and challenges of VC as well as stated travel preferences in futuristic VC applications. Survey outcomes show that VC train operations can be very attractive to customers of the high-speed, main-line, and regional market segments, with benefits that are especially relevant for freight railways. In particular, customers of regional and freight railways are observed to be unsatisfied with current train services and willing to pay higher fares to avail of a more frequent and flexible service enabled by VC. Operational scenarios for VC are then defined by setting market-attractive service headways and by characteristics of the rolling stock, infrastructure, and traffic management. An analysis of strengths and weaknesses of such a concept together with business opportunities and threats is carried out. The defined VC future scenario is set to induce a sustainable shift of customers from other travel modes to the railways.
      Citation: Transportation Research Record
      PubDate: 2020-06-24T04:16:51Z
      DOI: 10.1177/0361198120925074
       
  • Investigating the Effect of Prestress Force on Cross-Tensioned Concrete
           Pavement Vibration
    • Authors: Hongduo Zhao, Mengyuan Zeng, Hui Chen, Jianming Ling, Difei Wu
      Abstract: Transportation Research Record, Ahead of Print.
      Prestress force loss is crucial to the structural performance of cross-tensioned concrete pavement (CTCP). Severe loss in prestress force will reduce the constricting-cracking capacity of the CTCP, resulting in damage with load and temperature applied. Vibration-based methods are commonly used in prestress force monitoring, but few relative studies are reported into CTCP and the relationship between prestress force and CTCP vibration is still unclear. The purpose of this paper is to investigate the effect of prestress force on CTCP vibration. The vibration characteristics of CTCP subjected to different prestress forces were studied through field testing and finite element (FE) analysis. Impulse load was applied as excitation at the anchorage zone and dynamic responses were measured in the time domain. A signal processing method was employed to obtain short-time power spectral from original vibration signals, which was utilized to extract vibration characteristics in time and frequency. As shown in both the field testing and the FE analysis, the prestress force has a more significant effect on frequency spectral distribution, rather than the dominant frequency. Integrated frequency is proved to be a reliable index for describing frequency spectral distribution and has a good correlation with prestress force, which suggests it can be used to reflect the change in prestress force. Overall, these findings indicate that vibration testing has potential in prestress force monitoring in CTCP, though the practicality of this method requires further demonstration.
      Citation: Transportation Research Record
      PubDate: 2020-06-23T05:40:45Z
      DOI: 10.1177/0361198120925670
       
  • Revenue Usages, Pricing Schemes, and Media Discussions for Taxing
           Ridesourcing Services
    • Authors: Jerry Zhirong Zhao, Camila Fonseca, Raihana Zeerak
      Abstract: Transportation Research Record, Ahead of Print.
      Shared mobility is transforming transportation in major urban cities. This paper focuses on taxes and fees on ridesourcing services, particularly those revenue strategies levied on their usages, generally on a per trip basis. These revenue strategies are analyzed from three main aspects. First, the usage of revenues was assessed. The majority of localities use them as a mechanism to cover regulatory costs or fill budget gaps, with very few using the proceeds to improve transportation systems or mobility overall. Second, the different pricing schemes used across localities were looked into. Most localities have adopted a fixed fee/surcharge charged per trip. Only two localities have established differential fees depending on the type of ride, aiming to increase vehicle occupancy and reduce traffic congestion. Lastly, a media analysis was conducted to examine the rationale for imposing a revenue-raising strategy, perceptions of key stakeholders, and ongoing discussions. Most debates around the adoption of the revenue-raising strategy involved the legislative and executive branches of governments at different levels, transportation network companies (TNCs), taxi businesses, and so forth. Supporters argued that the measure contributes to customer safety and the enhancement of equitable transportation options for all residents, while opponents stated concerns about the disproportionate impact of the measure on the middle-class and low-income populations. The findings provide a framework of current practices to assist state and local governments to make informed decisions in relation to TNC taxes and regulations.
      Citation: Transportation Research Record
      PubDate: 2020-06-23T04:08:34Z
      DOI: 10.1177/0361198120927403
       
  • Multiple-Case Study of U.S. General Aviation Airports for Operational
           Sustainability
    • Authors: Yue Gu, Mary E. Johnson
      Abstract: Transportation Research Record, Ahead of Print.
      Improving operational sustainability may help U.S. general aviation (GA) airports improve overall sustainable development without substantial financial inputs. An exploratory multiple-case study of five GA airports was conducted to explore the current understandings of airport operational sustainability among U.S. GA airports. Based on findings, a new definition of airport operational sustainability for U.S. GA airports was developed. A set of performance metrics for measuring operational sustainability in U.S. GA airports was identified. The new definition may help GA airports to develop sustainable management plans, and may help airports in other categories to expand their sustainability perspectives. The metrics identified in this study may be used to measure progress to the sustainable development, identify problems, and set performance goals or targets for airports.
      Citation: Transportation Research Record
      PubDate: 2020-06-23T04:08:33Z
      DOI: 10.1177/0361198120924414
       
  • Role of Timetable, Rolling Stock Rescheduling, and Information Strategies
           to Passengers in Public Transport Disruptions
    • Authors: Nuannuan Leng, Zhengwen Liao, Francesco Corman
      Abstract: Transportation Research Record, Ahead of Print.
      In the event of public transport disruption, operating companies produce disposition timetables depending on different rescheduling strategies, such as retiming or rerouting, with services fully/partially cancelled, and also taking into account more complex, adjusted, feasible rolling stock circulation. The aim is to reduce passengers’ delays, thereby limiting detriment to passengers’ activities and their related satisfaction. The key relation between the supply of operating companies and passengers’ satisfaction is information disseminated about running services. This paper innovatively combines an optimization model and an agent-based micro-simulation model (MATSim) to explore passengers’ (dis)satisfaction with different disposition timetables and information strategies, which is helpful for operating companies to offer better services to passengers in cases of public transport disruption. Activity-based agent behaviors in a multi-modal network are simulated and agents’ delays and scores for the city of Zürich, Switzerland, analyzed. Passengers’ (dis)satisfaction is indicated by their delays in the directly affected (i.e., disrupted) trip and utility for their whole trips and activities estimated by a score function. Disruption results in immediate delays for passengers whose planned services fail to run, plus delays for passengers on the line where extra services are planned to run (rerouted). The earlier information on the disposition timetable is disseminated to passengers, the higher their satisfaction during disruption. Compared with full cancellation of train services, computing a precise feasible rolling stock circulation able to handle partial train cancellations can significantly benefit passengers, especially those whose planned services are disrupted, against minor delays incurred by other group of passengers.
      Citation: Transportation Research Record
      PubDate: 2020-06-23T04:08:33Z
      DOI: 10.1177/0361198120927000
       
  • Analyzing the Application of Different Sources of Recycled Concrete
           Aggregate for Road Construction
    • Authors: Nazanin Ardalan, Douglas J. Wilson, Tam J. Larkin
      Abstract: Transportation Research Record, Ahead of Print.
      Because of the environmental, planning, and resource restrictions in the exploration and processing of natural aggregates, interest in better utilizing recycled aggregates in road pavement construction is increasing. Several researchers have investigated the characteristics of recycled concrete aggregate (RCAg) with the aim of understanding its performance as a base-course unbound material. As the pavement design techniques and the properties of re-processed RCAg in each country are non-homogeneous, previous international research on recycled aggregate cannot necessarily be incorporated in New Zealand’s pavement specifications. Moreover, RCAg is mainly sourced from vertical or horizontal concrete demolished structures. These sources of material have different engineering characteristics, and there is a lack of information about their performance. This paper investigates the difference between the properties of these two vertical and horizontal sources, and it evaluates their application as an unbound granular base-course material as opposed to an alternative layer in the pavement, for road construction in New Zealand. The physical properties of RCAgs engineering performance (durability) were evaluated through experimental laboratory-based tests. Also, the characteristics of the tested RCAgs were compared with the specification of base-course materials (NZ Transport Agency M4) in New Zealand, and their appropriateness for high-performing pavement construction layers was assessed. According to the tests results, the tested RCAgs have proven to meet the “premium” base-course grade product, and it is expected that recycled crushed concrete, if production processes are appropriately managed, could have great potential use as a base-course material in road construction and in some cases perform better than common natural aggregates.
      Citation: Transportation Research Record
      PubDate: 2020-06-23T04:08:31Z
      DOI: 10.1177/0361198120924664
       
  • Algorithm for Tracing Train Delays to Incident Causes
    • Authors: Anne Halvorsen, Darian Jefferson, Timon Stasko, Alla Reddy
      Abstract: Transportation Research Record, Ahead of Print.
      Knowledge of the root cause(s) of delays in transit networks has obvious value; it can be used to direct resources toward mitigation efforts and measure the effectiveness of those efforts. However, delays with indirect causes can be difficult to attribute, and may be assigned to broad categories that indicate “overcrowding,” incorrectly naming heavy ridership, train congestion, or both, as the cause. This paper describes a methodology to improve such incident assignments using historical train movement and incident data to determine if there is a root-cause incident responsible for the delay. It is intended as first step toward improved, data-driven delay recording to help time-strapped dispatchers investigate incident impacts. This methodology considers a train’s previous trip and when it arrived at the terminal to begin its next trip, as well as en route running times and dwell times. If the largest source of delay can be traced to a specific incident, that incident is suggested as the cause. For New York City Transit (NYCT), this methodology reassigns about 7% of trains originally without a root cause identified by dispatchers. Its results are provided to NYCT’s Rail Control Center staff via automated daily reports which, along with other improvements to delay recording procedures, has reduced these “overcrowding” categories from making up 38% of all delays in early 2018 to only 28% in 2019. The results confirm both that it is possible to improve delay cause diagnoses with algorithms and that there are delays for which both humans and algorithms find it difficult to determine a cause.
      Citation: Transportation Research Record
      PubDate: 2020-06-23T04:08:31Z
      DOI: 10.1177/0361198120926502
       
  • Enhancing Statewide Annual Average Daily Traffic Estimation with
           Ubiquitous Probe Vehicle Data
    • Authors: Xu Zhang, Mei Chen
      Abstract: Transportation Research Record, Ahead of Print.
      Annual average daily traffic (AADT) is a critical input into many transportation applications, particularly safety reporting. For example, the Highway Safety Improvement Program in the U.S. requires states to make AADT data for all public paved roadways accessible by 2026. Because collecting traffic counts on every network segment is prohibitively expensive, a method capable of accurately estimating AADT on unmonitored segments is of great value to state DOTs. The ubiquitous probe vehicle data present a great opportunity to this end. This paper presents an enhanced method for statewide AADT estimation by leveraging such data in Kentucky. The use of the probe data is explored in two ways. First, an annual average daily probes (AADP) variable is derived from hourly probe counts; second, a betweenness centrality (BC) variable is calculated using probe speeds. Including both variables and using the random forest model results in model performance that exceeds those previously reported for statewide applications. Incorporating AADP and BC improves the accuracy of AADT estimates by 30%–37% for all roads and 23%–43% for highways in functional classes 5–7, compared with only using sociodemographic and roadway characteristics. These results demonstrate the value of the probe data for enhancing AADT estimation. The analysis further shows that on roadways having more than 53 AADP or an average of 2.2 probe counts per hour, the median and the mean absolute percent errors are below 20% and 25%, respectively. These findings have practical implications for state DOTs wanting to maximize the utility of probe vehicle data.
      Citation: Transportation Research Record
      PubDate: 2020-06-22T05:27:35Z
      DOI: 10.1177/0361198120931100
       
  • Adjusting Dwell Time for Paratransit Services
    • Authors: Camille Garnier, Martin Trépanier, Catherine Morency
      Abstract: Transportation Research Record, Ahead of Print.
      Paratransit (door-to-door public transit services for people with disabilities) is a key element of the public transit system. This type of service can be very costly to operate, yet it is essential for social inclusion. The aim of this study was to develop a quantitative approach to estimate paratransit dwell times and improve trip scheduling. Dwell time is defined as the time required for a vehicle to stop to board or alight passengers. Data collected by the paratransit department of the Société de transport de Montréal (STM), the Montreal, Canada, public transit agency, between September 2014 and May 2018 was used to estimate a dwell time model. Over 5 million data points were analyzed using a multiple linear regression model. The model takes into consideration the type of vehicle used, passenger characteristics (ambulatory or wheelchair passenger, support person), the activity performed at the stop (boarding or alighting), the stop location, the time, day and month the trip took place, and the type of place (residential or non-residential) served. The results reveal all these variables have a significant impact on dwell times. Using these results, a method was developed to improve estimated dwell times in STM’s paratransit scheduling system. The new method was implemented on August 1, 2018. The difference between planned and actual travel times was measured, before and after the implementation of the new method. The results show the on-time performance of the service was improved which helped optimize routes and reduce associated operational costs.
      Citation: Transportation Research Record
      PubDate: 2020-06-22T05:26:15Z
      DOI: 10.1177/0361198120931099
       
  • Comprehensive Study of Risk Factors for Fatal Pedestrian Crashes in Urban
           Setup in a Developing Country
    • Authors: Dipanjan Mukherjee, Sudeshna Mitra
      Abstract: Transportation Research Record, Ahead of Print.
      In developing nations, pedestrian safety is a matter of major concern. The present study investigates historical crash data (2011–2016) obtained from Kolkata police, India, and identifies the key risk factors for fatal pedestrian crashes at the road network level (i.e., intersections and midblock crossings). To develop an understanding of the risk factors associated with fatal pedestrian crashes, a set of safety performance functions (SPF) are developed for both intersection and midblock level. In these SPFs, several attempts are executed to identify a host of risk factors ranging from road infrastructure to land use, traffic exposure, and operational parameters, pedestrian-level attributes, and spatial characteristics of the road network. Based on the study outcomes, there is strong evidence that approaching speed of vehicles, pedestrian-vehicular volume ratio, overtaking tendency of vehicles, inaccessibility of pedestrian crosswalk, land use type, lower post-encroachment time (PET), longer waiting time before crossing, a high share of “pedestrian is not following zebra crossing,” pedestrians’ perceived crossing difficulty, the presence of “pedestrian attraction zone” (e.g., hospital, educational institute, shopping mall, bars, etc.), and high population density significantly affect the fatal pedestrian crash frequency at the intersection level. On the other hand, over-speeding and overtaking tendency of vehicles, inadequate pavement marking, lack of visibility during night-time, lower PET, higher crossing difficulty, longer waiting time before crossing, and several spatial features such as slum population and the presence of “pedestrian attraction zone”, significantly increase the likelihood of fatal pedestrian crashes at the midblock level.
      Citation: Transportation Research Record
      PubDate: 2020-06-22T05:23:15Z
      DOI: 10.1177/0361198120925804
       
  • Development of Robotic Nondestructive Testing of Steel Corrosion of
           Prestressed Concrete Bridge Girders using Magnetic Flux Leakage System
    • Authors: Hoda Azari, Al Ghorbanpoor, Sadegh Shams
      Abstract: Transportation Research Record, Ahead of Print.
      This paper describes the development and validation of a new magnetic-based corrosion detection device integrated in a robotic system. The system nondestructively scans the length of AASHTO-type prestressed concrete I-girders of bridges. The system includes two primary subsystems: an independent magnetic flux leakage (MFL) system for nondestructive testing, and a robotic rover to transport the MFL system along the girder’s length with navigation around transverse diaphragms. The MFL unit inspects prestressing steel strands embedded in concrete and detects cross-section losses caused by corrosion. The MFL is designed with two permanent magnets to magnetize embedded strands and multiple Hall-effect sensors to detect normal and axial magnetic flux leakage. The system is evaluated by testing a laboratory mockup girder and further applied on a field girder. Resulting magnetic signals from both normal and axial Hall-effect sensors are recorded using a newly developed and integrated data acquisition system. Finite element simulations through multi-physics 3D transient analysis aided the development of the new MFL system components, including appropriate magnets strength and dimensions, as well as the verification of the developed system. The effects of lateral reinforcements on nearby section loss are obtained from tests and analyzed with numerical models. Results indicate that the system can successfully disclose magnetic leakage signals at the corrosion zone.
      Citation: Transportation Research Record
      PubDate: 2020-06-22T05:21:35Z
      DOI: 10.1177/0361198120925471
       
  • Mobility and Energy Consumption Impacts of Cooperative Adaptive Cruise
           Control Vehicle Strings on Freeway Corridors
    • Authors: Hao Liu, Xiao-Yun Lu, Steven E. Shladover
      Abstract: Transportation Research Record, Ahead of Print.
      Cooperative adaptive cruise control (CACC) vehicle string operations have the potential to improve significantly the mobility and energy consumption performance of congested freeway corridors. This study examines the impact of CACC string operations on vehicle speed and fuel economy on the 13-mi SR-99 corridor, near Sacramento, CA. It extends the existing body of knowledge by performing a multi-scenario simulation analysis of the freeway corridor. A simulation study evaluated the performance of the corridor under various CACC market penetration scenarios and traffic demand inputs. The CACC string operation was also analyzed when vehicle awareness device (VAD) and CACC managed lane (ML) strategies were implemented. The case study revealed that the average vehicle speed increased by 70% when the CACC market penetration increased from 0% to 100%. The highest average fuel economy, expressed in miles per gallon (mpg), was achieved under the 50% CACC scenario where mpg was 27. This was 10% higher than the baseline scenario. However, when the CACC market penetration was 50% or higher, the vehicle fuel efficiency only had minor increases. When CACC market penetration reached 100%, the corridor allowed 30% more traffic to enter the network without experiencing reduced average speed. Results also indicate that the VAD strategy increased the speed by 8% when the CACC market penetration was 20% or 40%, while there was a minor decrease in mpg. The ML strategy decreased the corridor performance when implemented alone.
      Citation: Transportation Research Record
      PubDate: 2020-06-21T05:20:24Z
      DOI: 10.1177/0361198120926997
       
  • Longitudinal Analysis of Light Rail and Streetcar Safety in the United
           States
    • Authors: Abubakr Ziedan, Candace Brakewood
      Abstract: Transportation Research Record, Ahead of Print.
      Many American cities have launched or expanded light rail or streetcar services recently, which has resulted in a 61% increase in light rail and streetcar revenue miles nationwide during the period 2006–2016. Moreover, light rail and streetcars exhibit higher fatality rates per passenger mile traveled compared with other transit modes. In light of these trends, this study explores light rail and streetcar collisions, injuries, and fatalities using data obtained from the National Transit Database. This study applies a two-part methodology. In the first part, descriptive statistics are calculated for light rail and streetcar collisions, injuries, and fatalities, and a comparative analysis of light rail and streetcars is performed. In the second part, multilevel negative binomial regression models are used to analyze light rail and streetcar collisions and injuries. Three key findings have emerged from this study. First, the results generally align with findings from prior studies that show the majority of light rail and streetcar collisions occur in mixed right-of-way or near at-grade crossings. Second, this analysis revealed an issue predominantly at stations: 42% of light rail injuries were people waiting or leaving. Third, suicide was the leading cause of light rail fatalities, which represents 28% of all light rail fatalities. The implications of this study are important for cities that currently operate these modes or are planning to introduce new light rail or streetcar service to improve safety.
      Citation: Transportation Research Record
      PubDate: 2020-06-21T05:20:23Z
      DOI: 10.1177/0361198120927004
       
  • Calibrating Design Guidelines using Mental Workload and Reliability
           Analysis
    • Authors: Karim Habib, Maged Gouda, Karim El-Basyouny
      Abstract: Transportation Research Record, Ahead of Print.
      The generic nature of road design is indiscriminate to age, race, or gender, as it is implicitly assumed that there are few behavioral differences between drivers while traversing various alignment elements (e.g., horizontal curves, tangential segments, etc.). For instance, the perception reaction time required, which is based on an 85th percentile value, on a tangent section is the same as that on a horizontal curve. This suggests that current guidelines do not consider the complexity that some geometric features might induce on drivers, and consequently, there is a need to address the many considerations of diversity. In this respect, human factors should be explicitly included in design guidelines. One aspect of human factors that has received little attention in the literature is related to the mental workload. In this study, a procedure is presented to estimate the mental workload for stopping sight distance. Then, reliability analysis is conducted to compare the change in the probability of non-compliance owing to the available sight distance and based on the mental workload. By analyzing data from 12 horizontal curves in Alberta, Canada, the probability of non-compliance dropped from 9.1% to 0.7%, and a moderate correlation with collisions was found. The results of the analysis showed that incorporating mental workload into the geometric design process can improve safety performance.
      Citation: Transportation Research Record
      PubDate: 2020-06-21T05:20:20Z
      DOI: 10.1177/0361198120928075
       
  • Analysis and Control of Heterogeneous Connected and Autonomous Vehicles
           using a Spring-Mass-Damper System
    • Authors: Sookyuk Bang, Soyoung Ahn
      Abstract: Transportation Research Record, Ahead of Print.
      This study analyzes the behavior of heterogeneous connected and autonomous vehicles (CAVs) and proposes the best vehicle sequence for optimal platoon throughput and platoon formation. A spring-mass-damper (SMD) system is adopted for control of CAVs, and the control parameters are formulated in relation to the physical capabilities of vehicles. To gain insight, we consider three types of vehicle: passenger cars, mini-vans, and heavy-duty vehicles. For each type, we investigate the maximum platoon throughput and the clustering time, defined as the time to reach the target equilibrium state. We further investigate different sequences of vehicle types in a platoon to identify the optimal vehicle order that maximizes the throughput and minimizes clustering time. Findings suggest that the highest performance vehicle (in relation to acceleration capability) should be placed as the leader of a platoon and that the number of passenger cars behind heavy vehicles (e.g., semi-trailers) should be minimized in the platoon. In addition, we examine how the proportions of lower performance vehicles affect throughput and clustering times. The result suggests that the higher the proportions, the lower the throughput and the longer the clustering time. The lowest performance vehicle had the greatest effect.
      Citation: Transportation Research Record
      PubDate: 2020-06-21T05:20:19Z
      DOI: 10.1177/0361198120927696
       
  • Application of Deep Learning for Characterization of Drivers’ Engagement
           in Secondary Tasks in In-Vehicle Systems
    • Authors: Osama A. Osman, Hesham Rakha
      Abstract: Transportation Research Record, Ahead of Print.
      Distracted driving (i.e., engaging in secondary tasks) is an epidemic that threatens the lives of thousands every year. Data collected from vehicular sensor technologies and through connectivity provide comprehensive information that, if used to detect driver engagement in secondary tasks, could save thousands of lives and millions of dollars. This study investigates the possibility of achieving this goal using promising deep learning tools. Specifically, two deep neural network models (a multilayer perceptron neural network model and a long short-term memory networks [LSTMN] model) were developed to identify three secondary tasks: cellphone calling, cellphone texting, and conversation with adjacent passengers. The Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS) time series data, collected using vehicle sensor technology, were used to train and test the model. The results show excellent performance for the developed models, with a slight improvement for the LSTMN model, with overall classification accuracies ranging between 95 and 96%. Specifically, the models are able to identify the different types of secondary tasks with high accuracies of 100% for calling, 96%–97% for texting, 90%–91% for conversation, and 95%–96% for the normal driving. Based on this performance, the developed models improve on the results of a previous model developed by the author to classify the same three secondary tasks, which had an accuracy of 82%. The model is promising for use in in-vehicle driving assistance technology to report engagement in unlawful tasks or alert drivers to take over control in level 1 and 2 automated vehicles.
      Citation: Transportation Research Record
      PubDate: 2020-06-21T05:20:17Z
      DOI: 10.1177/0361198120926507
       
  • Enhancing Decision-Making on Maintenance, Rehabilitation, and
           Reconstruction of Jointed Plain Concrete Pavements using Slab-Based
           Cracking Data and Life-Cycle Cost Analysis
    • Authors: Ryan Salameh, Yichang (James) Tsai
      Abstract: Transportation Research Record, Ahead of Print.
      Many jointed plain concrete pavements (JPCP) on critical roads in the United States are aged and have reached the end of their design lives. They thus require maintenance, rehabilitation, and reconstruction (MR&R) actions, which mainly involve slab replacement or lane reconstruction. Limited budgets challenge transportation agencies to determine the most cost-effective MR&R strategies, especially when life-cycle cost analysis (LCCA) is limited by the unreliable prediction of the pavement’s future needs. This paper proposes an enhanced LCCA-based methodology that utilizes slab-based cracking data collected using 3D laser technology, to select the best strategy for MR&R of JPCP by determining the timing and cost of slab replacement and lane reconstruction. By predicting pavement performance based on the current slab-based condition state using a Markov chain forecasting model, slab replacement projects are scheduled, and their feasibility is evaluated to determine the proper timing for lane reconstruction within the analysis period. LCCA is then conducted to select the alternative with the most cost-effective strategy for scheduling slab replacement and lane reconstruction projects. A case study is conducted on two 1-mi segments of I-16 in Georgia to validate the proposed methodology, followed by a sensitivity analysis to identify the input variables having a significant impact on the LCCA results. The developed framework proved its strength in determining the best MR&R strategy based on segment-level need assessment, which is utilized to perform “what if” analyses that evaluate different scenarios of project scheduling and accommodate the requirements and limitations defined by transportation agencies.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T11:32:44Z
      DOI: 10.1177/0361198120925068
       
  • Utilization Management of Highway Operations Equipment
    • Authors: Amir Mirheli, Mehrdad Tajalli, Rasool Mohebifard, Leila Hajibabai, Ali Hajbabaie
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents fleet utilization management processes for highway operations equipment based on actual tracked and reported usage data obtained from transportation agencies. The objective is to minimize total fleet utilization costs, including operational, purchase, and relocation expenses that yield the optimal utilization values and fleet composition of specific equipment types within each region in a year. The framework includes utilization prediction and optimization models, rather than relying on pre-determined utilization thresholds in existing strategies, to avoid under-utilization, over-utilization, or both. The prediction models are structured using equipment explanatory variables with their significant contributing factors, for example, annual equipment usage, annual fuel cost, downtime hours, age, and class code, to predict operational costs. The optimization model is formulated as a set of mathematical formulations, with embedded predictive models, that minimizes the total costs of (i) keeping an asset in-service using predictive annual operational cost functions, (ii) purchasing new assets in a region in the following year, and (iii) relocating assets by capturing the distance between regions. The costs include equipment purchase, operation, maintenance, and transportation expenses. The proposed framework captures the remedial actions to balance under-/over-utilized assets in the fleet in a cost-efficient manner. The proposed methodology is applied to utilization management of a set of operations equipment, and the findings of the dump trucks are presented. Several scenarios are designed to analyze the sensitivity of the costs to various decisions and parameters. The numerical experiments reveal that the proposed framework can facilitate the utilization prediction and management of highway operations equipment and save up to 16.6% in operational costs considering different demand scenarios.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T11:32:44Z
      DOI: 10.1177/0361198120927400
       
