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  Subjects -> TRANSPORTATION (Total: 171 journals)
    - AIR TRANSPORT (8 journals)
    - AUTOMOBILES (22 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (6 journals)
    - SHIPS AND SHIPPING (34 journals)
    - TRANSPORTATION (96 journals)

TRANSPORTATION (96 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 89)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4)
Archives of Transport     Open Access   (Followers: 17)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 12)
Cities in the 21st Century     Open Access   (Followers: 14)
Economics of Transportation     Partially Free   (Followers: 13)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 11)
European Transport Research Review     Open Access   (Followers: 21)
Geosystem Engineering     Hybrid Journal   (Followers: 1)
IATSS Research     Open Access  
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 9)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 8)
IFAC-PapersOnLine     Open Access  
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 8)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 9)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 3)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 9)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 9)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 10)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 11)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 12)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 15)
International Journal of Transportation Science and Technology     Open Access   (Followers: 9)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 12)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 210)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 12)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 2)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 5)
Journal of Transport & Health     Hybrid Journal   (Followers: 8)
Journal of Transport and Land Use     Open Access   (Followers: 22)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 12)
Journal of Transport Geography     Hybrid Journal   (Followers: 21)
Journal of Transport History     Hybrid Journal   (Followers: 15)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 8)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 16)
Journal of Transportation Technologies     Open Access   (Followers: 14)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 9)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics     Open Access   (Followers: 1)
Logistics & Sustainable Transport     Open Access   (Followers: 2)
Logistique & Management     Full-text available via subscription  
Mobility in History     Full-text available via subscription   (Followers: 2)
Modern Transportation     Open Access   (Followers: 10)
Nonlinear Dynamics     Hybrid Journal   (Followers: 16)
Open Journal of Safety Science and Technology     Open Access   (Followers: 8)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 2)
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 8)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 13)
Public Transport     Hybrid Journal   (Followers: 18)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 5)
Revista Transporte y Territorio     Open Access   (Followers: 1)
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 11)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 2)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 5)
Transport     Hybrid Journal   (Followers: 14)
Transport and Telecommunication Journal     Open Access   (Followers: 4)
Transport in Porous Media     Hybrid Journal   (Followers: 1)
Transport Problems     Open Access   (Followers: 1)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 9)
Transportation     Hybrid Journal   (Followers: 27)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 13)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 4)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 32)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 30)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 22)
Transportation Research Procedia     Open Access   (Followers: 5)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 34)
Transportation Science     Full-text available via subscription   (Followers: 21)
TRANSPORTES     Open Access   (Followers: 5)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 5)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 2)
Transportrecht     Unknown  
Travel Behaviour and Society     Full-text available via subscription   (Followers: 6)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
Urban, Planning and Transport Research     Open Access   (Followers: 26)
Vehicular Communications     Full-text available via subscription   (Followers: 4)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 6)
Транспортні системи та технології перевезень     Open Access  
Journal Cover Transportation Research Part B: Methodological
  [SJR: 3.905]   [H-I: 87]   [30 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0191-2615
   Published by Elsevier Homepage  [3118 journals]
  • Capacity-drop at extended bottlenecks: Merge, diverge, and weave
    • Authors: Danjue Chen; Soyoung Ahn
      Pages: 1 - 20
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Danjue Chen, Soyoung Ahn
      This paper investigates the mechanisms of how spatially distributed lane changes (LCs) interact and contribute to “capacity-drop” at three types of extended bottlenecks: merge, diverge, and weave. A hybrid approach is used to study the problem: analytical approach to capture the behavior of merging and diverging LCs and numerical simulations to quantify capacity-drop considering various geometric configurations of extended bottlenecks. This study focuses on the impact of LC vehicles’ bounded acceleration on “void” (wasted space) creation in traffic streams when they insert/desert at a lower speed, and interactions among multiple voids. We found that (1) LCs closer to the downstream end of bottlenecks are more likely to create persisting voids and contribute to capacity-drop. (2) For weave bottlenecks, capacity-drop is governed by two counteracting effects of LCs: persisting voids and utilization of vacancies created by diverging vehicles; (3) the more balanced the merging and diverging flows, the lower the capacity-drop; and (4) capacity-drop is minimum if merging LCs occur downstream of diverging LCs, and maximum in the opposite alignment.

      PubDate: 2017-12-27T07:47:07Z
      DOI: 10.1016/j.trb.2017.12.006
      Issue No: Vol. 108 (2017)
  • A chance-constrained two-stage stochastic programming model for
           humanitarian relief network design
    • Authors: Özgün Elçi; Nilay Noyan
      Pages: 55 - 83
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Özgün Elçi, Nilay Noyan
      We consider a stochastic pre-disaster relief network design problem, which mainly determines the capacities and locations of the response facilities and their inventory levels of the relief supplies in the presence of uncertainty in post-disaster demands and transportation network conditions. In contrast to the traditional humanitarian logistics literature, we develop a chance-constrained two-stage mean-risk stochastic programming model. This risk-averse model features a mean-risk objective, where the conditional value-at-risk (CVaR) is specified as the risk measure, and enforces a joint probabilistic constraint on the feasibility of the second-stage problem concerned with distributing the relief supplies to the affected areas in case of a disaster. To solve this computationally challenging stochastic optimization model, we employ an exact Benders decomposition-based branch-and-cut algorithm. We develop three variants of the proposed algorithm by using alternative representations of CVaR. We illustrate the application of our model and solution methods on a case study concerning the threat of hurricanes in the Southeastern part of the United States. An extensive computational study provides practical insights about the proposed modeling approach and demonstrates the computational effectiveness of the solution framework.