  • Estimating Light-Duty Vehicle Emission Factors using Random Forest
           Regression Model with Pavement Roughness
    • Authors: Fengxiang Qiao, Mahreen Nabi, Qing Li, Lei Yu
      Abstract: Transportation Research Record, Ahead of Print.
      Pavement roughness would affect the running of vehicle movement, and thus possibly impact fuel consumption and vehicle emissions, the numerical relationships and analytical steps of which are, however, not yet well studied. The major objective of this paper is to quantify vehicular emission factors—hydrocarbons (HC), carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2)—and fuel consumption as a function of pavement roughness (the International Roughness Index [IRI]) and other factors. Within each operating mode identification (OMID) bins of vehicle operational status, a random forest regression model (RFRM) was identified to estimate emission factors and fuel consumption. The field test data, with a total length of 1,067.41 mi driving and 323,075 data pairs from one test vehicle, were used to train and validate models. The portable emissions measurement system (PEMS) and a smartphone application for IRI were employed for the tests in Texas, U.S., roadways. Results show that the optimum roughness conditions for lower emissions and fuel consumption are in categories B and C with moderate roughness. The root-mean-square error (RMSE) during training, testing, and validation processes of the RFRM are within 6.4%, implying a good fit of resulted models. IRI has the most OMID bins as number one predictor, followed by vehicle specific power (VSP) and speed. Through separated modeling for each OMID, the impacts of IRI are successfully grasped. It is recommended conducting more field measurements with more vehicle types. This would help with possible incorporation of vehicle emissions, fuel consumption, and other environmental factors into the pavement design, maintenance, and retrofitting process.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T11:32:43Z
      DOI: 10.1177/0361198120922997
       
  • Adaptive Bike Share: Expanding Bike Share to People with Disabilities and
           Older Adults
    • Authors: John MacArthur, Nathan McNeil, Austin Cummings, Joseph Broach
      Abstract: Transportation Research Record, Ahead of Print.
      Bike share systems are expanding efforts to be more equitable and accessible to everyone by offering adaptive bicycle options to people who might otherwise be unable to ride. These systems tend to range from the inclusion of electric bikes and standard trikes into the existing systems to offering a more full range of adaptive bicycle options for use at rental location. Surveys of residents living in several low-income communities of color (n = 1,885) are used to explore the potential need for adaptive bike share options in urban locations. A national survey of cities and bike share operators (n = 70) is used to document the prevalence and basic models of adaptive bike share programming currently in place. Interviews conducted with bike share representatives in select cities with adaptive bike share programs provide context and details on how specific programs operate. Finally, interviews with adaptive bike share participants (n = 5) in Portland, Oregon, help to illuminate users’ experiences, including the perceived value and potential improvements for adaptive bike share. This opportunistic combination of data sources indicated that there is an underserved market of people who do not feel they can use existing bike share systems because of some type of physical limitation, but that reaching and serving those people presents substantial hurdles. Current bike share systems are slowly exploring the right way to include accessible options but are challenged by cost, resources, bicycle types, program implementation, and infrastructure.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T11:32:42Z
      DOI: 10.1177/0361198120925079
       
  • Defining and Analyzing Forceful Gap Behavior at Unsignalized Intersections
    • Authors: Mukti Advani, Neelam J. Gupta, S. Velmurugan, Erramppalli Madhu, Satish Chandra
      Abstract: Transportation Research Record, Ahead of Print.
      Under mixed-mode traffic conditions prevailing on Indian roads at unsignalized intersections, it is commonly observed that vehicles entering from minor streets indulge in forceful gap creation/delay for the vehicles moving on the major road. Although this driving behavior has been reported in some of the published studies for Indian traffic conditions, a clear definition of such forceful entries is not available. An attempt has been made in this study to define this forceful entry phenomenon on the basis of changes in the speed of major streets’ vehicles approaching the intersection on a typical case of mixed-traffic environs. In this regard, field observations were recorded through videography to obtain the speed reduction threshold value for categorizing an entry as a forceful entry. To quantify the above, data in relation to various vehicle types approaching intersections and their associated speeds at the reference area were extracted at the approach arms of the intersection. On the basis of observations, collected data were divided into three scenarios: () vehicles on major roads reduce their speed when vehicles are absent on minor roads; () vehicles on major roads reduce their speed when vehicles are waiting on minor roads; and () vehicles on major roads reduce their speed when vehicles from minor roads have accepted the gap/lag for movement. The changes in speed in all the three scenarios were compared to identify forceful entries with the base case of normal traffic flow on the major road without the existence of forceful entry phenomenon. The study revealed that the speed reduction to the extent of 73% is considered as a forceful entry at the selected location. Furthermore, the study estimated the effect of forceful behavior on critical gap at unsignalized intersections.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T11:32:42Z
      DOI: 10.1177/0361198120925258
       
  • Emergency Response Times for Fatal Motor Vehicle Crashes, 1975–2017
    • Authors: Maria C. Cruz, Nicholas N. Ferenchak
      Abstract: Transportation Research Record, Ahead of Print.
      Emergency response times are an important component of road safety outcomes. Research has shown that there are potential benefits from shortened response times in patient outcomes for motor vehicle crashes. While a safety analysis may identify a decrease in traffic fatalities, that decrease may be a result of improved road safety or it may simply reflect improved emergency response times. However, it is currently unclear how emergency response times have changed over the last few decades. With data from the Fatality Analysis Reporting System (FARS), we identify the national trend in emergency response times from 1975 through 2017. To control for changes in response time, we analyze crashes that resulted in an immediate death. Results suggest that emergency response times have improved by approximately 50% over this timeframe. Additionally, we analyze response time trends in three states (North Carolina, Georgia, and Louisiana) that had consistent data and large sample sizes, finding patterns similar to the national trend. Outcomes suggest higher response times in rural areas. High standard deviations of average response times observed from 2003 to 2008 indicate a need for improvement in data collection. Future work could aim to better understand and reduce response times specific to certain regions and understand the effect of the popularization of cell phone usage. Our findings have important implications for fatality-based traffic safety analyses. Improving response time could help continue the trend of reduced mortality rates caused by motor vehicle crashes in the United States.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T11:32:42Z
      DOI: 10.1177/0361198120927698
       
  • Field and Laboratory Characterization of Subgrade Resilient Modulus for
           Pavement Mechanistic-Empirical Pavement Design Guide Application
    • Authors: Kazi Moinul Islam, Sarah Gassman, Md Mostaqur Rahman
      Abstract: Transportation Research Record, Ahead of Print.
      The resilient modulus (MR) of subgrade material is an important parameter in pavement design using the Mechanistic-Empirical Pavement Design Guide (MEPDG) and has a significant influence on pavement performance. MR can be obtained indirectly from falling weight deflectometer (FWD) data using a back-calculation tool (i.e., AASHTOWare 2017) or from empirical correlations with soil index properties. MR can also be obtained directly using repeated load triaxial tests (AASHTO T 307-99, 2017). In this study, the field test program included FWD tests and soil sampling. These field tests were performed on six asphalt pavement sections in South Carolina, U.S., to estimate the MR of the subgrade soil. This study involved extensive laboratory characterization of subgrade soils collected from underneath the pavement sections. Laboratory characterization included index tests (sieve analysis, Atterberg limits, specific gravity, moisture content, and standard Proctor density tests) on bulk samples and repeated load triaxial tests on thin-walled tube samples to obtain a direct measure of MR. Results show that the MR values found from the FWD data have similar trends to the laboratory-measured MR values. However, results from lab testing were 33%–75% lower than the back-calculated MR. Laboratory-measured MR, and back-calculated MR were used to determine a C-factor of 0.33, 0.25, and 0.29 for coarse-grained, fine-grained, and all types of soils, respectively. This parameter can be used to estimate resilient modulus for MEPDG Level 2 design inputs across South Carolina and similar geologic regions. The research studies will be facilitated by the local calibration and implementation of the MEPDG.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T09:54:02Z
      DOI: 10.1177/0361198120926171
       
  • Automated Safety Diagnosis Based on Unmanned Aerial Vehicle Video and Deep
           Learning Algorithm
    • Authors: Yina Wu, Mohamed Abdel-Aty, Ou Zheng, Qing Cai, Shile Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents an automated traffic safety diagnostics solution named “Automated Roadway Conflict Identification System” (ARCIS) that uses deep learning techniques to process traffic videos collected by unmanned aerial vehicle (UAV). Mask region convolutional neural network (R-CNN) is employed to improve detection of vehicles in UAV videos. The detected vehicles are tracked by a channel and spatial reliability tracking algorithm, and vehicle trajectories are generated based on the tracking algorithm. Missing vehicles can be identified and tracked by identifying stationary vehicles and comparing intersect of union (IOU) between the detection results and the tracking results. Rotated bounding rectangles based on the pixel-to-pixel manner masks that are generated by mask R-CNN detection are introduced to obtain precise vehicle size and location data. Based on the vehicle trajectories, post-encroachment time (PET) is calculated for each conflict event at the pixel level. By comparing the PET values and the threshold, conflicts with the corresponding pixels in which the conflicts happened can be reported. Various conflict types: rear-end, head on, sideswipe, and angle, can also be determined. A case study at a typical signalized intersection is presented; the results indicate that the proposed framework could significantly improve the accuracy of the output data. Moreover, safety diagnostics for the studied intersection are conducted by calculating the PET values for each conflict event. It is expected that the proposed detection and tracking method with UAVs could help diagnose road safety problems efficiently and appropriate countermeasures could then be proposed.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T09:52:55Z
      DOI: 10.1177/0361198120925808
       
  • Identifying Pedestrian Crash Contributing Factors using Association
           Analysis and Their Implications for Development of Active Pedestrian
           Safety System
    • Authors: Lishengsa Yue, Mohamed Abdel-Aty, Yina Wu, Samiul Hasan, Ou Zheng
      Abstract: Transportation Research Record, Ahead of Print.
      An active pedestrian safety system (APSS) would be more effective by considering the implications of crash contributing factors. In addition, the APSS needs to be tested and evaluated in the field; therefore, a comprehensive scenario library is necessary. In this study, 135 pedestrian crash reports were investigated. The driving reliability and error analysis method was first applied to identify the contributing factors that can be potentially solved by the APSS function; then, the association rules method was adopted to analyze the joint effect of contributing factors and roadway facility features on injury/fatal pedestrian crashes. The results showed that “inattention,”“failure intention prediction,”“reduced visibility,” and “temporary/permanent obstruction of view” were the first four most frequent contributing factors. Moreover, injury/fatal pedestrian crashes resulting from “failure intention prediction” and “temporary/permanent obstruction of view” were more likely to occur at a location with more than three lanes, a curb shoulder, and a posted speed limit of 40–45 mph. Further, based on the crash contributing factors, the APSS’s functional design is suggested to provide conflict-time-based warning information, pedestrian movement prediction, and detection and tracking of moving objects behind the obstruction. The APSS’s sensing ability is required to detect the vehicle’s nearby area and to be adaptive to poor lighting conditions. Finally, a scenario library was proposed for field testing/evaluation of the APSS. The scenario library has 10 sub-scenarios with detailed object configurations as well as required testing/evaluation items for the APSS. This study’s findings would be helpful for automobile manufacturers to improve the APSS.
      Citation: Transportation Research Record
      PubDate: 2020-06-19T09:52:37Z
      DOI: 10.1177/0361198120925472
       
  • Integration of Departure Time Choice Modeling and Dynamic
           Origin–Destination Demand Estimation in a Large-Scale Network
    • Authors: Sajjad Shafiei, Meead Saberi, Hai L. Vu
      Abstract: Transportation Research Record, Ahead of Print.
      Time-dependent origin–destination (OD) demand estimation using link traffic data in a large-scale network is a highly underdetermined problem. As a result, providing an accurate initial solution is crucial for obtaining a more reliable estimated demand. In this paper, we discuss the necessity of having a comprehensive demand profiling model that considers the spatial differences of OD pairs and we demonstrate its application in the calibration of large-scale traffic assignment models. First, we apply a departure choice model that adds a time dimension to the OD demand flows concerning their spatial differences. The time-profiled demand is then fed into the time-dependent OD demand estimation problem for further adjustment. Results show that in addition to reducing the error between simulation outputs and the observed link counts, the estimated demand profile more accurately reflects the spatial correlation of the OD pairs in the large-scale network being studied. Results provide practical insights into deployment and calibration of simulation-based dynamic traffic assignment models.
      Citation: Transportation Research Record
      PubDate: 2020-06-18T08:42:52Z
      DOI: 10.1177/0361198120933267
       
  • Investigation of Highway Stormwater Management Pond Capacity for Flood
           Detention and Water Quality Treatment Retention via Remote Sensing Data
           and Conventional Topographic Survey
    • Authors: Houng Li
      Abstract: Transportation Research Record, Ahead of Print.
      Stormwater management ponds are common best management practice (BMP) and green infrastructure (GI) for flood attenuation and water quality treatment in highway projects. Originally designed to provide storage volume for flood detention, stormwater ponds today often employ additional retention volume at pond bottom in a hope to improve water quality via sedimentation and other pollutant-removal mechanisms. It is commonly assumed that sediment accumulation and topographic variations (such as erosion, channelization, and in-pond plant growth and decay) over time often decrease the capacity of stormwater ponds. However, differences between design capacities and field capacities over time have never been verified and quantitatively analyzed before. This study presents such analysis using conventional topographic survey techniques and remote sensing data (topographic light detection and ranging digital elevation model [LIDAR DEM]) for 10 highway stormwater ponds along Interstate Highway-95 (I-95) systems in Baltimore City, Cecil County, and Harford County, Maryland, United States, with facility service life ranging from 14 to 26 years (1990–2015). Data derived from LIDAR DEM were compared with those from topographic survey; the LIDAR DEM data appear to be effective in measuring flood detention capacities and identifying silted ponds, but not in estimating the remaining retention volume for water quality treatment. Data from topographic survey indicate that the total volume in the ponds was relatively unchanged compared with the design, with increases in some instances. The increase typically occurred at the pond’s upper stages. Nonetheless, the water quality treatment capacity at pond bottom (wet pool volume) was drastically less (up to 100% of the design). As current maintenance practice of stormwater ponds relies heavily on visual inspection, the storage volume variations are often overlooked. As such, the findings prompt uncertainty on the long-term effectiveness of watershed implementation plan and models in the Chesapeake Bay watersheds, as many of them depend on wet pool volume design in BMP and GI.
      Citation: Transportation Research Record
      PubDate: 2020-06-18T08:41:43Z
      DOI: 10.1177/0361198120923658
       
  • Seismic Isolation Retrofitting of Typical Multi-Span Steel Girder Bridges
           in New York State
    • Authors: Dongming Feng, Fangyin Zhang
      Abstract: Transportation Research Record, Ahead of Print.
      Many of the existing multi-span simply supported bridges in New York State, U.S., are susceptible to earthquake damage and need to be retrofitted to reduce their seismic risk. In this study, seismic retrofit of a five-span simply supported bridge with typical high-type fixed and expansion steel rocker bearings is conducted. A refined three-dimensional (3D) finite element model of the bridge is developed in ANSYS by considering foundation impedances. Multi-support time history analyses have been implemented in the seismic retrofit design for two levels of ground motions: 1,000- and 2,500-year return period earthquakes. The site-specific ground motions with consideration of the spatial variation are generated based on the geotechnical information. Seismic retrofit by replacing existing steel bearings with lead-rubber bearing (LRB) isolators has been adopted. The parameters of the isolators are determined by considering factors such as the seismic performance and translational resistance during normal service. The vulnerability of structural members and seismic retrofit effectiveness are quantified by the demand-to-capacity (D/C) ratio for the combined demands at the extreme limit state. The analyses show that after seismic isolation retrofit the pervasive vulnerabilities in pier columns and cap beams are eliminated. Comparing with strengthening the vunerable structural members, seismic isolation is proved a cost-effective retrofit solution. The overall seismic isolation design and analysis procedures presented in this study can help guide future seismic retrofit of similar types of bridges.
      Citation: Transportation Research Record
      PubDate: 2020-06-18T06:25:13Z
      DOI: 10.1177/0361198120924665
       
  • How Much of Which Mode': Using Revealed Preference Data to Design
           Mobility As a Service Plans
    • Authors: Daniel J. Reck, Kay W. Axhausen
      Abstract: Transportation Research Record, Ahead of Print.
      Mobility as a service (MaaS) seeks to integrate emerging shared mobility modes with existing public transportation (PT). Decisive to its uptake will be attractive subscription plans that cater for heterogeneous mobility needs. Research on willingness to pay for such plans has commenced, yet remains divided on a central question: how much to include of which mode, and how' Complementing previous research building on stated preference data, in this study revealed preference data is used to analyze the viability of different subscription plan components (PT, car-sharing, bike-sharing, taxi), modes of inclusion (budgets in minutes and season tickets) and subscription cycles (weekly, monthly). PT season tickets are found to be viable for 83% of all respondents. Interestingly, the viability of minute budgets of car- and bike-sharing depends on subscription cycle length. Using a monthly subscription cycle, car-/bike-sharing appears viable to include in a bundle for 35%/31% of all respondents, respectively. Using a weekly subscription cycle, these figures drop to 1.4%/0.4%, respectively, as weekly variation in demand is much higher than monthly variation. In contrast to many current MaaS pilots, taxi use remains too infrequent to include as recurring credit in MaaS plans. Rather, pay-as-you-go is the economically more sensible option for consumers. This research therefore challenges the idea of all-inclusive mobility flat rates and suggests a more modular design.
      Citation: Transportation Research Record
      PubDate: 2020-06-17T10:53:57Z
      DOI: 10.1177/0361198120923667
       
  • Personalized Choice Model for Managed Lane Travel Behavior
    • Authors: Yifei Xie, Yundi Zhang, Arun Prakash Akkinepally, Moshe Ben-Akiva
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a methodology for enhancing discrete choice models for managed lane travel behavior with personal trip history. We refer to this process as personalization and the enhanced model as a personalized choice model. With the objective of better understanding managed lane choices and improving the model’s prediction capability, personalization was carried out at two levels. First, we used each traveler’s habits and travel experiences before each trip for constructing a set of explanatory variables that could be used with any model structure. Second, under a logit mixture framework, the distribution of random parameters was updated with Bayesian inference according to personal trip history. The structure of the parameter distribution explicitly considered preference variations across individuals (interpersonal heterogeneity), as well as preference variations across trips performed by the same individual (intrapersonal heterogeneity). The proposed methodology is especially relevant for modeling revealed preference (RP) data from automatic vehicle identification sensors, for which limited socioeconomic characteristics of travelers are available. An empirical study was conducted on an operational managed lane corridor near Dallas/Fort Worth Airport in Texas. Available trip records over a 5-month period were utilized. A hierarchical Bayes estimator was adopted for efficient model estimation. The results suggest significant inter- and intrapersonal heterogeneity and that the proposed personalization method improves the model’s explanatory power and prediction capability. To the best of our knowledge, this paper represents the first introduction of personalization in managed lane choice behavior modeling and the first attempt to estimate intrapersonal heterogeneity with RP data.
      Citation: Transportation Research Record
      PubDate: 2020-06-17T10:53:55Z
      DOI: 10.1177/0361198120923355
       
  • Evaluation of the Precision and Accuracy of Cycle-Average Light Duty
           Gasoline Vehicles Tailpipe Emission Rates Predicted by Modal Models
    • Authors: Tongchuan Wei, H. Christopher Frey
      Abstract: Transportation Research Record, Ahead of Print.
      A vehicle specific power (VSP) modal model and the MOtor Vehicle Emission Simulator (MOVES) Operating Mode (OpMode) model have been used to evaluate and quantify the fuel use and emission rates (FUERs) for on-road vehicles. These models bin second-by-second FUERs based on factors such as VSP, speed, and others. The validity of binning approaches depends on their precision and accuracy in predicting variability in cycle-average emission rates (CAERs). The objective is to quantify the precision and accuracy of the two modeling methods. Since 2008, North Carolina State University has used portable emission measurement systems to measure tailpipe emission rates for 214 light duty gasoline vehicles on 1,677 driving cycles, including 839 outbound cycles and 838 inbound cycles on the same routes. These vehicles represent a wide range of characteristics and emission standards. For each vehicle, the models were calibrated based on outbound cycles and were validated based on inbound cycles. The goodness-of-fit of the calibrated models was assessed using linear least squares regression without intercept between model-predicted versus empirical CAERs for individual vehicles. Based on model calibration and validation, the coefficients of determination (R2) typically range from 0.60 to 0.97 depending on the vehicle group and pollutant, indicating moderate to high precision, with precision typically higher for higher-emitting vehicle groups. The slopes of parity plots for each vehicle group and all vehicles typically range from 0.90 to 1.10, indicating good accuracy. The two modeling approaches are similar to each other at the microscopic and macroscopic levels.
      Citation: Transportation Research Record
      PubDate: 2020-06-17T10:53:54Z
      DOI: 10.1177/0361198120924006
       
  • Long-Term Stability of High-Speed Railway Geosynthetic Reinforced
           Pile-Supported Embankment Subjected to Traffic Loading Considering Arching
           Effect
    • Authors: Zongqi Bi, Quanmei Gong, Jiandan Huang
      Abstract: Transportation Research Record, Ahead of Print.
      Geosynthetic reinforced pile-supported (GRPS) embankment is widely used in the construction of high-speed railways on soft foundations. Arching effect, which is a common phenomenon in the system involving soil-structure interaction, is considered a key factor in the design of GRPS embankment. Its performance has been found inevitably to affect the post-construction settlement and bearing capacity of the embankment. However, the existing design methods are mainly based on static loading condition; soil arching effect under high-cycle loading has not been fully understood. In this study, a series of numerical simulations were conducted to study the long-term behavior of GRPS embankment under traffic loading, with the consideration of arching effect in soil. An implicit–explicit transition calculation algorithm was implemented to predict the permanent deformation under high-cycle traffic loading through the data transfer and conversion between implicit and explicit numerical stages, in which the mixed “implicit” and “explicit” calculation strategy were carried out based on the high-cycle accumulation (HCA) model. By using the proposed algorithm, a cross-section of high-speed railway GRPS embankment was selected as a case for discussion. Results indicate that the affected areas of stress concentration over piles in the embankment are reduced under traffic loading. With different levels of stability, the variation of stress concentration ratio of the arching effect can be mainly classified into three groups: stable, gradually weakened, and destroyed. Through parameter study, the effect of subsoil stiffness is discussed and a reasonable modulus ratio between pile and subsoil is suggested for the design reference.
      Citation: Transportation Research Record
      PubDate: 2020-06-17T10:53:53Z
      DOI: 10.1177/0361198120924008
       
  • Effect of Tactile Walking Surface Indicators on Travelers with Mobility
           Disabilities
    • Authors: Billie Louise (Beezy) Bentzen, Alan C. Scott, Robert Wall Emerson, Janet M. Barlow
      Abstract: Transportation Research Record, Ahead of Print.
      Guidance tactile walking surface indicators (TWSIs), typically a surface of raised bars, are used internationally to provide location and directional information at crosswalks to pedestrians who are blind. The bars are installed across the sidewalk, with the bars perpendicular to the travel path on the sidewalk and parallel to the direction of travel on the crosswalk. In the U.S., there has been little or no use of such surfaces at crosswalks because of concerns about the effect of these bars on individuals with mobility disabilities. However, difficulties of blind pedestrians in locating crosswalks and aligning to cross have been documented, and the installation of surfaces with bars parallel to the direction of travel on the sidewalk has been shown to be a possible solution. This research investigated the effects of crossings of TWSIs installed perpendicular versus parallel to the direction of travel on the sidewalk on 38 participants with mobility disabilities who used a variety of mobility aids. Crossing either orientation of bars caused some increase in effort and instability for more than half of participants. Effort was somewhat greater on average for all participants when crossing bars perpendicular to their travel. Stability for wheelchair users was poorer, on average, when the bars were oriented perpendicular to their travel. There was low incidence of any slipping of feet or mobility aids, and low incidence of trapping of wheels or cane/crutch/walker tips. A significant majority of participants expressed their preference for crossing bars oriented parallel to their travel.
      Citation: Transportation Research Record
      PubDate: 2020-06-17T05:50:41Z
      DOI: 10.1177/0361198120922995
       
  • Induced Vehicle Travel in the Environmental Review Process
    • Authors: Jamey M. B. Volker, Amy E. Lee, Susan Handy
      Abstract: Transportation Research Record, Ahead of Print.
      If we expand roadway capacity, more drivers will come, or so economic theory suggests and a substantial body of empirical research now shows. Despite strong evidence, the “induced travel” effect is often ignored, underestimated, or misestimated in the planning process, particularly in the assessment of the environmental impacts of roadway capacity expansions. Underestimating induced travel will generally lead to overestimation of the traffic congestion relief benefits a highway expansion project might generate, along with underestimation of its environmental impacts. A major reason that induced travel tends to be underplayed in environmental analyses is that travel demand models do not typically include all of the feedback loops necessary to accurately predict the induced travel effect. We developed an online tool, based on elasticities reported in the literature, to facilitate the estimation of the induced vehicle travel impacts of roadway capacity expansion projects in California, with potential future expansion to other geographies. We describe the tool, apply it to five case study highway capacity expansion projects, and then compare the results with the induced travel estimates reported in the environmental impact analyses for those projects. Our results suggest that environmental analyses frequently fail to fully capture the induced vehicle travel effects of highway capacity expansion projects.
      Citation: Transportation Research Record
      PubDate: 2020-06-16T01:56:59Z
      DOI: 10.1177/0361198120923365
       
  • Investigation on Identifying Road Anomalies using In-Vehicle Sensors for
           Cooperative Applications and Road Asset Management
    • Authors: Moksheeth Padarthy, Mohammed Sami, Emiliano Heyns
      Abstract: Transportation Research Record, Ahead of Print.
      One of the main challenges for road authorities is to maintain the quality of the road infrastructure. Road anomalies can have a significant impact on traffic flow, the condition of vehicles, and the comfort of occupants of vehicles. Strategies such as pavement management systems use pavement evaluation vehicles that are equipped with state-of-the-art devices to assist road authorities in identifying and repairing these anomalies. The quantity of data available is limited, however, by the limited availability and, therefore, coverage of these vehicles. To address this problem, several investigations have been conducted on the use of smartphones or equipping vehicles with additional sensors to identify the presence of road anomalies. This paper aims to add to this arsenal by using sensors already available in production vehicles to identify road anomalies. If production vehicles could be used to identify road anomalies, then road authorities would be equipped with an additional fleet of mobile sensors (vehicles traveling on a particular road) to receive initial insights into the presence of anomalies. This information could then be used to assist road authorities to deploy their staff and equipment more precisely at these locations, such that appropriate equipment reaches the right place at the right time. In this paper, an algorithm that uses lateral acceleration and individual wheel speed signals, which are commonly available vehicular variables, was developed to detect potholes using machine learning techniques. The results of the algorithm were validated with real life test scenarios.
      Citation: Transportation Research Record
      PubDate: 2020-06-16T01:56:58Z
      DOI: 10.1177/0361198120923989
       
  • Evolution of Transportation Network Companies and Taxis through
           2013–2018 in Chicago
    • Authors: Sneha Roy, Anurag Komanduri, Kimon Proussaloglou
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this paper is to highlight important differences between taxis and transportation network companies (TNCs) in a large urban area. We analyze the publicly available dataset from Chicago which includes taxi and transportation network company (TNC) utilization and the level of service measures from five months in 2013–2014 and the same five months in 2018–2019. We compare and contrast the data from these two points in time to document utilization of taxis and TNCs and to measure differences in travel times, travel distances, fares, destinations served, and the spatial and temporal distribution of these trips. Travel to and from airports has been evaluated separately owing to the exceptionally high number of trips they generate. Striking differences between pooled and unpooled TNC trip volumes and other travel metrics have been assessed to highlight their operational diversity despite being considered as the same mode. The exploratory analysis has been carried out across the shared-ride, time, and mode dimensions. The study revealed both similarities and differences in taxi trip characteristics between the two evaluation periods and also outlined how the ridehailing market has grown over the years despite the near stagnation in population and employment in the city. We believe that assessing how taxis have fared through this time and highlighting the intrinsic differences between how the old and new mode of on-demand ride services coexist is important. This study aims to help understand how new-age mobility services are impacting transportation in one of the largest cities in the U.S.
      Citation: Transportation Research Record
      PubDate: 2020-06-16T01:56:55Z
      DOI: 10.1177/0361198120922851
       
  • Analyzing Characteristics of the Unreliable Segments of the National
           Highway System across South Eastern States of the United States
    • Authors: Chowdhury Siddiqui
      Abstract: Transportation Research Record, Ahead of Print.
      The latest transportation law in the United States continues to put emphasis on a performance management approach similar to the previous one. Since the transportation performance management rules were made in 2017, limited work has been done to understand the travel time reliability on the national highway system (NHS) and the factors influencing it. This study contributes to the literature by analyzing the characteristics of the unreliable segments of the NHS in 13 south eastern states. It was observed that there was a higher percentage of unreliable segments in the non-Interstate NHS (about 34%) than in the Interstate system (about 13% of segments were unreliable). Analyses of the unreliability of the Interstate and non-Interstate NHS were conducted separately to understand each of them better. To capture the influence of the attributes on the reliability of the NHS segments, multivariate binary logistic models were developed. The results from the models suggest that the reference traffic message channels (TMCs), which were characterized by being in urban areas with shorter length (≤0.25 mi) and ≤10% trucks in the traffic stream, generally have a higher chance of being unreliable than those that are not in the reference category. Interstate TMCs on bridges, tunnels, or causeways, and those with directional traffic volume greater than 30,000, have higher chances of being unreliable than the reference category. The chances of internal TMCs (between decision points) in the non-Interstate NHS being unreliable were about 14% higher than the mean chance of the reference TMCs.
      Citation: Transportation Research Record
      PubDate: 2020-06-16T01:56:55Z
      DOI: 10.1177/0361198120923369
       
  • Macroscopic Fundamental Diagram Approach to Evaluating the Performance of
           Regional Traffic Controls
    • Authors: Weike Lu, Jun Liu, Jiannan Mao, Guojing Hu, Chuqiao Gao, Lan Liu
      Abstract: Transportation Research Record, Ahead of Print.
      Evaluating a regional traffic control system requires understanding both the advantages and disadvantages of control schemes as well as the interrelated characteristics of the system. To assess the efficiency of regional signal control schemes in a road network, this study, which is based on the macroscopic fundamental diagram (MFD) concept, proposes four evaluative indicators: maximum throughput, critical accumulation, gridlock accumulation and the degree of homogeneity. The maximum throughput and gridlock accumulation can be used to reflect the road network capacity and load capacity, respectively. The degree of homogeneity quantifies the spatial variations of traffic flows in the network. Combined with the gridlock accumulation, the critical accumulation values the durability of a regional control system in managing congestion in the network. This study used the regional road network in Qingyang District of Chengdu, China, as a real-world example to demonstrate the proposed MFD-based approach. In the demonstration, the MFD-based evaluation method was compared to the traditional travel time-based method. The demonstration evaluated the control effect and characteristic values of the network under four control modes: fixed-time, actuated, adaptive and adaptive coordinated control.
      Citation: Transportation Research Record
      PubDate: 2020-06-16T01:56:53Z
      DOI: 10.1177/0361198120923359
       
  • Comprehensive Evaluation of Rutting of Warm-Mix Asphalt Utilizing
           Long-Term Pavement Performance Specific Pavement Studies
    • Authors: Biswajit K. Bairgi, A.S.M. Asifur Rahman, Rafiqul A. Tarefder, Matias M. Mendez Larrain
      Abstract: Transportation Research Record, Ahead of Print.
      Warm-mix asphalt (WMA) technologies allow binder softening for compaction benefits. Lower production temperature also causes reduced short-term aging in WMA. Considering the long-term implication of the reduced aging and binder softening, WMA is being questioned about its rutting characteristics. As such, this study evaluates different WMA technologies for rutting characteristics in comparison to traditional hot-mix asphalt (HMA) through laboratory and field investigation. The study utilized the long-term pavement performance (LTPP) project in the state of New Mexico called Specific Pavement Study-10 (SPS-10), which was designed to evaluate the WMA performances. The LTPP SPS-10 section includes: (i) control HMA, (ii) foaming, (iii) Evotherm, (iv) Cecabase 1, and (v) Cecabase 2 mixtures. Cecabase 2 mixture consists of a polymer-modified binder (PG 70-28+), whereas other mixtures consist of PG 70-28 binder. The aggregate type, properties, and gradations are the same in all the sections. Laboratory evaluation of rutting was conducted through the Hamburg wheel tracking test. Long-term field rutting was evaluated through Mandli’s pavement profile scanner, a laser-based distress evaluation technology. The study found that WMA with foaming, Evotherm, or Cecabase shows slightly higher rutting compared with the control HMA; however, all the sections satisfied laboratory and field rutting criteria. The use of a polymer-modified binder in WMA significantly improves the rutting characteristics.
      Citation: Transportation Research Record
      PubDate: 2020-06-16T01:56:51Z
      DOI: 10.1177/0361198120921852
       
  • Conceptualization of Three-Stage Fatigue Failure in Asphalt-Rubber
           Gap-Graded Mixtures using Dynamic Semi-Circular Bending Test
    • Authors: Veena Venudharan, Krishna Prapoorna Biligiri
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this study was to qualitatively measure the cracking mechanism of asphalt-rubber gap-graded (AR-Gap) mixtures and compare the methodical approach proposed in this research with the conventional fatigue process. As part of experimentation plan, dynamic a semi-circular bending (SCB) test was conducted on 27 AR-Gap mixtures with varying mix parameters, including, binder type, binder content, and aggregate gradation. Fatigue life (Nf) obtained from the dynamic SCB test was analyzed from a statistical viewpoint, and key relationships that potentially contribute to fatigue performance were identified. Later, crack mouth opening displacement (CMOD) was used to study the cracking mechanism of AR-Gap mixtures. CMOD data were analyzed using the Francken model that theorizes the accumulated damage as a three-stage failure. Further, fatigue tertiary life (Nft) was determined on the premise of structural deterioration obtained from the three-stage failure process. The fatigue disparity factor (ξ), the ratio of Nf to Nft for each asphalt mix was estimated to compare fatigue performance indices. The score of ξ for all the mixtures exceeded 50%, which was indicative of longer crack initiation and crack propagation phase over the third stage of the fatigue cracking mechanism. Overall, the fatigue mechanism was explained through the conceptualization of the three-stage fatigue process through various intrinsic properties of AR-Gap mixtures.
      Citation: Transportation Research Record
      PubDate: 2020-06-16T01:27:32Z
      DOI: 10.1177/0361198120920872
       
  • Modeling Lane-Changing Behaviors in Merging Areas of Urban Expressways in
           Nanjing, China
    • Authors: Quan Chen, Hao Wang, Changyin Dong
      Abstract: Transportation Research Record, Ahead of Print.
      Merging bottlenecks in urban expressways have attracted much attention in recent years. In this paper, vehicular mandatory lane-changing (MLC) data are collected from Yingtian Avenue in Nanjing, China using cameras. Based on a series of video processing algorithms, 656 MLC behaviors of 1,560 vehicles are extracted from videos. A logistic regression model is proposed to depict MLC at the merging bottleneck and estimate the possibility of accepting gaps for merging, which is validated by precision testing and simulation. During the simulation, a discretionary lane-changing (DLC) model is utilized and calibrated to describe vehicular DLC behaviors for the sake of consistency and completeness. Finally, by simulating different arrival rates of mainline and ramp, a linear regression model is built to predict breakdown at merging bottlenecks. According to data analysis, the MLC model represents high precision during the decision-making process. Besides, the breakdown prediction model implies strong correlation between traffic demand and breakdown occurrence.
      Citation: Transportation Research Record
      PubDate: 2020-06-14T06:55:17Z
      DOI: 10.1177/0361198120923361
       
  • Multiple Regression Model for Load Rating of Reinforced Concrete Bridges
    • Authors: Edgardo Ruiz, Seamus Freyne
      Abstract: Transportation Research Record, Ahead of Print.
      This paper describes the development of a multiple regression model to estimate the load rating of reinforced concrete bridges. There are over 250,000 reinforced concrete bridges in the U.S. many of which do not have a load rating on record nor the plans required to perform the calculations. The U.S. Army owns and maintains hundreds of these bridges throughout the U.S. An exploratory data analysis of the 2017 National Bridge Inventory (NBI) data was performed for the selection of a representative data sample. The data required significant processing to extract a reliable sample for modeling. After processing, a data sample of 31,112 bridges remained, which provided a sufficient sample for model training and validation. A six-variable linear model that relates inventory rating to span length, deck width, year built, region, design load, and superstructure condition was determined to provide the best performance while maintaining a desired low level of complexity. The model had an adjusted R2 of 0.514 and a standard error of 6.51 metric tons (7.17 tons). The model was validated against unseen data by comparing the percentage of cases that fell within its 95% prediction interval, which resulted in 94.9% of the real values falling within the prediction interval.
      Citation: Transportation Research Record
      PubDate: 2020-06-14T06:55:16Z
      DOI: 10.1177/0361198120922546
       
  • Replicating Advanced Detection using Low Ping Frequency Probe Vehicle
           Trajectory Data to Optimize Signal Progression
    • Authors: Jonathan M. Waddell, Stephen M. Remias, Jenna N. Kirsch, Mohsen Kamyab
      Abstract: Transportation Research Record, Ahead of Print.
      Probe vehicle trajectory data has the potential to transform the current practice of traffic signal optimization. Current scalable trajectory data is limited in both the penetration rate and the ping frequency, or the length of time between vehicle waypoints. This paper introduces a methodology to create binary vehicle trajectories which can be used in a neural network to predict when vehicles will arrive at a virtual detector. The methodology allows for vehicles with ping frequencies of up to 60 s to be utilized for the optimization of offsets at signalized intersections. A nine-signal corridor in west Michigan was used to test the proposed methodology. The neural network was compared to traditional linear interpolation strategies and found to improve the root mean squared error of the arrival times by up to 6.18 s. Using the virtual detector data stacked over time to optimize the offsets of the corridor resulted in 77% of the benefit of an offset optimization performed with continuously collected high resolution signal controller data. In the era of big data, this alternative approach can assist with the large-scale implementation of traffic signal performance measures for improved operations.
      Citation: Transportation Research Record
      PubDate: 2020-06-14T06:55:14Z
      DOI: 10.1177/0361198120923654
       
  • Incorporating Autonomous Vehicles in the Traditional Four-Step Model
    • Authors: Felipe F. Dias, Gopindra S. Nair, Natalia Ruíz-Juri, Chandra R. Bhat, Arash Mirzaei
      Abstract: Transportation Research Record, Ahead of Print.
      Automated vehicles (AVs) are a concrete possibility in the near future. As AVs may shift transportation paradigms, transportation agencies are eager to update their models to consider them in planning. In this context, the use of advanced models may be challenging, given the uncertainty in the use and deployment of AVs. In this paper, we present a general framework to extend the four-step model to include AVs, and test our extension on North Central Texas Council of Governments’ model. Our approach introduces a module for AV ownership and exogenous parameters into an existing four-step model to account for changes in travel decisions for AV owners, and for the impacts of AVs on network performance. The latter is modeled using the concept of passenger-car-equivalent to avoid imposing network-wide assumptions on AVs’ capacity consumption. We analyze five scenarios, representing different assumptions on the impacts of AVs, and include references to inform the selection of modeling parameters. We compute aggregate metrics that suggest that the model is sensitive to the proposed parameters, with the passenger-car-equivalent assumptions having the largest impact on model outcomes. Results suggest that, even when we assume that AVs can better use network capacity and that trip-making rates do not drastically increase, AVs may lead to an increase of about 2.8% in vehicle-hours traveled while also improving speeds by about 1.8%. If AVs introduce additional friction on traffic, the system performance may deteriorate. The analyses presented here suggest that existing modeling tools may be adjusted to support analyses of a future with AVs.
      Citation: Transportation Research Record
      PubDate: 2020-06-14T06:55:12Z
      DOI: 10.1177/0361198120922544
       
  • Prediction of Lane-Changing Maneuvers with Automatic Labeling and Deep
           Learning
    • Authors: Vishal Mahajan, Christos Katrakazas, Constantinos Antoniou
      Abstract: Transportation Research Record, Ahead of Print.
      Highway safety has attracted significant research interest in recent years, especially as innovative technologies such as connected and autonomous vehicles (CAVs) are fast becoming a reality. Identification and prediction of driving intention are fundamental for avoiding collisions as it can provide useful information to drivers and vehicles in their vicinity. However, the state-of-the-art in maneuver prediction requires the utilization of large labeled datasets, which demand a significant amount of processing and might hinder real-time applications. In this paper, an end-to-end machine learning model for predicting lane-change maneuvers from unlabeled data using a limited number of features is developed and presented. The model is built on a novel comprehensive dataset (i.e., highD) obtained from German highways with camera-equipped drones. Density-based clustering is used to identify lane-changing and lane-keeping maneuvers and a support vector machine (SVM) model is then trained to learn the boundaries of the clustered labels and automatically label the new raw data. The labeled data are then input to a long short-term memory (LSTM) model which is used to predict maneuver class. The classification results show that lane changes can efficiently be predicted in real-time, with an average detection time of at least 3 s with a small percentage of false alarms. The utilization of unlabeled data and vehicle characteristics as features increases the prospects of transferability of the approach and its practical application for highway safety.
      Citation: Transportation Research Record
      PubDate: 2020-06-13T05:09:01Z
      DOI: 10.1177/0361198120922210
       
  • Estimate of the Safety Effect of All-Way Stop Control Conversion in
           Washington, DC
    • Authors: Zuxuan Deng, Sergiy Kyrychenko, Taylor Lee, Richard Retting
      Abstract: Transportation Research Record, Ahead of Print.
      This study evaluated safety effects associated with converting traditional stop control (TSC) to all-way stop control (AWSC) at 53 intersections in Washington, DC. The study utilized an observational treatment group and a randomly selected comparison group. Negative binomial regression modeling was used to estimate the effect of AWSC conversion on crash outcomes, control for confounding factors, and check its statistical significance. The study also examined potential covariates that could influence AWSC crash outcomes, such as the number of legs of the intersection and the functional classification of the intersecting roads. This study found an overall 36% reduction in all crashes and a 42% reduction in injury crashes associated with converting intersections from TSC to AWSC. In addition, the study revealed a statistically significant reduction in right-angle crashes along with a statistically significant increase in straight hit pedestrian crashes. For all the other collision types, including right turn, left turn, rear-end, sideswipes, and bicycle crashes, no statistically significant coefficients were found. With many “Vision Zero” cities considering increased use of AWSC to help achieve their safety goals, it is important to understand and communicate the safety effects of AWSC.
      Citation: Transportation Research Record
      PubDate: 2020-06-13T05:08:22Z
      DOI: 10.1177/0361198120920871
       
  • Reducing Delays on High-Density Railway Lines: London–Shenfield Case
           Study
    • Authors: Giorgio Medeossi, Andrew Nash
      Abstract: Transportation Research Record, Ahead of Print.
      This case study describes the development of a new timetable designed to reduce delays on the London–Shenfield regional railway line in the United Kingdom (UK). Reducing delays on high-density railway lines is challenging because frequent service makes it difficult to identify the root cause of delays and there is limited ability to solve delay problems by adding buffer times to timetables. On the other hand, it is very important to reduce delays on high-density lines since they affect many passengers and because a delay on one train can easily affect following trains. In this study, detailed railway operational data was used together with Oyster card ridership data to identify the root cause of delays and help develop an alternative timetable. The alternative timetable was tested and refined using stochastic simulation. The new timetable was placed in service during 2016 and led to a significant reduction in delays: punctuality within 5-min of scheduled arrival time increased by 6.2% during the most critical hour of the morning peak period. The paper describes the methodology, its application, study results, and transferability.
      Citation: Transportation Research Record
      PubDate: 2020-06-13T05:06:23Z
      DOI: 10.1177/0361198120921159
       
  • Option Value of Contingent Finance Support in Transportation
           Public–Private Partnership Projects
    • Authors: Yunping Liang, Baabak Ashuri
      Abstract: Transportation Research Record, Ahead of Print.
      Uncertainties about construction cost and operational revenues are two major risks in transportation public–private partnership (P3) projects. These uncertainties put projects at risk of being unable to fulfill annual debt repayment obligations. When a project generates insufficient cash flow to service the debt in a certain year, it normally has to go for short-term financing by borrowing short-term loans. With the help of revenue risk-sharing mechanisms, supported projects may be able to get rid of unexpected interest disbursement. The objectives of this paper are twofold: () evaluate the refinancing cost of P3 highway projects caused by cash flow shortage; and () critically examine the option value of contingent finance support and compare it with the option value of minimum revenue guarantee on saving refinancing cost for debt repayment. An integrated real options valuation model is created that utilizes utility method for pricing the technical project risk (e.g., construction cost overruns), and utilizes a risk-neutral option pricing method for pricing the market risk (e.g., future traffic). The proposed model has good transferability in relation to involving various risk factors, no matter technical risks or market risks, random variables or random processes. The proposed model helps stakeholders better understand and measure the burden of assuring annual debt repayment under uncertain cash flow. The stakeholders can use the proposed model to evaluate the value of the revenue risk-sharing mechanisms on reducing refinancing cost.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:15:28Z
      DOI: 10.1177/0361198120923668
       
  • Shifting from Private to Public Transport using Duration-Based Modeling of
           a School-Based Intervention
    • Authors: Mariza Motta Queiroz, Carlos Roque, Filipe Moura
      Abstract: Transportation Research Record, Ahead of Print.
      School commuting with public transportation (PT) and shifting away from private cars remains a challenge, especially for transport planners. From behavioral and cultural viewpoints, car dependence has not yet been reversed in many cities. Actions to promote the shift to PT should be multidisciplinary and multi-instrumental to increase PT adoption and achieve more sustainable mobility. There is a lack of strategic alignment between the different stakeholders involved in school commuting of children (parents, school, PT operators) and empirical studies sustaining the effectiveness of actions to shift away from the car. Moreover, PT behavioral aspects are still poorly researched from a marketing perspective. This research aims to help fill the gap by implementing actions related to the 4Ps of the marketing mix (product, place, price, promotion). Ten schools in the Lisbon Metropolitan Area were involved in those actions and then surveyed (1,760 survey participants) to evaluate the impact on their behavioral change, that is, to start going to school with PT. The study explores the impact of a set of marketing events on the time duration before children shift to PT when commuting to school, with a hazard-based duration model. Results suggest that to promote school commuting with PT, it is necessary to characterize the school community before commencing any mobility-oriented intervention, particularly concerning sociodemographic attributes and mobility patterns. These are critical information to design marketing actions better and to adapt and improve the quality of PT vehicles and services that operate to and from schools.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:15:27Z
      DOI: 10.1177/0361198120923666
       
  • Demonstrative Case of a Pedestrian Network Design Model Considering
           Effects on Motorized Traffic
    • Authors: Christina Iliopoulou, Maria Tseliou, Konstantinos Kepaptsoglou, Stratos Papadimitriou
      Abstract: Transportation Research Record, Ahead of Print.
      The transformation of urban roadways into pedestrian streets is a popular measure for reshaping city parts and enhancing their livability. Nevertheless, pedestrianization schemes are expected to have some impact on the performance of the neighboring road network, especially if these are established ad-hoc or solely based on non-transport criteria. This study introduces a methodological tool for supporting decisions on implementing pedestrianization schemes in urban networks. A bi-level network design model variant is developed for that purpose, whose design objective is to maximize the extent of pedestrian streets in an urban network, while maintaining acceptable impacts to the performance of the road network. Alternative decisions on pedestrianization are considered for each network segment; these include partial (one-directional) or complete (bi-directional) pedestrianization under physical and operational criteria and constraints. The model is applied for a mid-sized urban network in Greece and solved using a genetic algorithm. Results show that the pedestrianization of almost 7% of the road network in relation to length leads to a 40% increase in total network travel time, while a higher ratio of complete versus partial pedestrianization is more advantageous. Outcomes also reveal that that rigid design guidelines should be examined in a case-by-case approach, as superior results may be attained if some constraints, such as those related to the overall street width, are relaxed. Reasonably, policy priorities significantly impact generated solutions and are expected to play a decisive role in the design of pedestrianization schemes.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:15:26Z
      DOI: 10.1177/0361198120922848
       
  • Artificial Neural Network Models for Performance Design of Asphalt
           Pavements Reinforced with Geosynthetics
    • Authors: Adnan Qadir, Uneb Gazder, Karam Un Nisa Choudhary
      Abstract: Transportation Research Record, Ahead of Print.
      Flexible pavements, made up of asphalt concrete, are commonly used for highways all around the world. These pavements suffer from distresses like reflective cracking, rutting and fatigue cracking. Performance-based design methods have been adopted to enhance the service life of flexible pavements. Other measures to enhance the life cycle of these pavements include reinforcement with materials such as geosynthetics. However, there is a gap in the literature on development of performance-based design models for reinforced pavements. In this study, artificial neural network (ANN) models are developed for predicting flexural stiffness and rutting depth of reinforced asphalt pavements using design parameters from the simple laboratory procedures for Marshall and rut depth tests. A multilayer feedforward neural network (MLFNN) was found suitable in this study when a larger dataset was available with a flexural stiffness model. On the other hand, radial basis neural network (RBNN) was found to give higher accuracy with the smaller dataset of rut depth available in this study. In both cases, ANNs were found to predict the parameters with sufficient accuracy. These models show that reinforced asphalt designs with central gradation have the best design. The models developed in this study will be helpful to design long-lasting pavements with geosynthetic reinforcement without the requirement for high-tech testing facilities.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:13:41Z
      DOI: 10.1177/0361198120924387
       
  • Predicting Trip Cancellations and No-Shows in Paratransit Operations
    • Authors: Fernando A. Acosta Pérez, Gabriel E. Rodríguez Ortiz, Everson Rodríguez Muñiz, Fernando J. Ortiz Sacarello, Jee Eun Kang, Daniel Rodriguez-Roman
      Abstract: Transportation Research Record, Ahead of Print.
      The productivity of paratransit systems could be improved if transit agencies had the tools to accurately predict which trip reservations are likely to result in trips. A potentially useful approach to this prediction task is the use of machine learning algorithms, which are routinely applied in, for example, the airline and hotel industries to make predictions on reservation outcomes. In this study, the application of machine learning (ML) algorithms is examined for two prediction problems that are of interest to paratransit operations. In the first problem the operator is only concerned with predicting which reservations will result in trips and which ones will not, while in the second prediction problem the operator is interested in more than two reservation outcomes. Logistic regression, random forest, gradient boosting, and extreme gradient boosting were the main machine learning algorithms applied in this study. In addition, a clustering-based approach was developed to assign outcome probabilities to trip reservations. Using trip reservation data provided by the Metropolitan Bus Authority of Puerto Rico, tests were conducted to examine the predictive accuracy of the selected algorithms. The gradient boosting and extreme gradient boosting algorithms were the best performing methods in the classification tests. In addition, to illustrate an application of the algorithms, demand forecasting models were generated and shown to be a promising approach for predicting daily trips in paratransit systems. The best performing method in this exercise was a regression model that optimally combined the demand predictions generated by the machine learning algorithms considered in this study.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:13:41Z
      DOI: 10.1177/0361198120924661
       
  • Desiccation Cracking Behavior of Clayey Soils Treated with Biocement and
           Bottom Ash Admixture during Wetting–Drying Cycles
    • Authors: Mark Vail, Cheng Zhu, Chao-Sheng Tang, Nate Maute, Melissa Tababa Montalbo-Lomboy
      Abstract: Transportation Research Record, Ahead of Print.
      Desiccation cracking considerably impairs the hydraulic and mechanical properties of clayey soils that are critical to the long-term performance of infrastructure foundations and earth structures. Typical crack remediation methods are associated with high labor and maintenance costs or the use of environmentally unfriendly chemicals. Recycling waste materials and developing biomediated techniques have emerged as green, sustainable soil stabilization solutions. The objective of this study was to investigate the feasibility of soil crack remediation through use of bottom ash admixtures and microbial-induced calcite precipitation (MICP). We carried out cyclic wetting–drying tests to characterize the effects of bottom ash and MICP on the desiccation cracking behaviors of bentonite soils. Two groups of soil samples that contained different percentages of bottom ash (0%, 20%, 40% by weight) were prepared for cyclic water and MICP treatments, respectively. The desiccation cracking patterns captured by a high-resolution camera were quantified using image processing. We also employed scanning electron microscopy for microstructural characterizations. Experimental results revealed that cyclic water treatment resulted in more cracking, whereas cyclic MICP treatment improved soil strength owing to the precipitation of calcite crystals on the soil particle surface and inside the interparticle pores. Adding bottom ash to bentonite reduced the plasticity of the mixture, promoted the flocculation of clay particles by cation exchange, and also provided soluble calcium to enhance calcite precipitation. This study demonstrates the potential of bottom ash and MICP for crack remediation and brings new insights into the design and assessment of sustainable infrastructures under climate changes.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:13:40Z
      DOI: 10.1177/0361198120924409
       
  • Comparison of System Characteristics of the Guangzhou Water Transit System
           with Its International Peers
    • Authors: Matthew I. Burke, Lizhu Dai, Abraham Leung
      Abstract: Transportation Research Record, Ahead of Print.
      With ports having moved downriver, redevelopment of central city areas and waterfronts has transformed the urban centres and created new economic bases for once industrial cities. Water transit systems, such as New York’s East River and City-Wide Ferry services and Gothenburg’s harbor ferries, are being installed by economic development agencies as a device to stimulate further land development, provide tourism opportunities, and promote a new social engagement with the river. Guangzhou’s water transit system is the third largest in Asia by passenger volume, behind only Bangkok and Sydney. This paper describes the Guangzhou system in depth, comparing its operations favourably with the world’s leading water transit systems. Comparisons are made in vessel design, route design, terminals, operations, and fares. The Guangzhou case is distinctive, with a mixture of cross-river and parallel routes, and an especially unique approach to subsidy that may be an option for North American cities considering water transit. Opportunities to further improve the system in line with international trends are identified, as well as a research agenda to further the knowledge of water transit operations and regulation generally.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:13:39Z
      DOI: 10.1177/0361198120925272
       
  • New Pavement Performance Indicators using Crack Fundamental Elements and
           3D Pavement Surface Data with Multiple-Timestamp Registration for Crack
           Deterioration Analysis and Optimal Treatment Determination
    • Authors: Yichang (James) Tsai, Zhongyu Yang
      Abstract: Transportation Research Record, Ahead of Print.
      With the availability of pavement distress information with high granularity, there is a great opportunity to develop and apply new pavement performance indicators, including crack length, width, intersection point, and polygon, derived from crack fundamental elements (CFEs), to study pavement behavior and determine the optimal timing of treatments. Using CFEs and 3D high-resolution pavement surface data, we can study real-world crack deterioration behavior and correlate these new performance indicators to determine optimal maintenance and rehabilitation (M&R) method and timing (e.g., crack filling/sealing) to take full advantage of these 3D pavement surface data. This paper presents a proposed methodology to explore this opportunity. The proposed methodology consists of the following steps: (1) multiple-timestamp 3D pavement data registration, (2) new pavement performance indicators extraction from CFEs, (3) spatial–temporal analysis of new pavement performance indicators, and (4) optimal treatment and timing determination using the proposed spatial–temporal analysis of new pavement performance indicators (e.g., optimal crack filling/sealing timing and location). A case study using 6 years of 3D pavement surface data collected using 3D laser technology on SR-26 in Savannah, Georgia, was conducted to evaluate the feasibility of using the new pavement performance indicators generated by the proposed methodology. The outcomes demonstrate the proposed method is very promising for quantifying and planning M&R treatments (e.g., crack filling/sealing), which has previously been very difficult to achieve. Results also show that multiple-timestamp registration is a very crucial step in ensuring the consistent measurement of regions of interest for different years.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:08:20Z
      DOI: 10.1177/0361198120920877
       
  • Evidence from Urban Roads without Bicycle Lanes on the Impact of Bicycle
           Traffic on Passenger Car Travel Speeds
    • Authors: Jaclyn S. Schaefer, Miguel A. Figliozzi, Avinash Unnikrishnan
      Abstract: Transportation Research Record, Ahead of Print.
      A concern raised by some motorists in relation to the presence of bicycles on urban roads without bicycle lanes, discussed in part of the traffic literature, is that cyclists will slow down motorized vehicles and therefore create congestion. This research answers this question: do bicycles reduce passenger car travel speeds on urban roads without bicycle lanes' To answer this question, a detailed comparative analysis of the travel speeds of passenger car (class two vehicles) on lower volume urban roads without bicycle lanes is presented. Speed distributions, the mean, and the 50th and 85th percentile speeds for two scenarios were examined: (i) a passenger car that was preceded by a bicycle and (ii) a passenger car that was preceded by another passenger car. Peak hour traffic and 24-h traffic speeds were analyzed using t-tests and confidence intervals. Although a few statistically significant differences between scenarios (i) and (ii) were found, the actual speed differences were generally in the order of 1 mph or less. Therefore, differences in class two (motorized passenger) vehicle speeds with and without cyclists were found to be negligible from a practical perspective.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:07:02Z
      DOI: 10.1177/0361198120920880
       
  • Comparison of Cycling Behavior between Keyboard-Controlled and
           Instrumented Bicycle Experiments in Virtual Reality
    • Authors: Martyna Bogacz, Stephane Hess, Chiara Calastri, Charisma F. Choudhury, Alexander Erath, Michael A. B. van Eggermond, Faisal Mushtaq, Mohsen Nazemi, Muhammad Awais
      Abstract: Transportation Research Record, Ahead of Print.
      The use of virtual reality (VR) in transport research offers the opportunity to collect behavioral data in a controlled dynamic setting. VR settings are useful in the context of hypothetical situations in which real-world data does not exist or in situations which involve risk and safety issues making real-world data collection infeasible. Nevertheless, VR studies can contribute to transport-related research only if the behavior elicited in a virtual environment closely resembles real-world behavior. Importantly, as VR is a relatively new research tool, the best-practice with regards to the experimental design is still to be established. In this paper, we contribute to a better understanding of the implications of the choice of the experimental setup by comparing cycling behavior in VR between two groups of participants in similar immersive scenarios, the first group controlling the maneuvers using a keyboard and the other group riding an instrumented bicycle. We critically compare the speed, acceleration, braking and head movements of the participants in the two experiments. We also collect electroencephalography (EEG) data to compare the alpha wave amplitudes and assess the engagement levels of participants in the two settings. The results demonstrate the ability of VR to elicit behavioral patterns in line with those observed in the real-world and indicate the importance of the experimental design in a VR environment beyond the choice of audio-visual stimuli. The findings will be useful for researchers in designing the experimental setup of VR for behavioral data collection.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:05:22Z
      DOI: 10.1177/0361198120921850
       
  • A Correlated Random Parameters Model with Heterogeneity in Means to
           Account for Unobserved Heterogeneity in Crash Frequency Analysis
    • Authors: Xiaoyan Huo, Junqiang Leng, Qinzhong Hou, Hao Yang
      Abstract: Transportation Research Record, Ahead of Print.
      Unobserved heterogeneity induced by omitted variables is a major challenge in developing reliable road safety models. In recent years, the random parameters negative binomial (RPNB) model has been used frequently in crash frequency analysis to account for unobserved heterogeneity. However, the majority of past studies of the RPNB model assumed that there was no correlation between different sources of unobserved heterogeneity, which is not always true given the complex interactions of safety factors. Compared with the RPNB model, a more flexible random parameters model that is the correlated random parameters negative binomial with heterogeneity in means (CRPNBHM) model was proposed in this study. Results indicate that the CRPNBHM model could not only capture the otherwise unobserved heterogeneity, but also track the underlying correlation among different sources of unobserved heterogeneity, thus outperforming the RPNB model. In addition, new insights into the interactions of safety factors (e.g., the joint safety effects of heavy trucks and pavement rutting depth) were obtained from the CRPNBHM model and these are expected to be beneficial in developing effective safety countermeasures. Results from this study demonstrated the CRPNBHM model to be a good alternative for crash frequency analysis, particularly when unobserved heterogeneity was detected.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T09:03:43Z
      DOI: 10.1177/0361198120922212
       
  • Development of a Computer Program for Calculation of the Alpha Parameter
           in the Linear Amplitude Sweep Test and Comparison with Rheological
           Parameters
    • Authors: Seyed Farhad Abdollahi, Mehdi Farrokhi, Nader Tabatabaee
      Abstract: Transportation Research Record, Ahead of Print.
      Characterizing and modeling the fatigue performance of an asphalt binder is important when designing asphalt mixtures which can resist premature fatigue failure. Performance grading (PG) standards include the fatigue factor (G*.sinδ) to evaluate the fatigue resistance of asphalt binders. This criterion seems to be inaccurate, especially when applied to modified asphalt binders. American Association of State Highway and Transportation Officials (AASHTO) TP 101 has been designed to evaluate the fatigue resistance of asphalt binders using Schapery’s work potential theory. The damage evolution rate (α parameter) is the key element of this method and is calculated from the rheological properties of the undamaged asphalt binder using the slope of the relaxation modulus versus the time on the log-log scale. Owing to the difficulties of conducting the relaxation test, the relaxation modulus is usually obtained using conversion methods. However, AASHTO TP 101 uses a simplified indirect method to calculate α. The present study developed a computer program called RheoSUT with which to construct relaxation master curves using different methods. The relaxation master curves of 27 asphalt binders were evaluated for estimation of the value of α. The results indicated that AASHTO TP 101 yields higher values of α. The results of the sensitivity analysis show that overestimation of α will result in up to about 200% error in the estimation of the fatigue life (Nf). It is also shown that binder aging and styrene-butadiene-styrene (SBS) modification directly affected the rheological parameters and relaxation master curves. Finally, it is recommended to use the relaxation-master curved based methods of calculation of α instead of the storage-modulus based ones.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T08:50:36Z
      DOI: 10.1177/0361198120922042
       
  • Multi-Period Optimization Model for Siting Capacitated Intermodal
           Facilities
    • Authors: Vishal Badyal, William G. Ferrell, Nathan Huynh, Bhavya Padmanabhan
      Abstract: Transportation Research Record, Ahead of Print.
      The objective of this study is to design an intermodal transport network considering multiple planning periods and accounting for product volume, mode, budget, and inventory at intermodal terminals (IMTs). A mixed integer linear programming model is developed. An experimental study is conducted for the State of South Carolina using the Freight Analysis Framework Version 4.5 (FAF4) dataset. Sensitivity analyses are performed to study the impact of budget, the maximum number of IMTs allowed, and increasing demand on the intermodal network design. The experimental results indicate that Columbia as an IMT location has a significantly effects on the total network cost and intermodal shipping share. Increasing the budget and number of IMTs allowed improved the network performance non-linearly.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T08:46:04Z
      DOI: 10.1177/0361198120921165
       
  • Performance-Based Approach for Deciding Concrete Age for Healer Sealer
           Application on New Concrete
    • Authors: Abul Fazal Mazumder, Upul Attanayake, Neal S. Berke
      Abstract: Transportation Research Record, Ahead of Print.
      Healer sealer application is one of the capital schedule maintenance (CSM) activities for enhancing concrete bridge deck durability and extending the service life. A healer sealer is expected to seal the cracks and reduce the rate of chloride ion ingress. Highway agency policies and manufacturer specifications require maintaining a total of 28-day curing period (7-day wet and 21-day dry curing) before the application of a healer sealer on bridge decks with new concrete in patches and repairs. Consequently, the contractors have to wait for 28 days to apply a healer sealer. Delaying application time increases project completion time and cost of construction and mobility. This paper presents a performance-based approach for evaluating the possibility of reducing the 28-day waiting period for healer sealer application on bridge decks with new concrete. An experimental program was developed and executed to evaluate the impact of healer sealer application parameters on crack sealing ability. A healer sealer was applied at 14, 21, and 28 days of concrete age. The treated surface was ponded with 3% NaCl. The performance of the treated concrete was evaluated using the acid-soluble chloride content test. The results showed the possibility of applying a sealer before the end of the 28-day curing period stipulated in the current specifications. The performance-based approach presented in this paper can be used to identify the age of concrete for healer sealer application.
      Citation: Transportation Research Record
      PubDate: 2020-06-12T08:44:58Z
      DOI: 10.1177/0361198120923363
       
  • Potential Contribution of Deflection-Induced Fuel Consumption to U.S.
           Greenhouse Gas Emissions
    • Authors: Hessam AzariJafari, Jeremy Gregory, Randolph Kirchain
      Abstract: Transportation Research Record, Ahead of Print.
      Various methods have been proposed to reduce greenhouse gas (GHG) emissions associated with transportation. We investigate the potential of increasing the elastic modulus of pavement surface layers across the entire U.S. pavement network as a means of lowering vehicle excess fuel consumption (EFC) resulting from deflection-induced pavement–vehicle interaction. We show that in a business-as-usual case deflection-induced EFC represents up to 2660 million metric tons (Mt) over a 50-year analysis period. Elastic modulus increases can be accomplished using several currently implementable methods. The analysis shows that increasing the modulus of elasticity using 10% resurfacing in the network per year leads to an 18% reduction of GHG emissions from the pavement network, or 440 Mt CO2eq, over a 50-year analysis period. This would potentially offset 0.5% of the future GHG emission of the whole transportation sector.
      Citation: Transportation Research Record
      PubDate: 2020-06-11T06:52:06Z
      DOI: 10.1177/0361198120926169
       
  • Lessons from a Large-Scale Experiment on the Use of Smartphone Apps to
           Collect Travel Diary Data: The “City Logger” for the Greater Golden
           Horseshoe Area
    • Authors: Ahmadreza Faghih Imani, Chris Harding, Siva Srikukenthiran, Eric J. Miller, Khandker Nurul Habib
      Abstract: Transportation Research Record, Ahead of Print.
      Smartphones offer a potential alternative to collect high-quality information on the travel patterns of individuals without burdening the respondents with reporting every detail of their travel. Smartphone apps have recently become a common tool for travel survey data collection around the world, especially for multiday surveys. However, there still exists a lack of systematic assessment of issues related to smartphone app-based surveys, such as the impact of app design or the recruitment method on the collected data. Through a large-scale experiment (named the City Logger), this paper assesses the data produced by the City Logger app, to better understand recruitment avenues (targeted invitation versus crowdsourcing), and examine differences in respondents’ travel behavior recruited through crowdsourcing methods. The paper also examines how app design, and particularly the user input method for trip validation, influences participants’ responses. The results indicate that, while crowdsourcing recruitment is promising, it might not yet be the best way to capture a true representation of the population. For app design, a combination of real-time and travel diary approaches is recommended. An ideal app would prompt users real-time and create a travel diary, so users can validate, edit, or delete the recorded information.
      Citation: Transportation Research Record
      PubDate: 2020-06-10T06:37:49Z
      DOI: 10.1177/0361198120921860
       
  • Quantitative Analysis of Macrotexture of Asphalt Concrete Pavement Surface
           Based on 3D Data
    • Authors: Ju Huyan, Wei Li, Susan Tighe, Zhaoyun Sun, Hongchao Sun
      Abstract: Transportation Research Record, Ahead of Print.
      This research conducts a quantitative analysis on the macrotexture of asphalt concrete pavement based on three-dimensional (3D) point cloud data. A binocular stereovision-based 3D point cloud data collection system is developed. The system is composed of a packaged component that includes a lighting source and two cameras, a dark shading cloth, and the computer control side with the configuration of the operation interface. Meanwhile, specimens of both asphalt concrete and open graded friction course (OGFC) are prepared as the test specimens. Next, 3D point cloud data of the specimens are collected using the proposed system. The macrotexture information is then extracted using the robust Gaussian method. The macrotextures of the pavement surface are characterized by 10 indicators; profile arithmetic average deviation, profile root mean square difference, mean texture depth, profile skewness value, profile steepness, profile unevenness distance, profile peak distance, profile root mean square slope, profile root mean square wavelength, and surface roughness area ratio. At the same time, the friction coefficients of these specimens are measured by British Pendulum Number. Finally, the correlations between each indicator and the friction conditions of different specimens are assessed. Results demonstrate that the proposed macrotexture indicators are reliable for evaluating the friction conditions because significant correlations have been observed. Meanwhile, the correlations for the OGFC gradations are always higher than the asphalt concrete gradations. All the findings prove that the proposed quantitative indicators are effective for the characterization of the macrotexture of asphalt concrete pavement.
      Citation: Transportation Research Record
      PubDate: 2020-06-10T06:37:13Z
      DOI: 10.1177/0361198120920269
       
  • Safety Prediction Model for Reinforced Highway Slope using a Machine
           Learning Method
    • Authors: Asif Ahmed, Sadik Khan, Sahadat Hossain, Tural Sadigov, Prabesh Bhandari
      Abstract: Transportation Research Record, Ahead of Print.
      Recycled plastic pin (RPP) has been proved to be an effective and inexpensive solution for shallow slope stabilization. Current practice suggests conducting numerical modeling to find out the desired factor of safety (FS) using RPP in the design of landslide repair. While the slope stability is heavily dependent on soil strength parameters and slope geometry, RPP length and spacing can also play a significant role in reaching the target factor of safety for the highway slope. During this study, a safety prediction model was developed using both statistical and machine learning (ML) approaches to use RPP in slope stabilization. Initially, parametric study was conducted using five different soil strengths, six slope heights, three slope ratios, three RPP lengths, and five RPP spacing configurations. Using the strength reduction techniques of Finite Element Modeling Software PLAXIS 2D, FS was determined for more than 1,000 combinations. Afterwards, a statistical approach was undertaken to determine a safety prediction model containing all possible parameters. Finally, an ML approach was conducted for safety model. The ML approach was found to be more accurate than the classical statistical approach with 85% accuracy of predicting the FS for an RPP reinforced highway slope. The developed model was validated against the values obtained from the numerical modeling, which indicated that the SF obtained from the developed model was in good agreement with those from finite element method (FEM) analysis.
      Citation: Transportation Research Record
      PubDate: 2020-06-09T11:21:05Z
      DOI: 10.1177/0361198120924415
       
  • Laboratory Investigation of the Performance Evaluation of Fiber-Modified
           Asphalt Mixes in Cold Regions
    • Authors: Luis Alberto Perca Callomamani, Leila Hashemian, Katrina Sha
      Abstract: Transportation Research Record, Ahead of Print.
      Thermal cracking of pavement is caused by contraction of the asphalt layer at low temperatures, when tensile stresses build up to a critical point at which a crack is formed. The cracks formed then propagate under traffic loading conditions. Freeze-thaw cycles accelerate crack propagation and deterioration of the asphalt layer, and can also lead to the formation of more severe distresses such as potholes. Fibers have attracted increasing attention in the asphalt industry for use as asphalt concrete modifiers. The addition of fibers to hot mix asphalt (HMA) results in a composite material that has a higher tensile strength, along with the ability to absorb greater energy during the fracture process. The fibers within the material also act as a barrier preventing the formation and propagation of cracks in the asphalt mix. This research evaluates the effectiveness of adding polymer fibers to HMA to increase both its resistance to cracking at intermediate and low temperatures, and its rutting resistance and moisture susceptibility at high temperatures. For this purpose, three different types of polymer fibers: aramids, polyethylene terephthalate (PET), and polyacrylonitrile (PAN), were added to conventional HMA mixes. The resulting samples were compacted, and their mechanical properties were compared with conventional HMA in the laboratory. At the end of the paper, a material cost comparison is provided as a reliable source of information when selecting materials to fulfill minimum industry specifications.
      Citation: Transportation Research Record
      PubDate: 2020-06-09T07:09:50Z
      DOI: 10.1177/0361198120922213
       
  • Prevention of End-of-Track Collisions in Passenger Terminals via Positive
           Train Control: Benefit-Cost Analysis and Operational Impact Assessment
    • Authors: Zhipeng Zhang, Xiang Liu, Keith Holt
      Abstract: Transportation Research Record, Ahead of Print.
      End-of-track collisions at passenger terminals have raised safety concerns because of their potentially severe consequences such as infrastructure and rolling stock damage, service disruption, and even casualties. As introduced in the previous study sponsored by the U.S. Federal Railroad Administration, the implementation of Positive Train Control (PTC) systems at passenger terminal stations could potentially prevent end-of-track collisions. As the second phase of that project, this paper aims to provide a comprehensive evaluation of the proposed concept of operation via quantitatively identifying the safety benefits, incremental costs, and operational impacts associated with PTC enforcement on terminating tracks. The benefit-cost analysis indicates that the safety benefits may exceed the incremental costs over a 20-year period under specified circumstances and assumptions. In addition, the preliminary results disclose that the operational impact in PTC enforcement should be negligible, except for the rare occurrence of wayside interface unit (WIU) failure or radio failure in the Interoperable Electronic Train Management System (I-ETMS)-type PTC system that would result in a stop well short of the targeted point and potentially delay both onboard passengers and inbound/outbound trains. Both benefit-cost analysis and operational impact assessment methodologies are implemented in a decision tool that can be customized for different terminals with heterogeneous infrastructure and operational characteristics and be adapted to other transportation modes.
      Citation: Transportation Research Record
      PubDate: 2020-06-09T07:07:45Z
      DOI: 10.1177/0361198120920628
       
  • Natural Experiment to Assess the Impacts of Street-Level Urban Design
           Interventions on Walkability and Business Activity
    • Authors: Maher Said, Georges Geha, Maya Abou-Zeid
      Abstract: Transportation Research Record, Ahead of Print.
      This study uses a natural experiment in Beirut, Lebanon, to investigate the effects of a street-level urban design intervention that improved the walking environment through a wider sidewalk, removal of a parking lane, raised junctions, and other elements. This study analyzes the impacts on pedestrian flow, pedestrian satisfaction with the walking experience, commercial activity, and business managers’ attitudes. Difference-in-difference regressions suggest that the main effect of such interventions is not necessarily an increase in pedestrian traffic, but instead safer pedestrian maneuvering and a better walking experience. It is also found through descriptive analysis that while businesses and shops experience increased business post-intervention, noticeable dissatisfaction with the intervention is reported by managers and owners. It is hypothesized that this dissatisfaction is a result of the lengthy construction process renovating and refurbishing the street, and the removal of parking spaces. Policy recommendations are drawn for the mitigation of business managers’ concerns and the enhancement of the walking environment for the design of future similar interventions.
      Citation: Transportation Research Record
      PubDate: 2020-06-09T06:52:35Z
      DOI: 10.1177/0361198120921849
       
  • Analysis of Overtaking Maneuvers to Cycling Groups on Two-Lane Rural Roads
           using Objective and Subjective Risk
    • Authors: Griselda López, Ana María Pérez-Zuriaga, Sara Moll, Alfredo García
      Abstract: Transportation Research Record, Ahead of Print.
      In Spain, the presence of cyclists’ groups riding on two-lane rural roads in a single file or in parallel line is growing. The number of overtaking maneuvers to them is also increasing. This is one of the most dangerous interactions between motor vehicles and bicycles. However, the risk of these maneuvers has not been analyzed in depth. This research analyzes the objective and subjective risk of overtaking maneuvers to cyclists’ groups. During this maneuver, the motorized vehicle overtakes the bicycles with a certain speed and lateral distance. These are the surrogate measures used to analyze the objective risk, whereas the subjective risk was analyzed based on the subjective risk perception that 10 cyclists riding instrumented bicycles (in different group configurations) indicated when every motor vehicle overtook them. Results show that the cyclists most exposed to the overtaking maneuver are those at the front and at the rear of the group. In relation to the configuration, the risk is higher in parallel lines, as the lateral clearance is lower compared with a single line. It is even higher when the overtaking maneuver is flying, which is usually performed at higher speeds and lower lateral clearance. The subjective risk perception increases with higher speed and lower lateral clearance, and is higher at the rear positions. Overtaking in which lateral distance is less than 1.5 m is perceived as the riskiest. These results provide scientific recommendations to enhance safety for cyclists’ groups, and to integrate cycling with vehicular traffic on two-lane rural roads.
      Citation: Transportation Research Record
      PubDate: 2020-06-05T11:38:30Z
      DOI: 10.1177/0361198120921169
       
  • Comparative Study of Cyclic and Shake Table Tests for Simple for Dead Load
           and Continuous for Live Load Steel Bridge System in Seismic Area
    • Authors: Amir Sadeghnejad, Sheharyar Rehmat, Islam M. Mantawy, Atorod Azizinamini
      Abstract: Transportation Research Record, Ahead of Print.
      A new superstructure to pier connection for simple for dead load and continuous for live load (SDCL) steel bridge system in seismic areas was developed. As proof of concept, component level and system level tests were carried out on scale models. The component test was conducted under cyclic loading and the results showed satisfactory performance conforming to design standards. The same detail was incorporated in a system level shake table testing which was subjected to bidirectional earthquake excitations. The results showed that the connection behaved well under high levels of drift and acceleration. The capacity protected elements sustained minimal damage and the plastic hinge was limited to a predefined location in the column. In this paper, a summary of results from both tests is presented and compared. The results showed that the SDCL components remained within the elastic range. It was concluded that the dowel bars in the cap beam are the main load-carrying elements under excitations in the longitudinal direction of the bridge and the provisions of current design codes are adequate for the design of these reinforcing bars. Both test protocols showed similar behavior despite the differences in construction methods and material properties.
      Citation: Transportation Research Record
      PubDate: 2020-06-05T11:35:38Z
      DOI: 10.1177/0361198120921853
       
  • Reliability-Based Design for Passing Maneuvers Based on Observational Data
    • Authors: Udai Hassein
      Abstract: Transportation Research Record, Ahead of Print.
      Two-lane roadways constitute the largest proportion of road networks. Their operational characteristics are significantly different from other road classifications. Allowing passing maneuvers is considered as one of the effective measures to improve mobility levels along two-lane highways, while crash records show that head-on collisions, which usually are attributed to passing maneuvers, are among the most common and most severe types of crashes on two-lane roadways. Therefore, rational and realistic estimation of the needed passing sight distance (PSD) considering driver behavior is essential for the safe design of passing zones along two-lane highways. Several random variables help to determine the minimum length required for safe passing maneuvers. Current PSD models are based on single deterministic values of the input variables to determine PSD values. This paper presents a reliability model PSD that accounts for the variability of the input random variables to offer a better representation of real-life conditions. The objectives of this paper are: (1) to design driving simulator and field experiments for data collection, (2) to develop a PSD model using the mechanics of passing maneuvers, (3) to develop a reliability model based on the first-order second-moment (FOSM) method, and (4) to validate the model using Monte Carlo simulation. In this study, driving simulator experiments were conducted to determine the passing behavior of drivers, and field data were used to validate the proposed PSD model. The proposed model accounts for the variability in the parameters by using the mean and standard deviation in a closed form estimation method. The analysis was performed for a design speed of 80 km/h, and the corresponding PSD distribution was established. A comparison of the results of the proposed model, which reflects driver behavior, and those of existing models was presented. Using the reliability-based design method, transportation engineers can adjust the PSD to fulfill a desired probability of non-compliance.
      Citation: Transportation Research Record
      PubDate: 2020-06-05T11:34:50Z
      DOI: 10.1177/0361198120920875
       
  • Lane Detection and Lane-Changing Identification with High-Resolution Data
           from a Swarm of Drones
    • Authors: Emmanouil Barmpounakis, Guillaume M. Sauvin, Nikolaos Geroliminis
      Abstract: Transportation Research Record, Ahead of Print.
      In the era of big data, new transportation-related concepts and methodologies need to be proposed to understand how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment using a swarm of drones over a dense city center, has uncovered new opportunities for revisiting and evaluating existing concepts, and new ways to describe significant traffic-related phenomena. This dataset is part of an open science initiative shared with the research community and consists of more than half a million detailed trajectories of almost every vehicle that was present in the study area. The aim of this paper is to describe the first methodological approach to how such information can be utilized to extract lane-specific information from this new kind of data and set the benchmark for possible future approaches. Specifically, we describe the methodological framework of two related algorithms: lane detection and lane-changing maneuver identification. Azimuth was the main concept utilized in this methodological framework to overcome existing issues in the literature related to identifying lane-changing maneuvers. The combination of high-quality data, clustering techniques, and detailed spatial information in the lane-detection algorithm indicated it was an effective tool without the need for complex computational effort. Moreover, high-resolution data together with modern time-series analysis tools for lane-changing identification, showed that high-accuracy predictive algorithms can be obtained. The accuracy of both tools was over 95%. Challenging scenarios are identified for future studies and to further improve the tools.
      Citation: Transportation Research Record
      PubDate: 2020-06-05T11:29:55Z
      DOI: 10.1177/0361198120920627
       
  • City-to-City and Temporal Assessment of Peer City Scooter Policy
    • Authors: Caroline Janssen, William Barbour, Erin Hafkenschiel, Mark Abkowitz, Craig Philip, Daniel B. Work
      Abstract: Transportation Research Record, Ahead of Print.
      This paper presents a micromobility scooter policy comparison between 10 mid-sized peer cities with respect to 12 policy dimensions. Because of the evolutionary nature of the policy, a temporal analysis of policy dimensions is required, which we conduct and present in this work. The impact of these individual policies reaches across the city itself, the operating company, and the mobility user—all of which are assessed throughout this work. Many of these policy dimensions are acute pain points for cities, such as fleet caps, permitting fees, and equity requirements. In the temporal analysis, some dimensions show not just happenstance variability in attempts to manage forms of micromobility, but appreciable trends. Approximately 1 year after the deployment of dockless electric scooters in cities throughout the United States and the world, cities have made multiple attempts at regulations and legislation to handle the new mobility mode. Throughout this time, cities have agreed from the start in some aspects of policy such as device removal, safety, speed limit, and bonds. In other dimensions, such as fleet expansion plans, equity regulations, and parking requirements, cities see directed movement over time toward a convergence point.
      Citation: Transportation Research Record
      PubDate: 2020-06-05T11:28:49Z
      DOI: 10.1177/0361198120921848
       
  • Control Design, Stability Analysis, and Traffic Flow Implications for
           Cooperative Adaptive Cruise Control Systems with Compensation of
           Communication Delay
    • Authors: Yu Zhang, Yu Bai, Jia Hu, Meng Wang
      Abstract: Transportation Research Record, Ahead of Print.
      Communication delay is detrimental to the performance of cooperative adaptive cruise control (CACC) systems. In this paper, we incorporate communication delay explicitly into control design and propose a delay-compensating CACC. In this new CACC system, the semi-constant time gap (Semi-CTG) policy, which is modified on the basis of the widely-used CTG policy, is employed by a linear feedback control law to regulate the spacing error. The semi-CTG policy uses historical information of the predecessor instead of its current information. By doing so, communication delay is fully compensated, which leads to better stability performance. Three stability properties—local stability, string stability, and traffic flow stability—are analyzed. The local stability and string stability of the proposed CACC system are guaranteed with the desired time gap as small as the communication delay. Both theoretical analysis and simulation results show that the delay-compensating CACC has better string stability and traffic flow stability than the widely-used CACC system. Furthermore, the proposed CACC system also shows the potential for improving traffic throughput and fuel efficiency. Robustness of the proposed system against uncertainties of sensor delay and vehicle dynamics is also verified with simulation.
      Citation: Transportation Research Record
      PubDate: 2020-06-05T02:18:15Z
      DOI: 10.1177/0361198120918873
       
  • Contribution of MnROAD Research to Improvements in Concrete Pavement
           Technology from 1994–2019
    • Authors: Thomas Burnham, Benjamin Worel, Bernard Izevbekhai
      Abstract: Transportation Research Record, Ahead of Print.
      By the late 1980s several states, including Minnesota, began to wonder if American Association of State Highway Official (AASHO) based asphalt and concrete pavement designs were still valid, given the significant changes in traffic loads, materials and construction practices over time. This interest in validating current designs, as well as seeking improved and more efficient designs and materials, led to the creation of the Minnesota Road Research facility, known as MnROAD. Construction of the first phase of test sections at MnROAD took place from 1991 to 1994, and it was open to traffic loading commencing on July 15, 1994. Since 1994, three phases of pavement research have been, and continue to be, conducted at MnROAD. In its first 25 years of operation, an overwhelming amount of pavement research and development has been accomplished at MnROAD. The focus of this paper is to describe many of the more unique and significant findings that have improved concrete pavement technology not only in Minnesota, but throughout the U.S. and other parts of the world. The contributions are categorized into the following areas: design, materials, construction, rehabilitation, pavement monitoring and evaluation, and full-scale testing. In each of the areas, the significant contributions are described and relevant references are cited. The positive contributions of MnROAD toward concrete pavement knowledge and technology have been recognized, and as a result, the MnROAD facility will continue to operate successfully into the future under the National Road Research Alliance (NRRA).
      Citation: Transportation Research Record
      PubDate: 2020-06-03T06:09:49Z
      DOI: 10.1177/0361198120920874
       
  • Crash Testing and Evaluation of Culvert-Mounted Midwest Guardrail System
    • Authors: Mojdeh Asadollahi Pajouh, Robert W. Bielenberg, Jennifer D. Schmidt-Rasmussen, Ronald K. Faller
      Abstract: Transportation Research Record, Ahead of Print.
      Concrete box culverts are usually installed under roadways to allow water drainage without affecting the motoring public. Culvert openings can represent a hazard on the roadside when they do not extend outside of the clear zone, and often require safety treatments in the form of roadside barriers. In this study, a modified design of Midwest Guardrail System (MGS) was evaluated for installation on a low-fill culvert with the strong-post attachment using through-bolts and epoxy anchorage through full-scale crash testing. The test installation consisted of MGS with a 31 in. top rail height, supported by W6 × 9 posts, spaced at 37½ in., attached to a low-fill culvert’s top slab with a 12 in. offset from the back of the post to the culvert headwall. Two crash tests were conducted according to the American Association of State Highway and Transportation Officials’ (AASHTO) Manual for Assessing Safety Hardware (MASH) 2016 Test Level 3 impact safety criteria. In test number CMGS-1, a 2,428-lb car impacted the MGS attached to the culvert at a speed of 61.3 mph and at an angle of 25.1°. In test number CMGS-2, a 5,013-lb pickup truck impacted the MGS attached to the culvert at a speed of 62.8 mph and an angle of 25.7°. In both tests, the vehicle was safely redirected and captured. Both tests were deemed acceptable according to TL-3 safety criteria in MASH. Recommendations were made for the safe installation of MGS atop low-fill culverts as well as transitions from the standard MGS to the culvert-mounted MGS.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T06:08:13Z
      DOI: 10.1177/0361198120921168
       
  • Delineator for Separated Bicycle Lanes at Sidewalk Level
    • Authors: Billie Louise (Beezy) Bentzen, Alan C. Scott, Linda Myers
      Abstract: Transportation Research Record, Ahead of Print.
      The City and County of San Francisco sponsored research to identify a delineator for separated bicycle lanes at sidewalk level that is at least as detectable as truncated-dome detectable warning surface (DWS) by pedestrians with visual impairments, and that is not a barrier to pedestrians with mobility impairments. Tested as potential delineators were a 12-in. wide continuous raised trapezoid (0.75 in. high), and 12- and 24-in. wide installations of relatively wide flat-top bars (FTBs) and of a “corduroy” surface of narrower bars spaced more closely together (both 0.2 in. high). Thirty-one visually-impaired participants detected all five surfaces in addition to DWS, a total of six times each, from 90° and 25° approaches, with mean detection accuracies better than 90% for all surfaces (no significant differences). The long white cane intruded into the cycle track significantly less frequently with 24-in. wide surfaces. In a counterbalanced manner, participants also briefly stepped onto each surface eight times, each time identifying it as “domes,”“bars,” or “trapezoid.” They identified the trapezoid significantly better (mean rate of correct identification = 98.8%) than all other surfaces. A majority of participants with vision disabilities preferred the trapezoid. Thirty participants with a variety of mobility impairments, using a variety of aids, crossed each surface four times with little significant difference from the DWS in effort, instability, and discomfort or pain. No surface was found to be a barrier to crossing. The trapezoidal surface was recommended as the delineator, although the 24-in. FTBs also performed very well.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T06:07:43Z
      DOI: 10.1177/0361198120922991
       
  • Integrating Supply and Demand Perspectives for a Large-Scale Simulation of
           Shared Autonomous Vehicles
    • Authors: Krishna Murthy Gurumurthy, Felipe de Souza, Annesha Enam, Joshua Auld
      Abstract: Transportation Research Record, Ahead of Print.
      Transportation Network Companies (TNCs) have been steadily increasing the share of total trips in metropolitan areas across the world. Micro-modeling TNC operation is essential for large-scale transportation systems simulation. In this study, an agent-based approach for analyzing supply and demand aspects of ride-sourcing operation is done using POLARIS, a high-performance simulation tool. On the demand side, a mode-choice model for the agent and a vehicle-ownership model that informs this choice are developed. On the supply side, TNC vehicle-assignment strategies, pick-up and drop-off operations, and vehicle repositioning are modeled with congestion feedback, an outcome of the mesoscopic traffic simulation. Two case studies of Bloomington and Chicago in Illinois are used to study the framework’s computational speed for large-scale operations and the effect of TNC fleets on a region’s congestion patterns. Simulation results show that a zone-based vehicle-assignment strategy scales better than relying on matching closest vehicles to requests. For large regions like Chicago, large fleets are seen to be detrimental to congestion, especially in a future in which more travelers will use TNCs. From an operational point of view, an efficient relocation strategy is critical for large regions with concentrated demand, but not regulating repositioning can worsen empty travel and, consequently, congestion. The TNC simulation framework developed in this study is of special interest to cities and regions, since it can be used to model both demand and supply aspects for large regions at scale, and in reasonably low computational time.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T06:06:44Z
      DOI: 10.1177/0361198120921157
       
  • Safety Evaluation of Median U-Turn Crossover-Based Intersections
    • Authors: Ma’en Mohammad Ali Al-Omari, Mohamed Abdel-Aty, Jaeyoung Lee, Lishengsa Yue, Ahmed Abdelrahman
      Abstract: Transportation Research Record, Ahead of Print.
      Alternative innovative designs for intersections were defined to enhance traffic operation and safety. Median U-turn (MUT) and restricted crossing U-turn (RCUT) intersections are among the types of alternative intersections that enable drivers to make left-turn movements at median U-turn crossovers downstream of the main intersection. Recently, municipalities and transport agencies have tended to implement these types of intersections. However, their effectiveness in crash reduction has not been adequately determined in previous studies. This is because of the limited number of alternative intersections that were considered in these studies. In addition, there was no consideration for the unusual new geometric design of these intersections. In this study, a safety evaluation was conducted while considering the new intersection-related areas at MUT and RCUT intersections to clarify and quantify their effectiveness in crash reduction. This study considered 73 MUT and 12 RCUT intersections. Two types of MUT intersections were considered in this study. Crash modification factors for MUT and RCUT intersections were estimated by using before–after and cross-sectional methods. The results indicated that MUT and RCUT intersections are safer than conventional intersections. MUT intersections are effective in reducing total, property damage only (PDO), rear-end, and opposite-direction sideswipe crashes, although they significantly increase single-vehicle and non-motorized crashes. RCUT intersections are effective in reducing fatal-and-injury, injury, head-on, and angle crashes. Findings of this research provide clear evaluation for decision makers about the effectiveness of MUT and RCUT intersections in crash reduction.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T06:04:05Z
      DOI: 10.1177/0361198120921158
       
  • Field Evaluation of Connected Vehicle-Based Transit Signal Priority
           Control under Two Different Signal Plans
    • Authors: Qinzheng Wang, Xianfeng (Terry) Yang, Blaine D. Leonard, Jamie Mackey
      Abstract: Transportation Research Record, Ahead of Print.
      In 2017, a connected vehicle (CV) corridor utilizing dedicated short-range communication (DSRC) technology was built along Redwood Road, Salt Lake City, Utah. One main goal of this CV corridor is to implement transit signal priority (TSP) when the bus is behind its published schedule by a certain threshold. With the data generated by the transit vehicles, transmitted through the DSRC system, logged by traffic signal controller, and coupled with the Utah Transit Authority (UTA) data from transit operation system, some performance data of the TSP can be analyzed including TSP requested, TSP served, bus reliability, bus travel time, and bus running time. For providing better signal coordination to buses, the signal plan for this CV corridor underwent retiming in October 2018. This research aims to compare the TSP performance before and after the signal retiming. The field data of August, September, November, and December in 2018 were selected to perform this evaluation. Results show that the TSP served rate after signal retiming is 35.29%, which is higher than that of 33.12% before signal retiming. In addition, compared with the signal plan before October, bus reliability northbound and southbound on the CV corridor was improved by 2.4% and 1.47%, respectively; bus travel time and bus running time were reduced as well.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T05:58:59Z
      DOI: 10.1177/0361198120921161
       
  • Households’ Intended Evacuation Transportation Behavior in Response to
           Earthquake and Tsunami Hazard in a Cascadia Subduction Zone City
    • Authors: Chen Chen, Alexandra Buylova, Cadell Chand, Haizhong Wang, Lori A. Cramer, Daniel T. Cox
      Abstract: Transportation Research Record, Ahead of Print.
      Earthquakes along the Cascadia subduction zone would generate a local tsunami that could arrive at coastlines within minutes. Few studies provide empirical evidence to understand the potential behaviors of local residents during this emergency. To fill this knowledge gap, this study examines residents’ perceptions and intended evacuation behaviors in response to an earthquake and tsunami, utilizing a survey sent to households in Seaside, OR. The results show that the majority of respondents can correctly identify whether their house is inside or outside a tsunami inundation zone. Older respondents are more likely to identify this correctly regardless of any previous disaster evacuation experience or community tenure. The majority of respondents (69%) say they would evacuate in the event of a tsunami. Factors influencing this choice include age, motor ability, access to transportation, and trust in infrastructure resiliency or traffic conditions. While the City of Seaside actively promotes evacuation by foot, 38% of respondents still state they would use a motor vehicle to evacuate. Females and older respondents are more likely to evacuate by foot. Respondents with both higher confidence in their knowledge of disaster evacuation and higher income are more likely to indicate less time needed to evacuate than others. Generally, respondents are more likely to lead rather than follow during an evacuation, especially respondents who report being more prepared for an evacuation and who have a higher perceived risk. This study showcases a unique effort at empirically analyzing human tsunami evacuation lead or follow choice behavior.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T05:58:04Z
      DOI: 10.1177/0361198120920873
       
  • Durable High Early Strength Concrete via Internal Curing Approach using
           Saturated Lightweight and Recycled Concrete Aggregates
    • Authors: Faisal Qadri, Christopher Jones
      Abstract: Transportation Research Record, Ahead of Print.
      Concrete pavements tend to degrade at joints when concrete gets exposed to freeze-thaw cycles in the presence of moisture. In Kansas, U.S., one common repair method for deteriorated concrete pavement involves patching with high early strength concrete (HESC). For heavily trafficked routes and intersections, this is often done at night, so that the pavement can be opened to traffic next morning. Often, patched concrete shows poor durability lasting for just few years. HESC mixtures often include high cement content and low water-to-cement ratio. These factors lead to shrinkage that creates cracks which, in turn, facilitate the ingress of detrimental substances that eventually degrade patches. Internal curing (IC) has been explored in this study to improve the durability of HESC repair materials. Saturated lightweight aggregates and recycled crushed concrete were used to replace a portion of the virgin fine aggregates. Both mixtures were compared with a control mixture. These three mixtures were replicated for low and high cement contents. The test program focused on assessing two main performance indicators—strength development and durability. Durability testing included autogenous and drying shrinkage, and freeze-thaw cycling where relative dynamic modulus of elasticity, expansion, and mass change were measured. Target strengths were achieved in all mixtures. Autogenous shrinkage test results showed that IC significantly improves shrinkage potential and durability. For these mixtures, low cement content also appears to improve durability.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T05:56:16Z
      DOI: 10.1177/0361198120920882
       
  • Comprehensive Approach to Measure the Mobility Energy Productivity of
           Freight Transport
    • Authors: Kyungsoo Jeong, Venu Garikapati, Yi Hou, Alicia Birky, Kevin Walkowicz
      Abstract: Transportation Research Record, Ahead of Print.
      Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement are critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting has been gaining pace in recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregate in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance or productivity of freight systems. Addressing the research need, this paper presents the “Freight Mobility Energy Productivity” metric to quantify freight productivity of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, and shows intuitive results in quantifying freight productivity. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight productivity as a result of vehicle electrification. The relative differences in Freight Mobility Energy Productivity scores help identify which zones benefit from the vehicle powertrain technology improvement. The results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the productivity of existing as well as future freight trends and technologies.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T05:55:16Z
      DOI: 10.1177/0361198120920879
       
  • Collaborative Parcels Logistics via the Carrier’s Carrier Operating
           Model
    • Authors: Fraser McLeod, Tom Cherrett, Oliver Bates, Tolga Bektaş, Carlos Lamas-Fernandez, Julian Allen, Marzena Piotrowska, Maja Piecyk, Andrew Oakey
      Abstract: Transportation Research Record, Ahead of Print.
      Parcel logistics in urban areas are characterized by many carriers undertaking similar activity patterns at the same times of day. Using substantial carrier manifest datasets, this paper demonstrates advantages from rival carriers collaborating using a “carrier’s carrier” operating model for their last-mile parcel logistics operations. Under these circumstances, a single carrier undertakes all the deliveries within a defined area on behalf of the carriers instead of them working independently. Modelling the daily delivery activity of five parcel carriers working over a 3.7 km2 area of central London, comprising around 3000 items being delivered to around 900 delivery locations, and consolidating their activity through a single carrier suggested that time, distance and associated vehicle emissions savings of around 60% could be achieved over the current business-as-usual operation. This equated to a reduction in the number of delivery vans and drivers needed from 33 to 13, with annual savings of 39,425 h, 176,324 km driven, 52,721 kg CO2 and 56.4 kg NOx. Reliance on vans and associated vehicle emissions could be reduced further by using cargo cycles alongside vans for the last-mile delivery, with estimated annual emissions savings increasing to 72,572 kg CO2 and 77.7 kg NOx. The results indicated that consolidation of items for delivery in this way would be especially beneficial to business-to-consumer (B2C) carriers whose parcel profiles comprise relatively small and light items. One of the key barriers to the wider take up of such services by individual carriers is the loss of individual brand identity that can result from operating through a carrier’s carrier.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T05:52:44Z
      DOI: 10.1177/0361198120920636
       
  • Estimating Baseline Numbers for Safety Measure Target Setting in Virginia
    • Authors: Scott Himes, Vikash Gayah, Jeff Gooch, Stephen Read
      Abstract: Transportation Research Record, Ahead of Print.
      The Federal Highway Administration (FHWA) established the Safety Performance Management program (Safety PM) to support the Highway Safety Improvement Program. The Safety PM Final Rule requires state departments of transportation (DOTs) to establish and report safety targets annually. FHWA does not identify a specific methodology to use when establishing safety targets. Many state DOTs apply annual growth/decline factors to previous-year safety measures. However, state DOTs also have flexibility to use a data-driven process. The Virginia Department of Transportation (VDOT) recently pursued the development of a more robust data-driven safety target setting methodology. This paper presents a methodology for establishing safety target baselines for several measures, including (1) fatalities, (2) serious injuries, and (3) nonmotorized fatalities and serious injuries. Predictive models were developed for establishing a baseline for 2019 targets and were further refined for 2020 targets. The predictive models include macro-level inputs and were developed for monthly, VDOT district-level outcomes. Performance measure data from 2018 were withheld from models for validation purposes and 2018–2020 model inputs were forecasted based on recent data. As 2019 data become available, the models should incorporate newer data and new models should be developed for revised 2020 and beyond predictions, as necessary. Refined models should include additional data elements as predictors, include more years of data to increase sample size, and capture moments when unobserved annual factors (i.e., unobserved underlying macro-level trends) begin to change.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T05:51:12Z
      DOI: 10.1177/0361198120920632
       
  • Estimation of the Effect of Rain and Incidents on Freeway Capacity and
           Free-Flow Speed
    • Authors: Abdulmajeed Alsharari, Mohamadamin Asgharzadeh, Alexandra Kondyli
      Abstract: Transportation Research Record, Ahead of Print.
      This research aims to examine the effect of incidents with lane closures and adverse weather conditions (medium to heavy rain intensity) on capacity and free-flow speed (FFS) of freeway segments. Data were collected from multiple freeway segments located in the Kansas City, U.S., metro area from 2014 to 2018. The capacity and FFS were measured for two-lane, three-lane, and four-lane freeways under four conditions: () base conditions, () adverse weather only, () incidents only, and () adverse-weather-and-incidents. Capacity adjustment factors (CAF), and speed adjustment factors (SAF) were established to identify the remaining capacity or the FFS reduction during an incident or adverse weather conditions. The findings indicated that medium to heavy rain resulted in a 5% reduction in FFS at three-lane sites which is consistent with the adjustment factors shown in the Highway Capacity Manual 6th edition (HCM6); however, rain was not found to have a significant impact on freeway capacity. It was also found that incidents leading to one-lane closures reduced capacities by 30%, 17%, and 17% at two-lane, three-lane, and four-lane sites, respectively. Incidents were also found to reduce FFS by approximately 5%–10%, possibly because of “rubbernecking.” Adjustment factors that capture the combined effect of incidents and rain on FFS and capacity are also presented.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T02:17:11Z
      DOI: 10.1177/0361198120926500
       
  • Impact of Cognitive Distractions on Drivers’ Hazardous Event
           Anticipation and Mitigation Behavior in Vehicle–Bicycle Conflict
           Situations
    • Authors: Yalda Ebadi, Ganesh Pai, Siby Samuel, Donald L. Fisher
      Abstract: Transportation Research Record, Ahead of Print.
      Vehicle–bicycle collisions are increasing alarmingly. A recent study shows that cognitively distracted drivers who are glancing on the forward roadway are also less likely to glance toward areas for potential vehicle–bicyclist conflicts. But this study did not determine whether cognitively distracted drivers who did glance toward the appropriate area were as likely to process the information as drivers who were not cognitively distracted. Evidence that drivers who were cognitively distracted and glanced toward the bicyclist were not as likely to process the information could be inferred either from shorter fixations in the area where a bicyclist could appear or from smaller reductions in the speed of their vehicle to mitigate a potential conflict. This study intends to add to previous results by examining only glance and vehicle behaviors of participants who glance toward the latent hazardous events involving bicyclists. Specifically, the durations of the glances toward the latent hazardous events of participants who are and are not cognitively distracted are compared as well as their velocity while approaching the potential strike zones. Two groups of 20 participants (one distracted, one not distracted) each drove through seven scenarios on a fixed-based driving simulator while their eye movements were continuously tracked using an eye tracker. Analysis of the participants’ longest glance duration toward the latent hazardous events indicated that distracted drivers made shorter glances toward the latent hazardous events when compared with their non-distracted counterparts. However, there was no difference in vehicle velocity between distracted and non-distracted drivers near the potential strike zones.
      Citation: Transportation Research Record
      PubDate: 2020-06-02T10:55:27Z
      DOI: 10.1177/0361198120923660
       
  • Fracture Properties and Restrained Shrinkage Cracking Resistance of Cement
           Mortar Reinforced by Recycled Steel Fiber from Scrap Tires
    • Authors: Xijun Shi, Leonardo Brescia-Norambuena, Zachary Grasley, Joshua Hogancamp
      Abstract: Transportation Research Record, Ahead of Print.
      Thanks to better processing technology, quality recycled steel fiber (RSF) is routinely extracted from scrap tires, offering opportunities to reinforce cementitious materials in a more economical and sustainable manner. In this study, a detailed experimental program on cement mortar reinforced by up to 2 vol. % RSF was carried out. The work involved conventional tests to characterize cement mortar mechanical properties including compressive strength, elastic modulus, and splitting tensile strength. It also featured an innovative semi-circular bending (SCB) fracture test to characterize fracture-related properties, and a customized ring test to study the cracking resistance under restrained drying shrinkage of the studied mortars. The combined use of the fracture and ring tests is believed to lead to a better assessment of concrete structure behaviors in the field. Based on the test results, the addition of up to 2% RSF shows noticeable improvement on the splitting tensile strength, but it has marginal effects on the cement mortar compressive strength and elastic modulus. The improved fracture properties of the cement mortar reinforced by 2% RSF from the SCB fracture test demonstrate that the RSF-reinforced mortar not only has a better resistance to the initiation of major cracks but also exhibits an enhanced post-cracking performance. Based on the ring test results, the longer cracking time and higher residual strain level of the 2% RSF mortar samples clearly reveal that the RSF could effectively delay and bridge cracks.
      Citation: Transportation Research Record
      PubDate: 2020-06-02T10:55:27Z
      DOI: 10.1177/0361198120924407
       
  • Vulnerability Assessment of Urban Intersections apropos of Incident Impact
           on Road Network and Identification of Critical Intersections
    • Authors: Kaniska Ghosh, Bhargab Maitra
      Abstract: Transportation Research Record, Ahead of Print.
      One of the major challenges in a transportation network management program is responding to traffic incidents such as traffic crashes, disabled vehicles, spilled cargo, road debris, and so forth, at or near intersections. Intersections are vulnerable with respect to their susceptibility to incidents, therefore, it is important to assess their vulnerability to identify critical intersections for preparing traffic incident management strategies. In the present work, vulnerability of an intersection was measured in relation to the incident impact on surrounding road network using average aggregate network delay. Taking the case study of an urban arterial road network in Kolkata city, a methodology was demonstrated to assess the vulnerability of intersections using traffic microsimulation during peak and off-peak periods. A traffic microsimulation model was developed for this purpose and different incident scenarios were simulated to assess the vulnerability of various intersections. The intersections were then ranked in order of their vulnerability. Some key factors governing vulnerability of intersections were identified and an expert opinion survey was also conducted to assess the location-specific relevance of those factors for both peak and off-peak hour conditions using fuzzy analysis. Based on the analysis of expert opinion data, intersections were also ranked as per their vulnerability for comparative purposes. The rankings of intersections as obtained from traffic microsimulation and expert opinion analyses were found to be in agreement in the present context. However, traffic microsimulation as an approach is preferred over expert opinion because of its inherent strengths for vulnerability assessment and identification of critical intersections.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:26:14Z
      DOI: 10.1177/0361198120919400
       
  • Monte Carlo Tree Search-Based Mixed Traffic Flow Control Algorithm for
           Arterial Intersections
    • Authors: Yanqiu Cheng, Xianbiao Hu, Qing Tang, Hongsheng Qi, Hong Yang
      Abstract: Transportation Research Record, Ahead of Print.
      A model-free approach is presented, based on the Monte Carlo tree search (MCTS) algorithm, for the control of mixed traffic flow of human-driven vehicles (HDV) and connected and autonomous vehicles (CAV), named MCTS-MTF, on a one-lane roadway with signalized intersection control. Previous research has often simplified the problem with certain assumptions to reduce computational burden, such as dividing a vehicle trajectory into several segments with constant speed or linear acceleration/deceleration, which was rather unrealistic. This study departs from the existing research in that minimum constraints on CAV trajectory control were required, as long as the basic rules such as safety considerations and vehicular performance limits were followed. Modeling efforts were made to improve the algorithm solution quality and the run time efficiency over the naïve MCTS algorithm. This was achieved by an exploration-exploitation balance calibration module, and a tree expansion determination module to expand the tree more effectively along the desired direction. Results of a case study found that the proposed algorithm was able to achieve a travel time saving of 3.5% and a fuel consumption saving of 6.5%. It was also demonstrated to run at eight times the speed of a naïve MCTS model, suggesting a promising potential for real-time or near real-time applications.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:24:54Z
      DOI: 10.1177/0361198120919746
       
  • Insights from Integrated Geo-Location Data for Pedestrian Crashes,
           Demographics, and Land Uses
    • Authors: Rui Guo, Zhiqiang Wu, Yu Zhang, Pei-Sung Lin, Zhenyu Wang
      Abstract: Transportation Research Record, Ahead of Print.
      This study investigates the effects of demographics and land uses on pedestrian crash frequency by integrating the contextual geo-location data. To address the issue of heterogeneity, three negative binomial models (with fixed parameters, with observed heterogeneity, and with both observed and unobserved heterogeneities) were examined. The best fit with the data was obtained by explicitly incorporating the observed and unobserved heterogeneity into the model. This highlights the need to accommodate both observed heterogeneity across neighborhood characteristics and unobserved heterogeneity in pedestrian crash frequency modeling. The marginal effect results imply that some land-use types (e.g., discount department stores and fast-food restaurants) could be candidate locations for the education campaigns to improve pedestrian safety. The observed heterogeneity of the area indicator suggests that priority should be given to more populated low-income areas for pedestrian safety, but attention is also needed for the higher-income areas with larger densities of bus stops and hotels. Moreover, three normally distributed random parameters (proportion of older adults, proportion of lower-speed roads, and density of convenience stores in the area) were identified as having random effects on the probability of pedestrian crash occurrences. Finally, the identification of pedestrian crash hot zone provides practitioners with prioritized neighborhoods (e.g., a list of areas) for developing effective pedestrian safety countermeasures.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:23:34Z
      DOI: 10.1177/0361198120920267
       
  • Before–After Evaluation of Left-Turn Lane Extension Considering Injury
           Severity and Collision Type
    • Authors: Yanyong Guo, Tarek Sayed
      Abstract: Transportation Research Record, Ahead of Print.
      Left-turn lanes are commonly used to provide space to accommodate vehicle deceleration and provide adequate storage of turning vehicles. The objective of this study is to evaluate the safety effectiveness of extending the length of left-turn lanes at signalized intersection approaches. Five years of collision data including injury severity and collision type from three treatment sites and 31 comparison sites in the City of Surrey, Canada were used in the study. The analysis focused on target crashes including left-turn-related rear-end and left-turn-related sideswipe collisions. A full Bayesian (FB) before–after analysis was conducted for all collisions, severity levels, and collision types. Multivariate Poisson–lognormal linear intervention models were used for the analysis. The treatment effectiveness index was calculated to quantitatively measure the effectiveness of the safety treatment. The FB before–after results showed that the treatment-related collisions were reduced by 57.4% following the implementation of extended left-turn lane. The reduction in injuries and fatalities collisions (63.8%) was greater than that in property damage only collisions (55.7%). The decrease in rear-end collisions (62.8%) was greater than that in sideswipe collisions (58.1%). The findings indicate a remarkable improvement in safety after the length extension of the left-turn lane.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:20:37Z
      DOI: 10.1177/0361198120920270
       
  • Comparison between a Linear Regression and an Artificial Neural Network
           Model to Detect and Localize Damage in the Powder Mill Bridge
    • Authors: Kathryn Kaspar, Erin Santini-Bell, Marek Petrik, Masoud Sanayei
      Abstract: Transportation Research Record, Ahead of Print.
      This paper evaluates the ability of two different data-driven models to detect and localize simulated structural damage in an in-service bridge for long-term structural health monitoring (SHM). Strain gauge data collected over 4 years is used to characterize the undamaged state of the bridge. The Powder Mill Bridge in Barre, Massachusetts, U.S., which has been instrumented with strain gauges since its opening in 2009, is used as a case study, and the strain gauges used in this study are located at 26 different stations throughout the bridge superstructure. A linear regression (LR) model and an artificial neural network (ANN) model are evaluated based on the following criteria: (a) the ability to accurately predict the strain at each location in the undamaged state of the bridge; (b) the ability to detect simulated structural damage to the bridge superstructure; and (c) the ability to localize simulated structural damage. Both the LR and the ANN models were able to predict the strain at the 26 stations with an average error of less than 5%, indicating that both methodologies were effective in characterizing the undamaged state of the bridge. A calibrated finite element model was then used to simulate damage to the Powder Mill Bridge for three damage scenarios: fascia girder corrosion, girder fracture, and deck delamination. The LR model proved to be just as effective as the ANN model at detecting and localizing damage. A recommended protocol is thus presented for integrating data-driven models into bridge asset management systems.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:04:41Z
      DOI: 10.1177/0361198120920631
       
  • Temporal Analysis of Predictors of Pedestrian Crashes
    • Authors: Erick Guerra, Xiaoxia Dong, Lufeng Lin, Yue Guo
      Abstract: Transportation Research Record, Ahead of Print.
      This study investigates the relationship between pedestrian crashes and various socio-demographic, built environment, traffic exposure, and roadway characteristics across different times of day for both weekdays and weekends. Using the street segment as the unit of analysis, multilevel generalized linear mixed models with negative binomial estimators are applied to examine predictors of pedestrian crashes, including those resulting in severe injuries and fatalities, that occurred in Philadelphia, U.S., between 2010 and 2017. It is found that most of the relationships between the predictor variables and pedestrian crashes are consistent throughout the day for both weekdays and weekends. Although traffic volumes and pedestrian trips fluctuate throughout the day, average daily measures of traffic and pedestrian exposure have consistent relationships with pedestrian crashes throughout the day for both weekdays and weekends. Certain roadway characteristics, such as the amount of secondary highways and major arterials, have stronger relationships with pedestrian crashes than others at certain times of day. Results indicate that authorities should pay particular attention to pedestrian safety at night, as well as in lower-income neighborhoods throughout the day when designing interventions to improve the walking environment. Modeling pedestrian crashes by time of day provides additional information that might not be captured by temporally aggregate analyses. Scholars should consider incorporating time of day into future traffic crash analyses.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:03:29Z
      DOI: 10.1177/0361198120920633
       
  • Dynamic Origin–Destination Matrix Prediction with Line Graph Neural
           Networks and Kalman Filter
    • Authors: Xi Xiong, Kaan Ozbay, Li Jin, Chen Feng
      Abstract: Transportation Research Record, Ahead of Print.
      Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of prediction of dynamic origin–destination (O-D) demand matrices is that demand cannot be directly measured by traffic sensors; instead, it has to be inferred from aggregate traffic flow data on traffic links. Specifically, spatial correlation, congestion and time dependent factors need to be considered in general transportation networks. This paper proposes a novel O-D prediction framework combining heterogeneous prediction in graph neural networks and Kalman filter to recognize spatial and temporal patterns simultaneously. The underlying road network topology is converted into a corresponding line graph in the newly designed fusion line graph convolutional networks (FL-GCNs), which provide a general framework of predicting spatial-temporal O-D flows from link information. Data from the New Jersey Turnpike network are used to evaluate the proposed model. The results show that the proposed approach yields the best performance under various prediction scenarios. In addition, the advantage of combining deep neural networks and Kalman filter is demonstrated.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T03:25:58Z
      DOI: 10.1177/0361198120919399
       
  • System-Level Reliability Analysis of Cooperative Driving with V2X
           Communication for Intersection Collision Avoidance
    • Authors: Zhizhou Wu, Xin Zeng, Haochun Yang
      Abstract: Transportation Research Record, Ahead of Print.
      Cooperative driving with vehicle-to-everything (V2X) communication is a promising technique to improve traffic safety and efficiency. Intersection collision avoidance (ICA) is a typical safety application of it. This paper analyzes reliability of ICA with cooperative manual driving at the system level. First, the reliability of an ICA system is defined as the probability of the ICA system avoiding collisions or near-misses at intersections without failure under conditions that collisions or near-misses are about to happen. Post-encroachment time is used in the expression of this definition. Then, components of the ICA system are classified into four types: hardware, software, maneuver, and V2X communication, and a reliability block diagram (RBD) is applied to reveal how these components contribute to system reliability. Five ICA system patterns with different V2X communication modes and strategy types are compared based on RBD analysis. This shows that centralized strategies are more reliable than decentralized ones for V2I communication if software reliability of these two strategies is the same. Furthermore, reliabilities of ICA components are analyzed in detail, and they are classified into two categories based on their different impact modes on the system. Finally, a numerical example shows how to test reliability of an ICA system using reliabilities of its components by Monte Carlo simulation. Results show that closer distances from vehicles to their conflict point when alerted, longer driver reaction time, and smaller vehicle deceleration rates are more likely to lead to system failure, whereas communication latency has little effect on it.
      Citation: Transportation Research Record
      PubDate: 2020-05-27T10:42:19Z
      DOI: 10.1177/0361198120919756
       
  • Influence of Rain on Highway Breakdown Probability
    • Authors: Douglas Zechin, Felipe Caleffi, Helena Beatriz Bettella Cybis
      Abstract: Transportation Research Record, Ahead of Print.
      Capacity has been used to describe a deterministic value that represents the maximum volume of traffic supported by a road. Studies have pointed out the importance of not using a single value for capacity, but rather the concept of probability of occurrence of a traffic-flow breakdown. In this paper the probabilities of breakdown for a Brazilian highway under different weather conditions are compared. Data collected from inductive loop detectors and pluviometric data from automatic rain gauges are combined. Two methodologies of breakdown identification are then compared. The most consistent methodology for identifying breakdowns is used to generate breakdown probability distributions using the product limit and maximum-likelihood methods with the Weibull distribution. The results indicate significant differences in probability of breakdown for each studied climatic condition, including a maximum difference greater than 50% between dry and heavy rain conditions under the same traffic flow.
      Citation: Transportation Research Record
      PubDate: 2020-05-27T10:40:19Z
      DOI: 10.1177/0361198120919754
       
  • Preparation and Properties of Engineered Cementitious Composites
           Incorporating a High Volume of Fly Ash
    • Authors: Shuyin Wu, Jun Yang, Ruochong Yang, Jipeng Zhu
      Abstract: Transportation Research Record, Ahead of Print.
      As a type of fiber-reinforced composite, engineered cementitious composite (ECC) has the characteristics of multi-cracking and strain-hardening. In this study, domestic materials were used to prepare ECC incorporating a high volume of fly ash. The effect of fly ash on the microscopic and macroscopic performance was studied, and the relationship between the microscopic structure and macroscopic performance was also analyzed. The microscopic pore structure was analyzed by mercury intrusion porosimetry (MIP) with the aim of improving understanding of the variability in ductility. The results obtained show that mesopores and macropores (pores with a diameter greater than 20 nm) have a great influence on the fracture toughness and strength of the matrix, while micropores (diameter less than 20 nm) had no obvious effect on the fracture toughness and strength of the matrix. The fracture toughness and strength of the matrix are negatively correlated with the total porosity. Microscopic analysis showed that high-volume fly ash is conducive to the ductility of ECC and the macroscopic experiments verify this finding from the microscopic analysis.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:28:24Z
      DOI: 10.1177/0361198120919406
       
  • Asphalt Mixture Quality Acceptance using the Hamburg Wheel-Tracking Test
    • Authors: Dario Batioja-Alvarez, Jusang Lee, Reyhaneh Rahbar-Rastegar, John E. Haddock
      Abstract: Transportation Research Record, Ahead of Print.
      This paper investigates the applicability of the Hamburg wheel-tracking test (HWTT) for asphalt mixture quality acceptance using laboratory-compacted specimens and field-compacted specimens. Density distribution functions for rut depths, stripping inflection points, and rutting resistance index (RRI) values used in the HWTT were obtained for mixtures with different nominal maximum aggregate size (NMAS) values and binder performance grades. Clear distinctions among the rut depth distributions for the high-temperature performance grade mixtures were observed in the laboratory-compacted specimens. The RRI values for both the laboratory and field-compacted specimens increased with an increase in the binder performance grade. In addition, the RRI values showed clear differences for different binder grades among the mixtures with the same NMAS. The range of the RRI distributions for the laboratory-compacted specimens was narrower than that of the field-compacted specimens. The stripping inflection points of the field-compacted specimens increased as the binder grade was increased, indicating better moisture damage resistance for stiffer mixtures. HWTT results were significantly influenced by the air voids content of specimens. The relationship between air voids content and RRI can be used for understanding the critical effect of in-place density in pavement performance. The laboratory-compacted and field-compacted specimens offer advantages and disadvantages. The laboratory-compacted specimens were much easier to fabricate to standard dimensions, and the field-compacted specimens present inherent variability in relation to air voids content, diameter, and thickness.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:19:36Z
      DOI: 10.1177/0361198120919749
       
  • Driveway Access Spacing Considerations for Rural Highways with High Truck
           Volumes
    • Authors: Marcus A. Brewer, Kay Fitzpatrick, James C. Cline
      Abstract: Transportation Research Record, Ahead of Print.
      Increased traffic and heavy truck percentages associated with energy exploration in West Texas have placed unprecedented demands on the region’s highway network as well as driveway access to and from that network. Access management principles have proven to be effective in improving operations and safety in numerous locations, but many of those locations have been in urban or suburban locations where land uses and traffic patterns are different from those typically found in rural West Texas, so guidelines for driveway spacing and other access management treatments in rural, high-speed areas are not as commonplace. This paper describes the study of a corridor with high volumes, high truck percentages, high speeds, high turning volumes, and high demand for access. The study team reviewed the applicable guidelines and policies for driveway spacing in Texas, as well as relevant findings from other guidelines and research, to develop a set of recommended driveway spacing values for cars and for trucks on high-speed rural roads.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:15:14Z
      DOI: 10.1177/0361198120919757
       
  • Weigh-in-Motion-Based Fatigue Damage Assessment
    • Authors: Olga Iatsko, Anjan Ramesh Babu, J. Michael Stallings, Andrzej S. Nowak
      Abstract: Transportation Research Record, Ahead of Print.
      Weigh-in-motion (WIM) data provide an excellent opportunity to study the effects of actual traffic loads on bridges. Here procedures are presented for using WIM data to quantify the fatigue damage accumulated in steel bridges. These procedures allow comparisons of the impacts of truck traffic on various routes beyond simple comparisons of the numbers and gross vehicles weights of trucks in the traffic streams. The fatigue damage accumulation procedures are demonstrated using WIM traffic data collected in the state of Alabama. The results of the analysis show that approximately 20% of trucks are overloaded, that is, permit loads and illegal loads, and those trucks create more than 50% of the total damage based on the combined data from all the WIM locations in the state. The contribution of overloaded trucks to the total fatigue damage varies so that their contribution is less significant along some routes. A typical steel bridge with bottom flange coverplates was evaluated using the WIM data from 1 year for a heavily traveled route. This analysis shows that the fatigue life of the bridge was consumed at an annual rate consistent with a mean life of 100 years. These procedures have applications in planning weight limit enforcement, budgeting, and maintenance, and they have the potential for future use in planning inspection intervals.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:14:04Z
      DOI: 10.1177/0361198120919758
       
  • Understanding Why Drivers Cross the Line at Activated Railway Crossings
    • Authors: Grégoire S. Larue, Anjum Naweed
      Abstract: Transportation Research Record, Ahead of Print.
      Congestion at urban and active railway level crossings leads to non-compliant driver behavior, and scenarios in which road users may enter into the rail corridor with the crossing nearing full closure. Previous research indicates this scenario occurs with alarming regularity during peak periods. However, limited research has investigated whether such non-compliance arises from errors or from deliberate decisions. The objective of this study was to better understand driver decisions when approaching a level crossing during activation. Vehicle movements and crossing activation were continuously recorded for 2 months at a congested active level crossing close to Melbourne, Australia. Each movement corresponding to a vehicle approach to the level crossing during onset of activation was extracted with traversals counted, and the ability to stop safely modeled with linear motion equations, using the position and speed of the vehicle at activation. The probability of entering the level crossing was then modeled with generalized linear models. Analysis revealed that much of the non-compliance was involuntary and linked to a dilemma zone in the absence of sufficient warning time for drivers to react to and safely stop before proceeding through the crossing. However, deliberate non-compliance was also an issue, and independent of the time of day. Findings are discussed in relation to the ideal grace period for road users at such crossings, and consideration is given to enforcement as a viable treatment for reducing deliberate non-compliance.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T05:04:23Z
      DOI: 10.1177/0361198120912238
       
  • Upgrading the FHWA Work Zone Model Version 2.0 and Validating Its
           Performance along I-91 in Springfield, Massachusetts
    • Authors: Andrew Berthaume, Ian Berg, Rebecca Kiriazes, Brian O’Donnell, Stephen Zitzow-Childs, Tema Nwana
      Abstract: Transportation Research Record, Ahead of Print.
      Freeway work zones can have significant safety and operational impacts. To mitigate these, planners and engineers rely on accurate simulation tools to assess various work zone design and scheduling alternatives. Microsimulation models are often used to predict traffic conditions along freeways, however, they were not created to replicate car-following through work zones and therefore cannot be used to accurately predict work zone impacts. So that practitioners can use microsimulation to better predict work zone impacts, FHWA created the Work Zone Driver Model v1.0 (FHWA v1.0) software that overrides car-following in commercial microsimulation software packages for work zone segments. FHWA v1.0 was tested in a 2017 case study. Results showed acceptable performance, however, there were opportunities to improve the software’s usability and accuracy. Findings were used to upgrade the software and create the FHWA Work Zone Driver Model v2.0 (FHWA v2.0). This paper demonstrates the enhanced capabilities of FHWA v2.0 by interfacing with VISSIM and recreating the 2017 case study, testing its performance along the same interstate work zone in Springfield, MA. FHWA v2.0’s performance was compared with field data, with Wiedemann 99 (W99), and with FHWA v1.0. Performance metrics were selected to align with state departments of transportation (DOTs) work zone management efforts. Results show improved performance from FHWA v2.0 as it predicted queue lengths, queue locations, and travel speeds more accurately than FHWA v1.0 and W99. The enhanced software also addressed some of the variability and merging issues described in the 2017 case study. Next steps are described.
      Citation: Transportation Research Record
      PubDate: 2020-05-22T11:09:49Z
      DOI: 10.1177/0361198118821900
       
  • Meaningful Modeling of Section Bus Running Times by Time Varying Mixture
           Distributions of Fixed Components
    • Authors: Beda Büchel, Francesco Corman
      Abstract: Transportation Research Record, Ahead of Print.
      Understanding the variability of bus travel time is a key issue in the optimization of schedules, transit reliability, route choice analysis, and transit simulation. The statistical modeling of bus travel time data is of increasing importance given the increasing availability of data.In this paper, we introduce a novel approach to modeling the day-to-day variability of urban bus running times on a section level. First, the explanatory power of conventionally used distributions is examined, based on likelihood and effect size. We show that a mixture model is a powerful tool to increase fitting performance, but the applied components need to be justified. To overcome this issue, we propose a novel model consisting of two individual characteristic distributions representing either off-peak or peak hour dynamics. The observed running time distribution at every hour of the day can be described as a combination (mixture) of the two dynamics. The proposed time varying model uses a small set of parameters, which are physically interpretable and capable of accurately describing running time distributions. With our modeling approach, we reduce the complexity of mixture models and increase the explanatory power and fit compared with conventional models.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:22:35Z
      DOI: 10.1177/0361198120918576
       
  • Exploratory Analysis of Real-Time E-Scooter Trip Data in Washington, D.C.
    • Authors: Zhenpeng Zou, Hannah Younes, Sevgi Erdoğan, Jiahui Wu
      Abstract: Transportation Research Record, Ahead of Print.
      The proliferation of micromobility, evolving from station-based to dockless bikeshare programs, has dramatically accelerated since 2017 with an influx of investment from the private sector to a new product, dockless e-scooter share. As an alternative to pedal bikes, e-scooters have become widespread across the U.S.A. owing to the unprecedented convenience they bring to commuters and travelers with electric-power propulsion and freedom from docking stations. In cities like Washington, D.C., e-scooter share can play an important role to support transportation sustainability and boost accessibility in less-connected communities. This study takes advantage of publicly available but not readily accessible e-scooter share data in Washington, D.C. for an initial view of the travel patterns and behaviors related to this new mode. The study adopted an innovative approach to scrape and process general bikeshare feed specification data in real time for e-scooters. Not only locational time series data, but also e-scooter share trip trajectories were generated. The trip trajectory data provide a unique opportunity to examine travel patterns at the street link level—a level of analysis that has not been reached before for e-scooter share to the authors’ knowledge. The paper first provides descriptive statistics on e-scooter share trips, followed by an exploratory analysis of trip trajectories conjoined with street link level features. Important insights on e-scooter route choice are derived. Lastly, policy and regulatory implications in relation to e-scooter facility design and safety risks are discussed.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T06:55:35Z
      DOI: 10.1177/0361198120919760
       
  • Statistics and Artificial Intelligence-Based Pavement Performance and
           Remaining Service Life Prediction Models for Flexible and Composite
           Pavement Systems
    • Authors: Orhan Kaya, Halil Ceylan, Sunghwan Kim, Danny Waid, Brian P. Moore
      Abstract: Transportation Research Record, Ahead of Print.
      In their pavement management decision-making processes, U.S. state highway agencies are required to develop performance-based approaches by the Moving Ahead for Progress in the 21st Century (MAP-21) federal transportation legislation. One of the performance-based approaches to facilitate pavement management decision-making processes is the use of remaining service life (RSL) models. In this study, a detailed step-by-step methodology for the development of pavement performance and RSL prediction models for flexible and composite (asphalt concrete [AC] over jointed plain concrete pavement [JPCP]) pavement systems in Iowa is described. To develop such RSL models, pavement performance models based on statistics and artificial intelligence (AI) techniques were initially developed. While statistically defined pavement performance models were found to be accurate in predicting pavement performance at project level, AI-based pavement performance models were found to be successful in predicting pavement performance in network level analysis. Network level pavement performance models using both statistics and AI-based approaches were also developed to evaluate the relative success of these two models for network level pavement performance modeling. As part of this study, in the development of pavement RSL prediction models, automation tools for future pavement performance predictions were developed and used along with the threshold limits for various pavement performance indicators specified by the Federal Highway Administration. These RSL models will help engineers in decision-making processes at both network and project levels and for different types of pavement management business decisions.
      Citation: Transportation Research Record
      PubDate: 2020-05-08T03:25:14Z
      DOI: 10.1177/0361198120915889
       
  • Analytical and Agent-Based Model to Evaluate Ride-Pooling Impact Factors
    • Authors: Aledia Bilali, Roman Engelhardt, Florian Dandl, Ulrich Fastenrath, Klaus Bogenberger
      First page: 1
      Abstract: Transportation Research Record, Ahead of Print.
      On-demand ride-pooling (ODRP) services have the potential to improve traffic conditions in cities and at the same time offer user-centric mobility services. Recently, an analytical model, which investigates the influence of service quality parameters, such as detour, maximum waiting time, and boarding time, on the fraction of trips which could potentially be shared (a quantity called shareability), has been presented. The aim of this study is to test this model with a simulation framework that models an ODRP service in different levels of detail. The results show that by increasing the modeling complexity, in which we consider network topology, trip distribution patterns, optimization objectives, and changing velocity, the theoretical value of shareability and the actual experienced shared rides are decreased. It is observed that the shareability predicted by the mathematical model could be confirmed by a certain simulation setup with the objective to maximize shared rides. Nevertheless, changing the optimization objective to optimizing the total kilometers driven has the highest impact on shareability, decreasing it by up to 50%. By using a fitting procedure within this simulation setup, we can still exploit the analytical model to predict the influence of service quality parameters. This study may be useful for other researchers who plan to model ride-pooling systems and for operators who want to have an estimation of the level of shared rides they can achieve in an operating area.
      Citation: Transportation Research Record
      PubDate: 2020-05-09T12:20:59Z
      DOI: 10.1177/0361198120917666
       
  • Exploring a Quantitative and Qualitative Mixed Approach for Estimating
           Preliminary Engineering Efforts of Bridge Replacement Projects
    • Authors: Felipe Araya, Kasey Faust, Nabeel Khwaja, William J. O’Brien, Xiaopeng Liang, Mohamed K. Bur
      First page: 13
      Abstract: Transportation Research Record, Ahead of Print.
      While managing the transportation infrastructure, state transportation agencies (STAs) face multiple challenges. Primary among these are budgetary constraints and understaffing. One task that is impacted by these challenges is that of developing the plans, specifications, and estimates (PS&E) for construction projects. STAs often outsource this job to consultants. The outsourcing itself requires a contract negotiation process, which has historically relied on the work experience of the negotiation parties. PS&E budget development and management relies on an estimate of the engineering man-hours (EMHs). This paper presents a mixed approach to creating that estimate. To identify engineering-related tasks as variables in the estimation of EMHs for the development of PS&E, this approach uses qualitative analysis. The variables identified through qualitative analysis are used to build multiple linear regression models. Data used for this study include project characteristics from the Texas Department of Transportation (TxDOT) and the respective work authorizations from 38 bridge replacement (BR) projects. The results revealed that variables identified through the qualitative analysis are statistically significant to estimate the EMHs of BR projects. However, the improvement in such estimation was found to be marginal. By developing a data-driven approach, this study provides an improved process for estimating EMHs for BR projects—an improvement over the commonly used experience-based approach. This incremental step contributes a method STA staff can use to make better-informed decisions during the contract negotiation process undertaken while outsourcing preliminary engineering (PE) work.
      Citation: Transportation Research Record
      PubDate: 2020-05-09T12:19:18Z
      DOI: 10.1177/0361198120917677
       
  • Hurricane Wind and Storm Surge Effects on Coastal Bridges under a Changing
           Climate
    • Authors: Reda Snaiki, Teng Wu, Andrew S. Whittaker, Joseph F. Atkinson
      First page: 23
      Abstract: Transportation Research Record, Ahead of Print.
      Hurricanes and their cascading hazards have been responsible for widespread damage to life and property, and are the largest contributor to insured annual losses in coastal areas of the U.S.A. Such losses are expected to increase because of changing climate and growing coastal population density. An effective methodology to assess hurricane wind and surge hazard risks to coastal bridges under changing climate conditions is proposed. The influence of climate change scenarios on hurricane intensity and frequency is explored. A framework that couples the hurricane tracking model (consisting of genesis, track, and intensity) with a height-resolving analytical wind model and a newly developed machine learning-based surge model is used for risk assessment. The proposed methodology is applied to a coastal bridge to obtain its traffic closure rate resulting from the observed (historical) and future (projected) hurricane winds and storm surges, demonstrating the effects of changing climate on the civil infrastructure in a hurricane-prone region.
      Citation: Transportation Research Record
      PubDate: 2020-05-09T12:20:39Z
      DOI: 10.1177/0361198120917671
       
  • Investigating the Practices, Problems, and Policies for Port Sea–Rail
           Intermodal Transport in China
    • Authors: Jiawei Ge, Xuefeng Wang, Wenming Shi, Zheng Wan
      First page: 33
      Abstract: Transportation Research Record, Ahead of Print.
      Intermodalism is currently a mainstream mode of international transport because of its operational efficiency and cost-effectiveness compared with unimodal transport. In 2011, the Chinese government launched port sea–rail intermodal transport (PIT) projects to promote and facilitate its transport system. As a result, seaports are now ruling the waves of sea–rail intermodal transport in China. However, barriers have occurred in many parts of the system from transport sectors to government departments, challenging the accessibility, connectivity, and accountability of the intermodal system. This paper investigates the various parties that are involved in PIT, and aims to outline its development, including its present status, bottlenecks, and other influential elements. Through a questionnaire survey and content analysis, the main problems are identified as lack of institutional design and system regulation, resistance from the rail sector, insufficient cooperation and investment, and a fragmented information system. Policy recommendations are addressed through a three-step administrative framework: (a) unification of international regulations and standards; (b) rail sector reform for better alignment with other transport sectors; (c) incentive policies for enterprises instead of direct subsidies.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:05:15Z
      DOI: 10.1177/0361198120917670
       
  • Learning to Recommend Signal Plans under Incidents with Real-Time Traffic
           Prediction
    • Authors: Weiran Yao, Sean Qian
      First page: 45
      Abstract: Transportation Research Record, Ahead of Print.
      The main question to address in this paper is to recommend optimal signal timing plans in real time under incidents by incorporating domain knowledge developed with the traffic signal timing plans tuned for possible incidents, and learning from historical data of both traffic and implemented signals timing. The effectiveness of traffic incident management is often limited by the late response time and excessive workload of traffic operators. This paper proposes a novel decision-making framework that learns from both data and domain knowledge to real-time recommend contingency signal plans that accommodate non-recurrent traffic, with the outputs from real-time traffic prediction at least 30 min in advance. Specifically, considering the rare occurrences of engagement of contingency signal plans for incidents, it is proposed to decompose the end-to-end recommendation task into two hierarchical models—real-time traffic prediction and plan association. The connections between the two models are learnt through metric learning, which reinforces partial-order preferences observed from historical signal engagement records. The effectiveness of this approach is demonstrated by testing this framework on the traffic network in Cranberry Township, Pennsylvania, U.S., in 2019. Results show that the recommendation system has a precision score of 96.75% and recall of 87.5% on the testing plan, and makes recommendations an average of 22.5 min lead time ahead of Waze alerts. The results suggest that this framework is capable of giving traffic operators a significant time window to access the conditions and respond appropriately.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:03:55Z
      DOI: 10.1177/0361198120917668
       
  • Minimizing Cost of Highway Maintenance Considering the Impact of Vehicle
           Emissions using an Artificial Bee Colony Approach
    • Authors: Celina Semaan, Steven Chien, Ching-Jung Ting
      First page: 60
      Abstract: Transportation Research Record, Ahead of Print.
      The increasing traffic demand has reduced the efficiency of road networks and intensified the maintenance need for mobility and safety, increasing vehicle emissions, reducing air quality, and affecting climate change. To mitigate the negative impacts of work zone activities, a reliable method that can optimize spatio-temporal work zone activities is desirable. Previous studies have aimed to minimize the total cost, including maintenance, user delay, and accident costs, yet the associated environmental impact has been neglected. This study aims to optimize work zone activities using the artificial bee colony (ABC) algorithm, considering the cost of vehicle emissions in addition to the aforementioned costs for an environmentally sustainable optimization. MOtor Vehicle Emission Simulator (MOVES) is applied to calculate emission rates. The results show that the ABC algorithm is very efficient to search for the optimal solution that yields the minimum cost taking into account the well-being of the environment.
      Citation: Transportation Research Record
      PubDate: 2020-05-27T10:34:59Z
      DOI: 10.1177/0361198120917667
       
  • Variability of Reclaimed Asphalt Pavement (RAP) Properties within a State
           and Its Effects on RAP Specifications
    • Authors: Alexander J. Austerman, Walaa S. Mogawer, Kevin D. Stuart
      First page: 73
      Abstract: Transportation Research Record, Ahead of Print.
      Reclaimed Asphalt Pavement (RAP) is a highly recyclable material that provides a source of aggregates and asphalt binder to be re-utilized in new paving mixtures. State transportation agencies in the U.S. have constructed their specifications to allow for the use of RAP in new paving mixtures, but with conditions so that suitably performing mixtures are developed. These conditions are imposed because of concerns that the aged binder contained within the RAP may negatively impact the resultant mixtures performances. Many state transportation agencies have constructed their specifications with respect to the AASHTO guidance on utilizing RAP in Superpave mixtures. Questions remain as to the accuracy of these methods, especially if the RAP stockpiles’ properties vary greatly. The purpose of this study was to characterize and compare the properties of the RAP stockpiles being used throughout Massachusetts and to determine the impacts that these properties have on the currently utilized specifications for RAP. The properties of the RAP stockpiles within Massachusetts varied greatly. No geographical or regionalization of RAP properties could be made. By default, the current specifications for using RAP makes no distinction between RAP stockpile properties, especially at smaller percentages like
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:07:35Z
      DOI: 10.1177/0361198120917679
       
  • Analysis of Component Errors in the Highway Capacity Manual Travel Time
           Reliability Estimations for Urban Streets
    • Authors: Ernest O. A. Tufuor, Laurence R. Rilett
      First page: 85
      Abstract: Transportation Research Record, Ahead of Print.
      The Highway Capacity Manual 6th edition (HCM6) includes a new methodology to estimate and predict the distribution of average travel times (TTD) for urban streets. The TTD can then be used to estimate travel time reliability (TTR) metrics. Previous research on a 0.5-mi testbed showed statistically significant differences between the HCM6 estimated TTD and the corresponding empirical TTD. The difference in average travel time was 4 s that, while statistically significant, is not important from a practical perspective. More importantly, the TTD variance was underestimated by 70%. In other words, the HCM6 results reflected a more reliable testbed than field measurement. This paper expands the analysis on a longer testbed. It identifies the sources and magnitude of travel time variability that contribute to the HCM6 error. Understanding the potential sources of error, and their quantitative values, are the first steps in improving the HCM6 model to better reflect actual conditions. Empirical Bluetooth travel times were collected on a 1.16-mi testbed in Lincoln, Nebraska. The HCM6 methodology was used to model the testbed, and the estimated TTD by source of travel time variability was compared statistically to the corresponding empirical TTD. It was found that the HCM6 underestimated the TTD variability on the longer testbed by 67%. The demand component, missing variable(s), or both, which were not explicitly considered in the HCM6, were found to be the main source of the error in the HCM6 TTD. A focus on the demand estimators as the first step in improving the HCM6 TTR model was recommended.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:27:35Z
      DOI: 10.1177/0361198120917977
       
  • Building Information Modeling Implementation Framework for Smart Airport
           Life Cycle Management
    • Authors: Basak Keskin, Baris Salman
      First page: 98
      Abstract: Transportation Research Record, Ahead of Print.
      Connectivity is key in this new era of smart infrastructure. Smart airports utilize new connected technologies to improve end-user experience while ensuring operational feasibility in aeronautical and non-aeronautical segments. The increasing need for digitizing the design-build-operate life cycles of airports can be met by implementing building information modeling (BIM) that enables accessing, managing, utilizing, and connecting physical and operational data in a digital collaborative environment. This study investigates the current state of practice in airport BIM (ABIM) and the use of ABIM processes in digital airport operations and maintenance by connecting existing data sources and integrating smart airport systems. The study proposes a comprehensive and adaptive ABIM management framework that depicts the alignment and connectivity of ABIM processes, resources and stakeholders with airport operational requirements by identifying gaps in the industry and literature, and developing a global understanding in ABIM visions. Research data are collected through literature and industry review, online surveys, and semi-structured interviews with aviation professionals. Mixed methods including non-parametric statistical analysis and qualitative analysis are used to determine the elements of the framework. Model-based systems engineering (MBSE) principles and language are used to generate the framework. For framework validation, a proof of concept (POC) is conducted by development and deployment of a web-based application. The developed ABIM framework is expected to guide major airport stakeholders in their BIM implementation processes to enhance airport operational efficiencies and in strategizing digital initiatives on a connected-BIM platform.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:15:35Z
      DOI: 10.1177/0361198120917971
       
  • Evaluating the Self-Healing Efficiency of Hydrogel-Encapsulated Bacteria
           in Concrete
    • Authors: Ahsennur Soysal, Jose Milla, Gary M King, Marwa Hassan, Tyson Rupnow
      First page: 113
      Abstract: Transportation Research Record, Ahead of Print.
      Bacterial concrete has become one of the most promising self-healing alternatives owing to its capability to seal crack widths through microbial-induced calcite precipitation (MICP). In this study, two bacterial strains were embedded at varying dosages (by weight of cement) in concrete. Beam specimens were used to quantify the maximum crack-sealing efficiency, whereas cylinder samples were used to determine their effects on the intrinsic mechanical properties of concrete, as well as its stiffness recovery over time after inducing damage. The concrete specimens were cured in wet–dry cycles to enable healing. Results showed that the specimen groups with the highest calcium alginate concentrations (including the control specimens with embedded alginate beads but no bacteria) resulted in the greatest increase in stiffness recovery. Similarly, the beam samples containing alginate beads (also including the Control 3%C specimen group) had superior crack-healing efficiencies to the control samples without alginate beads (Control NC). This was attributed to the alginate beads acting as a reservoir that can further enhance the autogenous healing capability of concrete. Based on the results of this study, further research is recommended to explore factors that can maximize the self-healing mechanism of bacterial concrete through MICP and determine whether an alternative encapsulation mechanism, nutrient selection, curing regime, or bacterial strain is needed.
      Citation: Transportation Research Record
      PubDate: 2020-05-22T11:13:08Z
      DOI: 10.1177/0361198120917973
       
  • Prioritizing Metro Service Quality Attributes to Enhance Commuter
           Experience: TOPSIS Ranking and Importance Satisfaction Analysis Methods
    • Authors: Bandhan Bandhu Majumdar, Dilum Dissanayake, Avanindra Singh Rajput, Yong Qi Saw, Prasanta Kumar Sahu
      First page: 124
      Abstract: Transportation Research Record, Ahead of Print.
      A metro infrastructure, facility, and service quality investigation based on commuter perception was conducted in this study to explore and prioritize the key attributes influencing overall metro service quality in a typical Indian context. Based on the critical state-of-the-art review, 12 key attributes were identified and they were accommodated in a paper-based questionnaire to elicit commuter perception of importance and satisfaction by using a five-point Likert scale. Subsequently, TOPSIS, an extensively adopted multi-attribute decision-making technique, was carried out to rank the attributes with respect to perceived importance and satisfaction. Then an importance satisfaction analysis (ISA) was conducted to further classify the attributes in four quadrants based on their perceived degree of importance and satisfaction using an ISA matrix. Finally, the derived results from the TOPSIS and ISA analysis were combined and compared to obtain a prioritized set of attributes requiring intervention for better metro service quality in an Indian context. Results of this study clearly indicated the relative strengths and weaknesses of each metro service/infrastructure-specific attribute and presented the probable role of metro authorities for each of them. Attributes such as metro fare, connection to metro, and metro frequency were observed to be the most important, but were not performing satisfactorily, indicating that more emphasis is required on these attributes to improve the overall quality of travel by metro rail in an Indian context. Thus, this methodology would be instrumental in detecting a set of priority areas for improvement in metro rail services, which could contribute to retaining existing commuters and attracting new metro users.
      Citation: Transportation Research Record
      PubDate: 2020-05-09T12:18:38Z
      DOI: 10.1177/0361198120917972
       
  • Effect of Temperature and Prewetting for Ice Penetration with Sodium
           Formate
    • Authors: Mateusz Piotr Trzaskos, Alex Klein-Paste
      First page: 140
      Abstract: Transportation Research Record, Ahead of Print.
      Granular sodium formate (NaCOOH) is a popular deicer used at airports. It is mainly used to weaken compacted snow/ice and thereby facilitate mechanical ice removal. Earlier research has developed a set of methods quantifying deicer performance, but linking these test results to operational guidelines is difficult. The main objective of this study is to increase the knowledge of how temperature and prewetting affect the ice penetration performance of granular sodium formate. A new method to evaluate the development of ice penetration process is presented here. Ice penetration tests were performed with single grains on large, optically clear ice cubes, and digital image analysis is used to quantify the initial waiting time, penetration rate and –depth, and melted volume. Eighteen tests including dry and prewetted sodium formate grains were performed at three different temperatures (–2°C, −5°C, and −10°C). Prewetting reduced the initial waiting time (the time it takes before the particles started to penetrate) by a few minutes at −10°C, but at higher temperatures, this reduction was insignificant. The particles penetrated the ice at a constant rate. At −10°C, the particles penetrated at 10–15 mm/hour, while at −2°C this speed is about five times higher. Prewetting does not seem to have a clear beneficial effect on the penetration rate. Suggestions are given on how to capture the results from this study into operational guidelines for deicing operations at airports, using sodium formate as deicer.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:21:15Z
      DOI: 10.1177/0361198120917974
       
  • Characterizing Influence of Water Access Condition during Freezing on
           Resilient Behavior of Alaskan Base Course Materials
    • Authors: Lin Li, Jenny Liu, Xiong Zhang, Steve Saboundjian, Peng Li
      First page: 151
      Abstract: Transportation Research Record, Ahead of Print.
      Accurate characterization of the resilient behavior of the base course materials under different climatic conditions is critical for the design of reliable and cost-effective pavement structures. In Alaska, the resilient behavior of base course materials usually undergoes significant variation due to seasonal change and extreme climatic conditions. Previous studies have revealed that the resilient behavior of base course materials could be significantly influenced by the freezing process. In this study, the freezing process under two extreme conditions (i.e., free and no water access conditions) that base course materials could possibly experience in the field was simulated using a one-dimensional frost heave cell. The influences of the water access condition during freezing on the frost heave and resilient modulus (MR) of the base course materials with different fines and initial water contents was assessed based on the results from the freezing process and repeated load triaxial tests. A pressure plate test was also performed to build the relationship between suction and water content of soils with different fines content. Suction was then introduced to model MR of the materials tested under unfrozen conditions before and after a freeze–thaw cycle. The adoption of suction significantly simplified the equation for MR prediction. Finally, structural analyses were conducted using BISAR and Alaska Flexible Pavement Design (AKFPD) software and the results revealed that free water access during freezing can significantly accelerate cracking and reduce pavement service life.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:13:35Z
      DOI: 10.1177/0361198120918242
       
  • Combining Machine Learning and Fuzzy Rule-Based System in Automating
           Signal Timing Experts’ Decisions during Non-Recurrent Congestion
    • Authors: Mosammat Tahnin Tariq, Aidin Massahi, Rajib Saha, Mohammed Hadi
      First page: 163
      Abstract: Transportation Research Record, Ahead of Print.
      Events such as surges in demand or lane blockages can create queue spillbacks even during off-peak periods, resulting in delays and spillbacks to upstream intersections. To address this issue, some transportation agencies have started implementing processes to change signal timings in real time based on traffic signal engineers’ observations of incident and traffic conditions at the intersections upstream and downstream of the congested locations. Decisions to change the signal timing are governed by many factors, such as queue length, conditions of the main and side streets, potential of traffic spilling back to upstream intersections, the importance of upstream cross streets, and the potential of the queue backing up to a freeway ramp. This paper investigates and assesses automating the process of updating the signal timing plans during non-recurrent conditions by capturing the history of the responses of the traffic signal engineers to non-recurrent conditions and utilizing this experience to train a machine learning model. A combination of recursive partitioning and regression decision tree (RPART) and fuzzy rule-based system (FRBS) is utilized in this study to deal with the vagueness and uncertainty of human decisions. Comparing the decisions made based on the resulting fuzzy rules from applying the methodology with previously recorded expert decisions for a project case study indicates accurate recommendations for shifts in the green phases of traffic signals. The simulation results indicate that changing the green times based on the output of the fuzzy rules decreased delays caused by lane blockages or demand surge.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:25:15Z
      DOI: 10.1177/0361198120918248
       
  • Joint Choice Model for Airport Passengers’ Travel Mode and Departure
           Time Based on Agent Theory
    • Authors: Danwen Bao, Tianxuan Zhang, Shijia Tian, Zhiwei Di
      First page: 177
      Abstract: Transportation Research Record, Ahead of Print.
      Numerous strategies have been proposed to modify and transform passengers’ travel mode and departure time with the purpose of mitigating landside traffic pressure of airports. A core solution to tackle this problem is to build a travel behavior model so that pertinent predictions about the extent to which passengers shift their patterns of travel can hopefully be obtained. This paper aims at studying the passengers’ behaviors with respect to the travel mode and departure time based on agent theory. What distinguishes this model from traditional utility maximization theory is that it specifically places emphasis on the decision-making process with imperfect information and bounded rationality. Passengers continuously renew their knowledge of time management and their surrounding environment in the duration of the Bayesian learning process. It is evident that decisions about whether to substitute their current travel mode and departure time will be given thoughtful consideration before traveling, in relation to their presumptive gain and cost for searching. When performing additional searches, passengers tend to depend on a range of decision-making conditions to determine the necessity of converting to a new travel pattern. The process of both searching and deciding can be indicated by production (if–then) rules. These rules basically stem from the data gathered from Nanjing Lukou International Airport (NKG). Furthermore, this paper studies and discusses to what extent passengers will change their travel behaviors under variable costs of public transportation. Finally, this paper provides some recommendations on how to formulate appropriate subway fares.
      Citation: Transportation Research Record
      PubDate: 2020-05-21T01:35:25Z
      DOI: 10.1177/0361198120918244
       
  • Laboratory Method to Assess Efficacy of Dust Suppressants for Dirt and
           Gravel Roads
    • Authors: Audrey M. Stallworth, Eric H. Chase, William D. Burgos, Nathaniel R. Warner
      First page: 188
      Abstract: Transportation Research Record, Ahead of Print.
      Particulate matter (PM) generated from dirt and gravel roads is a concern for both human and environmental health. To help reduce the amount of PM generated, many states allow the use of water coproduced from oil and gas wells (i.e., brines) as road dust suppressants. However, few methods exist to quantify the effectiveness of these brines and other dust suppressants. Here we designed and tested a bench-scale method to test the efficacy of dust suppressants on dirt and gravel road materials. The Standard Proctor test was modified to create discs of road aggregate that could be treated with dust suppressant, dried, and then tumbled in a mechanical drum attached to an aerosol monitor that measured PM generated within the drum. Using two types of road aggregate (DSA and 2RC) and a combination of nine simulated brines, the effects of brine total dissolved solids (TDS), and sodium adsorption ratio (SAR) on dust suppression were calculated. The effects of moisture content and aggregate type were also observed. Higher TDS and lower SAR were found to be good predictors of dust-suppression effectiveness, with the degree of effectiveness partially dependent on the type of road aggregate. The test method provides a means to quickly and reproducibly compare effectiveness of dust suppressants, with other variables such as aggregate type and moisture content, to accurately estimate dust suppression. Comparisons of dust measurements collected within the laboratory and vehicle-based measurements offer the ability to relate laboratory results to conditions encountered on dirt and gravel roads.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:19:34Z
      DOI: 10.1177/0361198120918246
       
  • Methodology to Evaluate the Quality of Service of Traffic Flow on
           Intercity Expressway Sections by using Follower Percentage
    • Authors: Hiroyuki Konda, Hideki Nakamura
      First page: 200
      Abstract: Transportation Research Record, Ahead of Print.
      This study estimated composite headway distributions consisting of follower and non-follower headway elements and used the follower percentage obtained as the estimated parameters of those distributions to evaluate the quality of service (QOS) of traffic flow on Japanese intercity expressways under uncongested conditions. Analysis of pulse data obtained by vehicle detectors at multiple points with differing geometric structures showed that follower percentage is influenced by lane traffic volume, vehicle pair, and lane operation. Use of follower percentage also enabled clear and quantitative comparison and evaluation of the QOS of traffic flow for different lane operation formats, which could not be adequately expressed by such conventional macroscopic indices as average speed and traffic density. This indicates that follower percentage is a suitable performance measure for evaluating the QOS of traffic flow.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:17:14Z
      DOI: 10.1177/0361198120918575
       
  • Two-Stage Double Bootstrap Data Envelopment Analysis for Efficiency
           Evaluation of Shared-Bicycle Stations in Urban Cities
    • Authors: Jungyeol Hong, Reuben Tamakloe, Jihoon Tak, Dongjoo Park
      First page: 211
      Abstract: Transportation Research Record, Ahead of Print.
      To optimize the performance and operation of shared-bicycle systems, this study aims to evaluate the efficiency of shared-bicycle stations and to find factors affecting their efficiency scores. We analyzed the efficiency of 1,260 shared-bicycle stations in the City of Seoul using shared-bicycle rental and trajectory data as of June 2018. In this study, the two-stage bootstrap data envelopment analysis, which is a non-parametric frontier technique, was applied to estimate each shared-bicycle station’s efficiency. In the first stage, we evaluated efficiency scores by employing the number of bicycle racks and bicycle path ratio as input variables, and bicycle turnover rate and balancing rate as output variables. The efficiency scores were regressed on potential covariates using a bootstrapped truncated regression in the second stage. From our results, the efficiencies of shared-bicycle stations were found to be diverse depending on the nature of land use around the station location. The results present evidence to show that shared-bicycle stations located in residential and school-dominated areas are likely to be efficient, whereas those in semi-industrial areas, commercial, and business districts are generally inefficient. Furthermore, the effect of variables like the commuting population, the number of registered vehicles, and the number of bicycle-related accidents per year were statistically significant, thus affecting shared-bicycle station performance. This study offers essential insights into the efficiency of shared-bicycle stations, which could be incorporated into shared-transportation strategies to improve mobility in urban cities.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:18:34Z
      DOI: 10.1177/0361198120918568
       
  • Effect of Rail Pad Stiffness on Vehicle–Track Dynamic Interaction
           Excited by Rail Corrugation in Metro
    • Authors: Xiaolin Song, Yu Qian, Kaiyun Wang, Pengfei Liu
      First page: 225
      Abstract: Transportation Research Record, Ahead of Print.
      Rail corrugation can cause intense dynamic interaction between train and track, which can reduce riding comfort and lifespan of track structure, and even threaten running safety. Instead of investigating the root cause and growth of corrugation, this case study aims to investigate possible solutions to the excess train–track dynamic interaction excited by rail corrugation in a metro track through both numerical analysis and field experiments. Numerical analysis was performed based on a vehicle–track coupled dynamical model with field-measured rail corrugation information from two curves. The numerical analysis results indicated that rail pad stiffness was the key factor affecting wheel–rail contact force in the studied direct fixation type transit track system. Rail pads with a lower stiffness could reduce the wheel–rail interaction; however, softer rail pads will also increase the rail displacement. Therefore, both the wheel–rail contact force and rail displacement need to be considered while determining the optimal rail pad stiffness. New rail pads with a stiffness of 35 MN/m, which are softer than the original rail pads with a stiffness of 50 MN/m, were recommended for the track in this study. Through field validation and long-term monitoring, new rail pads have been proven to effectively reduce the vehicle–track dynamic interaction and ease the development of rail corrugation to a certain extent. Compared with regular rail grinding, using rail pads with the appropriate stiffness can save transit agencies a tremendous amount of time and cost. The observations from this case study can benefit transit facing rail corrugation problems.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:19:55Z
      DOI: 10.1177/0361198120918584
       
  • Investigating the Role of Big Data in Transportation Safety
    • Authors: Subasish Das, Greg P. Griffin
      First page: 244
      Abstract: Transportation Research Record, Ahead of Print.
      Big data may offer solutions for many challenges for transportation safety, providing more data faster, with higher spatial and temporal resolution. However, researchers and practitioners identify biases in big data that need to be explored and examined before performing data-driven decision-making. Leveraging semi-structured interviews of big data experts, this study includes a quantified analysis of topic frequency and an evaluation of the reliability of concepts through two independently trained coders. To identify the trends in the unstructured textual contents, the research team developed a text mining pipeline to identify trends, patterns, and biases. The study identifies key terms experts use when describing the role of big data in transportation safety, how the terms relate to the big data experts’ language through network plots, and clustering shows a need to focus on sources, quality, analysis, and implementation of big data. Results show value in maintaining the centrality of transportation experts and the public to determine the proper goals and metrics to evaluate transportation safety. Practitioners and researchers can develop new methods to improve population representation with big data, in addition to addressing difficult transportation safety problems. Working ahead of emerging trends and technologies of big data could support further advancements in transportation safety.
      Citation: Transportation Research Record
      PubDate: 2020-05-09T12:17:58Z
      DOI: 10.1177/0361198120918565
       
  • Safety, Energy, and Emissions Impacts of Adaptive Cruise Control and
           Cooperative Adaptive Cruise Control
    • Authors: Iman Mahdinia, Ramin Arvin, Asad J. Khattak, Amir Ghiasi
      First page: 253
      Abstract: Transportation Research Record, Ahead of Print.
      Connected and automated vehicle technologies have the potential to significantly improve transportation system performance. In particular, advanced driver-assistance systems, such as adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC), may lead to substantial improvements in performance by decreasing driver inputs and taking over control of the vehicle. However, the impacts of these technologies on the vehicle- and system-level energy consumption, emissions, and safety have not been quantified in field tests. The goal of this paper is to study the impacts of automated and cooperative systems in mixed traffic containing conventional, ACC, and CACC vehicles. To reach this goal, experimental data based on real-world conditions are collected (in tests conducted by the Federal Highway Administration and the U.S. Department of Transportation) with presence of ACC, CACC, and conventional vehicles in a vehicle platoon scenario and a cooperative merging scenario. Specifically, a platoon of five vehicles with different vehicle type combinations is analyzed to generate new knowledge about potential safety, energy efficiency, and emission improvement from vehicle automation and cooperation. Results show that adopting the CACC system in a five-vehicle platoon substantially reduces the driving volatility and reduces the risk of rear-end collision which consequently improves safety. Furthermore, it decreases fuel consumption and emissions compared with the ACC system and manually-driven vehicles. Results of the merging scenario show that while the cooperative merging system slightly reduces the driving volatility, the fuel consumption and emissions can increase because of sharper accelerations of CACC vehicles compared with manually-driven vehicles.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:21:54Z
      DOI: 10.1177/0361198120918572
       
  • Actuated Traffic Signal Performance Evaluation along Arterials using Wi-Fi
           Travel Time Samples and High-Resolution Traffic Signal Events Data
    • Authors: Pengfei (Taylor) Li, Farzana R. Chowdhury, Peirong (Slade) Wang, Sayem Mohammad Imtiaz
      First page: 268
      Abstract: Transportation Research Record, Ahead of Print.
      Understanding traffic progression on arterials is critical for traffic signal control and urban traffic management. Traffic conditions are highly dynamic and evolve over time. Therefore, it is necessary to evaluate the arterial’s performance periodically to determine how well a traffic signal system is functioning. Arterial performance is conventionally evaluated based on travel time/speed collected via the probe vehicles. New approaches based on high-resolution traffic signal events have been proposed by a group at Purdue University, based on the Purdue Coordination Diagrams (PCDs). Both traditional arterial travel times/speeds and the PCDs can effectively reflect the level of traffic progression on arterials, while some practical questions have been raised about how to synthesize these two methods. The framework proposed in this paper integrates two types of performance measures by defining new multi-intersection coordination diagrams to examine traffic signal performance. The multi-intersection coordination diagram under different speeds can provide a straightforward tool for informed offset adjustments of actuated traffic signal coordination. In contrast, the state-of-the-practice traffic coordination performance analysis relies on fixed timings and empirical fine-tuning in the field. It is expected that these efforts can provide new insights to practitioners on how to use emerging traffic data better to improve the performance of actuated traffic signal operations on arterials.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:29:15Z
      DOI: 10.1177/0361198120918869
       
  • Governance of Emerging Autonomous Driving Development in China
    • Authors: Qiuju Xue, Meng Xu, Caroline Mullen
      First page: 281
      Abstract: Transportation Research Record, Ahead of Print.
      The governance of autonomous driving (AD) technology is vital to enhance its benefits while avoiding the risks. In this paper, we attempt to focus on this issue and take the development of AD in China as an example for examining its governance. First, the positions and responsibilities of important stakeholders (the government and businesses) in the development of AD in the Chinese special administrative system environment are examined. Then, the regulatory relationship between them is discussed through investigating relevant policy documents, company websites, and media reports. The investigation shows that, thus far, the legislative process with regard to AD governance is lagging behind its development to some extent. In most instances, the government’s response is relatively conservative and focuses on creating normative documents to better regulate AD. There is, therefore, a comparative lack of commitment to confirming the legitimacy of AD. In contrast, companies are the pioneers of AD development. They actively explore the future of AD and relevant policy formulation via extensive alliances that share the risks and uncertainties of this innovation. To address the issue of governance, strategies ranging from supplying transportation infrastructure and investing in AD through government-led industrial funds to public–private partnerships have been adopted. However, it is not clear whether this enterprise-led direction of industrial development is consistent with the government’s management goals, although these industry lobbies are actively promoting effective policy-making.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:39:18Z
      DOI: 10.1177/0361198120918871
       
  • Travel Demand and Emissions from Driving Dogs to Dog Parks
    • Authors: Don MacKenzie, Hyun Cho
      First page: 291
      Abstract: Transportation Research Record, Ahead of Print.
      This paper reports on an intercept survey of dog park visitors in Seattle, U.S., which was combined with Google Maps and Google Popular Times data to develop estimates of the number of walking trips, vehicle miles traveled (VMT), and greenhouse gas (GHG) emissions associated with traveling to dog parks. It is estimated that approximately 1.6 million VMT and more than 700 tonnes CO2-equivalent are generated annually by driving dogs to dog parks in Seattle, representing approximately 0.07% of vehicle trips and 0.04% of GHG emissions from cars and light trucks in the city. Based on a stated choice exercise, it is estimated that allowing dogs off-leash in neighborhood parks could reduce these VMT and GHG emissions by 38% and 45%, respectively, while encouraging more than 39,000 additional walking trips annually. Even limiting such use to the hours of 6:00 to 8:00 a.m. would reduce VMT and GHGs by 24% and 28%, respectively, while encouraging 22,000 additional walking trips. Although less than 20% of survey respondents expressed an interest in replacing a trip to the dog park with a visit to a neighborhood park, those who did were likely to replace driving trips to the dog park with walking trips. Thus, allowing dogs off-leash in neighborhood parks, even for limited hours each day, could increase physical activity while reducing the vehicle travel and GHG emissions associated with driving dogs to dog parks.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:16:14Z
      DOI: 10.1177/0361198120918870
       
  • Person-Based Micro-Simulation Demand Model for National Long-Distance
           Travel in the U.S.A.
    • Authors: Lei Zhang, Yijing Lu, Sepehr Ghader, Carlos Carrion, Arash Asadabadi, Di Yang
      First page: 297
      Abstract: Transportation Research Record, Ahead of Print.
      As the nation and various states engage in funding transportation infrastructure improvements to meet future long-distance passenger travel demand, it is imperative to develop effective and practical modeling methods for analysis of long-distance passenger travel. Evaluating national-level infrastructure improvements requires a reliable analysis tool to model the demand for long-distance travel. The national travel demand model presented in this paper implements a person-level tour-based micro-simulation approach for modeling individuals’ long-distance or national activities in the U.S.A. This paper reviews the model framework, explains the model calibration, and presents applications of the model for policy evaluation and demand prediction. The model was estimated using the latest long-distance travel survey in the U.S.A., which is the 1995 American Travel Survey. As the estimation data is old, and no new long-distance travel survey with appropriate sample size is available to re-estimate the model, model calibration is the solution used to update the model and make it capable of capturing up-to-date travel patterns. Calibrating such a large-scale model can be challenging, because each calibration iteration is very costly. This paper describes the calibration effort conducted on the national long-distance micro-simulation model to showcase how a large-scale travel demand model can be calibrated efficiently. A fuel price scenario is analyzed to show how the national travel demand will change under a national fuel price increase scenario in the future year 2040. Another scenario analysis corresponding to construction of high-speed rail (HSR) is conducted to observe the effects of adding a HSR system to the northeast corridor on travel demand from a national perspective.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:14:54Z
      DOI: 10.1177/0361198120919119
       
  • Assessment of Deterioration of Highway Pavement using Bayesian Survival
           Model
    • Authors: Sylvester Inkoom, John O. Sobanjo, Eric Chicken, Debajyoti Sinha, Xufeng Niu
      First page: 310
      Abstract: Transportation Research Record, Ahead of Print.
      The size and level of complexity of highway pavement data and its associated covariates have led to the application of different approaches in the analysis of the highway pavement data for deterioration modeling. With the goal of predicting the survival of highway pavement with interpretable and reproducible models that are robust to uncertainties, errors, and overfitting, the Bayesian survival model (BSM) is proposed in this paper as a good method of estimating parameters for survival functions. Deterioration patterns in relation to the failure time distribution are treated as random quantities sampled from some stochastic prior processes. The specified priors are combined with the data sampled to obtain the distribution of the survival function using Bayes theorem and the Markov chain Monte Carlo method. A posteriori distribution of the survival function is obtained from the pavement information and compared with the classical product limit survival (Kaplan-Meier) estimate and the univariate parametric survival function. This paper reports experimental results of the three candidate models and their efficiency in describing the survival of highway pavement in the presence of deterioration. It is observed from the BSM outcomes that the posterior estimates are accurate in estimating the survival times of roadway segments at 95% credible interval. The outputs also show the robustness of the BSM in describing the uncertainties associated with the survival of highway pavement compared with the Kaplan-Meier and the univariate parametric survival models in the event of limited data and misspecification of underlying distribution.
      Citation: Transportation Research Record
      PubDate: 2020-06-01T06:02:33Z
      DOI: 10.1177/0361198120919112
       
  • Developing Technologies and Procedures to Reduce Tracking and Achieve
           Uniform and Accurate Tack Coat Application
    • Authors: Erdem Coleri, Richard Villarreal, Blaine M. Wruck
      First page: 326
      Abstract: Transportation Research Record, Ahead of Print.
      The tack coat bond is known to affect the longevity of asphalt pavements. Proper interlayer bonding prevents successive pavement layers from acting independently of one another and creating non-uniform stress and strain profiles in the pavement structure. Poor bonding between pavement layers can result in various pavement failures such as slippage cracking, debonding, and early fatigue cracking, all of which contribute to a reduced pavement fatigue life. Tack coat application rate and uniformity (that can be achieved by uniform tack coat application and by avoiding/minimizing tracking) are two major factors that control the performance of the tack coat bonding and longevity of the pavement structure. In this study, a wireless scale system (OreTackRate) that can be controlled from a tablet computer was developed to measure tack coat application rate accuracy and uniformity. The developed wireless scale system was recommended to be implemented during construction to validate application rate accuracy and uniformity. In addition, a distributor truck certification process was developed and presented in this study. The developed scale system can also be used to determine whether the applied tack coat is cured at any time point during construction. Residual tack coat application rate can also be measured using OreTackRate during construction. Implementation of all these tests, procedures, and technologies is expected to improve the tack coat uniformity during construction and improve the overall longevity of the pavement structure.
      Citation: Transportation Research Record
      PubDate: 2020-05-15T07:24:02Z
      DOI: 10.1177/0361198120919115
       
  • Durability aspects of Chemically Stabilized Quarry By-Product Applications
           in Pavement Base and Subbase
    • Authors: Issam I. A. Qamhia, Erol Tutumluer, Hasan Ozer, Huseyin Boler, Heather Shoup, Andrew J. Stolba
      First page: 339
      Abstract: Transportation Research Record, Ahead of Print.
      Recent research conducted at the Illinois Center for Transportation evaluated sustainable applications of quarry by-products (QB) or QB blended with coarse recycled aggregates in chemically stabilized base and subbase layers in flexible pavements and proved that stabilized QB pavement applications show satisfactory pavement performance. This paper investigates the durability aspects of the evaluated QB applications, particularly in relation to freezing–thawing cycles during winter and wetting–drying conditions. Durability tests were conducted on samples extracted from field test sections previously evaluated with accelerated pavement testing (APT) as well as on new samples prepared in the laboratory with the same QB types and material combinations. Field-extracted samples were exposed to multiple cycles of freezing and thawing and wetting and drying throughout APT. Both sets of samples were evaluated by AASHTO T 135 and AASHTO T 136 for wet–dry and freeze–thaw durability, respectively. The results of durability testing indicated that cement-stabilized QB materials benefited from the long-term curing in the field, whereas fly ash-stabilized QB materials were less durable after exposure to multiple freeze–thaw and wet–dry cycles in the field. Field samples compacted at or near the maximum dry density (i.e., having higher relative densities) consistently showed better performance for durability. Further, durability samples made with QB materials from dolomitic aggregate sources, having higher magnesium oxide content in chemical composition, showed better field performances than those with limestone QB having high calcium oxide content. This was possibly linked to cementation observed in the dolomitic QB applications after being exposed to freeze–thaw cycles in three winters.
      Citation: Transportation Research Record
      PubDate: 2020-05-15T07:29:01Z
      DOI: 10.1177/0361198120919113
       
  • Mobile Application Development and Testing for Work Zone Activity
           Real-Time Data Collection
    • Authors: Farzaneh Azadi, Yaw Adu-Gyamfi, Carlos Sun, Praveen Edara
      First page: 351
      Abstract: Transportation Research Record, Ahead of Print.
      Work zones are prevalent in the United States as the infrastructure is increasingly in need of maintenance. Lack of reliable data is one of the main obstacles in work zone research. Reliability suffers because of underreporting of crashes and inclusion in the analysis of irrelevant activities that are not attributable to work zones. In addition, the work zone environment is very dynamic, resulting in differing reasons for crashes. These are barriers to gaining an accurate understanding of safety in work zones. The objective of this paper is to design, develop, and deploy a mobile application (app) for real-time work zone data collection to address these issues. The development process consisted of the following steps. First, a user interface was designed to enable users to collect various work zone activity information. Second, taking advantage of recent advances in cloud computing, a real-time database was designed for efficient storage and instantaneous communication of work zone activity data. Field tests were then conducted at 13 work zone sites in Columbia, Missouri. Finally, the performance of the app was evaluated based on scalability, precision, and user friendliness. The app was able to respond to queries at real-time speeds even as the size of the database and the number of users increased. The precision of sensors was within appreciable accuracy for the geolocation. The app’s user friendliness was acknowledged by the users. The successful deployment of this mobile app would lead to accurate work zone data which is very useful for work zone management, traveler information, contract monitoring, safety analysis, and project coordination.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:50:19Z
      DOI: 10.1177/0361198120919118
       
  • Model Calibration and Forecasts of Air Travel Demand with Categorized
           Household Socioeconomic Attributes
    • Authors: Jungin Kim, Ikki Kim, Jaeyeob Shim, Hansol Yoo, Sangjun Park
      First page: 363
      Abstract: Transportation Research Record, Ahead of Print.
      The objectives of this study were to (1) construct an air demand model based on household data and (2) forecast future air demand to explain the relationship between air demand and individual travel behavior. To this end, domestic passenger air travel demand at Jeju Island in South Korea was examined. A multiple regression model with numerous explanatory variables was established by examining categorized household socioeconomic data that affected air demand. The air travel demand model was calibrated for 2009–2015 based on the annual average number of visits to Jeju Island by households in certain income groups. The explanatory variable was set using a dummy variable for each household income group and the proportion of airfare to GDP per capita. Higher household income meant more frequent visits to Jeju Island, which was well-represented in the model. However, the value of the coefficient for the highest income was lower than the value for the second-highest income group. This suggested that the highest income group preferred overseas travel destinations to domestic ones. The future air demand for Jeju airport was predicted as 26,587,407 passengers in 2026, with a subsequent gradual increase to approximately 33,000,000 passengers by 2045 in this study. This study proposed an air travel demand model incorporating household socioeconomic attributes to reflect individual travel behavior, which contrasts with previous studies that used aggregate data. By constructing an air travel model that incorporated socioeconomic factors as a behavioral model, more accurate and consistent projections could be obtained.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:17:35Z
      DOI: 10.1177/0361198120919111
       
  • Repair of Severely Damaged Reinforced Concrete Beams with High-Strength
           Cementitious Grout
    • Authors: Antoine N. Gergess, Mahfoud Shaikh Al Shabab, Razane Massouh
      First page: 372
      Abstract: Transportation Research Record, Ahead of Print.
      High-strength cementitious materials such as high-performance concrete are extensively used for retrofit of reinforced concrete (RC) structures. The effectiveness of these materials is increased when mixed with steel fibers. A commonly used technique for strengthening and repair of RC beams consists of applying high-performance fiber-reinforced concrete jackets around the beam perimeter. This paper investigates the jacketing method for repairing severely damaged RC beams. Four 2 m (6 ft 63/4 in.) long rectangular RC beams, 200 × 300 mm (8 ×12 in.) were initially cast and loaded until failure based on three-point bending tests. The four beams were then repaired by thickening the sides of the damaged RC beams using a commercially available high-strength shrinkage grout with and without steel fibers. Strain and deformation were recorded in the damaged and repaired beams to compare structural performance. It is shown that the flexural strength of the repaired beams is increased and the crack pattern under loading is improved, proving that the proposed repair method can restore the resistance capacity of RC beams despite the degree of damage. A method for repair is proposed and an analytical investigation is also performed to understand the structural behavior of the repaired beams based on different thickening configurations.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T06:56:19Z
      DOI: 10.1177/0361198120919116
       
  • Sensitivity Analysis to Define Guidelines for Predictive Control Design
    • Authors: M. C. Poelman, A. Hegyi, A. Verbraeck, J. W. C. van Lint
      First page: 385
      Abstract: Transportation Research Record, Ahead of Print.
      Signalized traffic control is important in traffic management to reduce congestion in urban areas. With recent technological developments, more data have become available to the controllers and advanced state estimation and prediction methods have been developed that use these data. To fully benefit from these techniques in the design of signalized traffic controllers, it is important to look at the quality of the estimated and predicted input quantities in relation to the performance of the controllers. Therefore, in this paper, a general framework for sensitivity analysis is proposed, to analyze the effect of erroneous input quantities on the performance of different types of signalized traffic control. The framework is illustrated for predictive control with different adaptivity levels. Experimental relations between the performance of the control system and the prediction horizon are obtained for perfect and erroneous predictions. The results show that prediction improves the performance of a signalized traffic controller, even in most of the cases with erroneous input data. Moreover, controllers with high adaptivity seem to outperform controllers with low adaptivity, under both perfect and erroneous predictions. The outcome of the sensitivity analysis contributes to understanding the relations between information quality and performance of signalized traffic control. In the design phase of a controller, this insight can be used to make choices on the length of the prediction horizon, the level of adaptivity of the controller, the representativeness of the objective of the control system, and the input quantities that need to be estimated and predicted the most accurately.
      Citation: Transportation Research Record
      PubDate: 2020-05-18T07:02:35Z
      DOI: 10.1177/0361198120919114
       
  • Bond Index Approach to the Evaluation of Transportation P3 Market in the
           U.S.
    • Authors: Yu Wang, Kunqi Zhang, Qingbin Cui, Felix Delgado
      First page: 399
      Abstract: Transportation Research Record, Ahead of Print.
      Private investment through revenue bonds has become an important source of financing for public agencies seeking to implement public–private partnership (P3) projects. It has been a long-standing assumption that private financing exceeds the limited investment opportunity attributed to P3 projects in the pipeline. This assumption, however, remains unexamined. Basic economics theory states that prices go up if demand exceeds supply. Therefore, this study presents the construction and performance of the P3 surface transportation bond index to evaluate private capital for P3 projects. The index will help encourage private investment in P3 projects in addition to measuring the return of such investment on a market basis. The index can also disclose the risks of P3 revenue bonds and potentially offer an investment instrument in the secondary market.
      Citation: Transportation Research Record
      PubDate: 2020-05-22T11:10:08Z
      DOI: 10.1177/0361198120919395
       
  • Observational Study of Pedestrian and Cyclist Interactions at
           Intersections in Vancouver, BC and Montréal, QC
    • Authors: Kate Hosford, Marie-Soleil Cloutier, Meghan Winters
      First page: 410
      Abstract: Transportation Research Record, Ahead of Print.
      As cycling and walking for transportation continues to become more popular in urban settings, there is increased potential for interactions between different types of road users, including between pedestrians and cyclists. However, because of limited data, we know relatively little about the frequency and nature of pedestrian-cyclist interactions. In this observational study we aimed to quantify the extent of pedestrian crossings that involved an interaction with a cyclist at 10 intersections in Vancouver, British Columbia (BC) and Montréal, Quebec (QC), and identify road user and crossing environment characteristics associated with these interactions. Of the 3,884 pedestrians we observed, 562 (14%) were involved in an interaction with a cyclist. The interaction rate was slightly higher in Montréal (16.5%) than Vancouver (13.4%), but varied considerably across intersections (range from 0.9% to 35.8%). Men were slightly more likely to be involved in an interaction with a cyclist, as well as pedestrians crossing at a slower pace at the beginning of the crossing, and at mid-crossing. Contrary to common thought, distracted pedestrians (either using a cell phone or wearing headphones) were not more likely to be involved in an interaction. When considering the street crossing environment, interactions were more likely at crossings with cycle tracks, stop or yield signs, three-way intersections, crossings that had no pedestrian ground markings, and longer crosswalks. Our study provides insight into interactions between pedestrians and cyclists, a well-known gap in transportation safety, and can help identify which urban design features are needed to ensure safe and comfortable pedestrian crossings.
      Citation: Transportation Research Record
      PubDate: 2020-05-07T06:44:15Z
      DOI: 10.1177/0361198120919407
       
  • Approach for Determination of Maximum Reclaimed Asphalt Pavement Content
           in Polymer-Modified Asphalt Mixture
    • Authors: Bongsuk Park, Jian Zou, Reynaldo Roque, George Lopp, Zhengyu Wu
      First page: 420
      Abstract: Transportation Research Record, Ahead of Print.
      Reclaimed asphalt pavement (RAP), commonly generated from the millings of damaged roads, contains recyclable asphalt and aggregate. Polymer-modified asphalt (PMA) binders have had proven success in mitigating rutting and cracking in asphalt pavements. However, benefits associated with PMA binder may be reduced by aged and more brittle RAP binder. Currently, the maximum usage of RAP in PMA mixture is limited to 10–20% by several Departments of Transportation in the United States. Other than maximum RAP content, no criterion related to RAP characteristics is used to limit RAP usage in PMA mixture. Recent studies showed RAP binder stiffness and RAP aggregate gradation appeared to be important characteristics related to cracking performance of PMA mixture containing RAP. Therefore, this research focused on determining maximum allowable RAP content in PMA mixture for individual RAP sources based on key RAP characteristics identified, that is, RAP stiffness and RAP fineness. Interstitial component direct tension (ICDT) test was conducted to determine fracture energy for interstitial component (i.e., the fine portion of PMA mixture containing RAP), which is known to be correlated well with the fracture energy of the corresponding mixture. Results showed introduction of coarser and less stiff RAP generally resulted in greater fracture energy, which allowed up to 40% RAP usage in PMA mixture. Integration of key RAP characteristics identified and the results of ICDT test provide a systematic approach for determination of maximum RAP content in PMA mixtures. Further research is recommended to evaluate additional RAP sources to verify the proposed approach.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:49:59Z
      DOI: 10.1177/0361198120919403
       
  • Evaluating the Long-Term Durability of Lime Treatment in Hydraulic
           Structures: Case Study on the Friant-Kern Canal
    • Authors: Pavan Akula, Narain Hariharan, Dallas N. Little, Didier Lesueur, Gontran Herrier
      First page: 431
      Abstract: Transportation Research Record, Ahead of Print.
      The slopes along the Friant-Kern Canal were last treated in the 1970s with 4% quick lime to mitigate issues related to slope failure caused by expansive Porterville soils. The immediate benefits of lime treatment were well documented by the Bureau of Reclamation. However, questions remain over the long-term durability of lime-treated materials. In this study, we compare the engineering properties and changes in the soil mineralogy of treated and untreated sections to establish the effectiveness of lime after more than 40 years of performance. A geochemical model was developed using the GEM-Selektor program to simulate the geochemical reactions in the soil-lime system and predict stable pozzolanic products. The experimental results show a reduction in the plasticity index from 23 to 6 after lime treatment together with a tenfold increase in strength. Lime addition lowers the risk of volumetric expansion and erosion in soils from moderately high to very low. Further, a pH increase from 6.30 to 8.90 in lime-treated sections indicates that lime treatment continues to be effective. X-ray fluorescence analysis shows the presence of Ca2+ ions in quantities similar to the initial treatment dosage indicating negligible leaching of lime. The geochemical model provides evidence of the formation of pozzolanic products in the soil-lime system which was validated using thermogravimetry analysis. The performance history of the Friant-Kern Canal together with the findings of this study affirm the long-term durability of lime treatment on this project and strengthens the case for using lime in the repair of hydraulic structures.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:42:39Z
      DOI: 10.1177/0361198120919404
       
  • Evaluation of CO2 Emission at Airports from Aircraft Operations within the
           Landing and Take-Off Cycle
    • Authors: D. M. M. S. Dissanayaka, V. V. Adikariwattage, H. R. Pasindu
      First page: 444
      Abstract: Transportation Research Record, Ahead of Print.
      The importance of airport emission inventory is more specific in the local context as it directly affects the local air quality. The specific gap addressed by this research is evaluating the CO2 emission from aircrafts within the landing and take-off (LTO) cycle. Using currently available methodologies for assessing emission within the LTO cycle in the Sri Lankan context has significant limitations, such as unavailability of relevant operational data and the International Civil Aviation Organization (ICAO)-specified “time-in-mode”(TIM) (e.g., take-off, climb-out, idle, and approach) estimates at different phases of the LTO cycle being inconsistent with local conditions. Such industry-wide standards have been found to over or underestimate actual volumes specific to local conditions. In this research, data collected from online flight-tracking services and daily aircraft movement record (DAMR) data maintained by the local air traffic service provider were used to estimate TIM values according to site-specific conditions. Existing literature to some extent addresses the assessment of CO2 emission levels under different phases of flight separately. In this research, a methodology was developed with available data sources to estimate CO2 emission levels under different phases of flight separately within the LTO cycle. The methodology was applied to Bandaranaike International Airport, Sri Lanka. This approach can be applied to similar scenarios in which operational data limitations exist as elaborated in the study.
      Citation: Transportation Research Record
      PubDate: 2020-05-27T10:36:59Z
      DOI: 10.1177/0361198120919411
       
  • Friction and Texture Retention of Concrete Pavements
    • Authors: Satyavati Komaragiri, Armen Amirkhanian, Amit Bhasin
      First page: 457
      Abstract: Transportation Research Record, Ahead of Print.
      In the late 1980s and early 1990s, the Alabama Department of Transportation (ALDOT), U.S., noticed a decline in skid trailer numbers on concrete pavements shortly after grinding operations. The engineers at the time suspected that the coarse aggregate caused the decline in these numbers and the resulting conclusion led to a ban of carbonate aggregates in mainline concrete pavement in Alabama that is still in place. This detailed laboratory study re-examines the fundamental friction issues that led to this policy. A total of 48 aggregate, grinding, and grooving combinations were tested as part of this study. Three aggregate sources were examined: a siliceous source, a “hard” limestone source, and a “soft” limestone source. Two blade spacings were examined for grinding operations: 52 blades/ft and 60 blades/ft. Some ground specimens were also grooved. Finally, a set of specimens had the Next Generation Concrete Surface (NGCS) applied to them. The specimens were polished with the National Center for Asphalt Technology (NCAT) three-wheel polishing device (TWPD). The dynamic friction tester was used to evaluate friction values at various points through the polishing process. After the polishing, the macrotexture was characterized using the circular track meter. Across the board, the highest performing texture was that with no grooves and 52 blades/ft. Very generally, the loss of friction decreased with increasing siliceous content. However, some of the trends were extremely minor and, in a few cases, siliceous aggregates caused higher friction loss. There were numerous instances when blended carbonate/siliceous concrete pavement surfaces performed better than sole siliceous concrete pavement surfaces.
      Citation: Transportation Research Record
      PubDate: 2020-05-26T09:50:59Z
      DOI: 10.1177/0361198120919397
       
  • Modeling Social Distance and Activity-Travel Decision Similarity to
           Identify Influential Agents in Social Networks and Geographic Space and
           Its Application to Travel Mode Choice Analysis
    • Authors: Jinhee Kim, Yun Kyung Bae, Jin-Hyuk Chung
      First page: 466
      Abstract: Transportation Research Record, Ahead of Print.
      Because humans are social beings, people are members of social networks and interact with other members. As a result of social interaction, people can be influenced by the behavior of others. The present study addresses conformity behavior in activity-travel decisions, implying that in making such decisions people mimic the behavior of other members of their social networks. The presence of conformity behavior in social networks implies that sustainable behavior can be dispersed through networks. Therefore, knowing which people in a network are influential can help make a sustainable transportation policy more effective. In particular, information about the topology of social networks and geographical distribution can help maximize the policy’s spill-over effects in social and geographic spaces. This study suggests a framework to locate influential agents in relation to activity-travel decisions using three procedures: (1) estimating social distance associated with similarity in activity-travel decisions, (2) identifying influential agents by measuring centralities, and (3) exploring the spatial and activity-travel characteristics of the influential agents. The suggested framework is applied using the travel mode choices of people who had recently taken trips by road beside/alongside the Han River in Seoul, South Korea.
      Citation: Transportation Research Record
      PubDate: 2020-05-27T10:38:59Z
      DOI: 10.1177/0361198120919412
       
  • Deep Learning Approach for Predictive Analytics to Support Diversion
           during Freeway Incidents
    • Authors: Rajib Saha, Mosammat Tahnin Tariq, Mohammed Hadi
      First page: 480
      Abstract: Transportation Research Record, Ahead of Print.
      Route diversion during incidents on freeways has been proven to be a useful tactic to mitigate non-recurrent congestion. However, the capacity constraints created by the signals on the alternative routes put limits on the diversion process since the typical time-of-day (TOD) signal control cannot handle the sudden increase in the traffic on the arterials because of diversion. Thus, there is a need for active transportation management strategies that support agencies in identifying the potential diversion routes for freeway incidents and the need for adjusting the traffic signal timing under different incident and traffic conditions. This paper investigates the use of a data analytic approach based on the long short-term memory (LSTM) deep neural network method to predict the alternative routes dynamically using incident attributes and traffic status on the freeway, and travel time on both the freeway and alternative routes during the incident. Additionally, a methodology is proposed for the development of special signal plans for the critical intersections on the alternative arterials based on the results from the LSTM neural network, combined with simulation modeling, and signal timing optimization. The methodology developed in the paper can be easily implemented by the transportation agencies, as it is based on data that are generally available to the agencies. The results from this paper indicate that the developed methodology can be used as part of a decision support system (DSS) to manage the traffic proactively during the incidents on the freeways.
      Citation: Transportation Research Record
      PubDate: 2020-06-03T06:06:11Z
      DOI: 10.1177/0361198120917673
       
 
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