      PubDate: 2017-12-27T07:47:07Z
      DOI: 10.1016/j.trb.2017.12.002
      Issue No: Vol. 108 (2017)
  • The Boundedly Rational User Equilibrium: A parametric analysis with
           application to the Network Design Problem
    • Authors: Oskar A.L. Eikenbroek; Georg J. Still; Eric C. van Berkum; Walter Kern
      Pages: 1 - 17
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Oskar A.L. Eikenbroek, Georg J. Still, Eric C. van Berkum, Walter Kern
      In this paper, we study a static traffic assignment that accounts for the boundedly rational route choice behavior of travelers. This assignment induces uncertainties to the ex-ante evaluation of a policy measure: the boundedly rational assignment is non-unique and the indifference band is an uncertain parameter. We consider two different ways to model the optimization problem that finds the best and worst-performing Boundedly Rational User Equilibrium with respect to the total travel time (Best/Worst-case BRUE). The first is the so-called branch approach, the second is a bilevel model. The latter approach is better suited to exploit techniques from parametric optimization and enables us, e.g., to prove the continuity of the optimal value function corresponding to the Best/Worst-case BRUE with respect to perturbations in the indifference band. We report on some numerical experiments. In addition, we extend our results to the Network Design Problem: we prove the existence of a second-best toll pricing scheme under bounded rationality.

      PubDate: 2017-11-16T13:06:14Z
      DOI: 10.1016/j.trb.2017.11.005
      Issue No: Vol. 107 (2017)
  • Decision field theory: Improvements to current methodology and comparisons
           with standard choice modelling techniques
    • Authors: Thomas O. Hancock; Stephane Hess; Charisma F. Choudhury
      Pages: 18 - 40
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Thomas O. Hancock, Stephane Hess, Charisma F. Choudhury
      There is a growing interest in the travel behaviour modelling community in using alternative methods to capture the behavioural mechanisms that drive our transport choices. The traditional method has been Random Utility Maximisation (RUM) and recent interest has focussed on Random Regret Minimisation (RRM), but there are many other possibilities. Decision Field Theory (DFT), a dynamic model popular in mathematical psychology, has recently been put forward as a rival to RUM but has not yet been investigated in detail or compared against other competing models like RRM. This paper considers arguments in favour of using DFT, reviews how it has been used in transport literature so far and provides theoretical improvements to further the mechanisms behind DFT to better represent general decision making. In particular, we demonstrate how the probability of alternatives can be calculated after any number of timesteps in a DFT model. We then look at how to best operationalise DFT using simulated datasets, finding that it can cope with underlying preferences towards alternatives, can include socio-demographic variables and that it performs best when standard score normalisation is applied to the alternative attribute levels. We also present a detailed comparison of DFT and Multinomial Logit (MNL) models using stated preference route choice datasets and find that DFT achieves significantly better fit in estimation as well as forecasting. We also find that our theoretical improvement provides DFT with much greater flexibility and that there are numerous approaches that can be adopted to incorporate heterogeneity within a DFT model. In particular, random parameters vastly improve the model fit.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.004
      Issue No: Vol. 107 (2017)
  • Kinematic wave models of sag and tunnel bottlenecks
    • Authors: Wen-Long Jin
      Pages: 41 - 56
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Wen-Long Jin
      Sags and tunnels are critical traffic bottlenecks, as they can cause capacity reduction, capacity drop, and extreme low acceleration rates when vehicles accelerate away from the upstream queue. In this paper, we present a behavioral kinematic wave model to explain the three bottleneck effects of sags and tunnels. Assuming increasing time gaps, we derive location-dependent triangular fundamental diagrams to explain the capacity reduction effect; with a bounded acceleration constraint on the stationary states inside the capacity reduction zone, we demonstrate the occurrence of capacity drop and derive a formula to calculate the dropped capacity from the fundamental diagram, road geometry, and acceleration process; from the structure of continuous standing waves we verify the low acceleration rate out of the upstream queue. We also present a simplified phenomenological model of capacity drop at sag/tunnel bottlenecks and two Cell Transmission Models for numerical simulations. With four stationary trajectories at the Kobotoke tunnel in Japan, we calibrate and validate the behavioral model and find that the theoretical predictions match the observations very well. This study can help to develop better design and control strategies to improve the performance of a sag or tunnel bottleneck.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.006
      Issue No: Vol. 107 (2017)
  • Pricing for a Last-Mile Transportation System
    • Authors: Yiwei Chen; Hai Wang
      Pages: 57 - 69
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Yiwei Chen, Hai Wang
      The Last-Mile Problem refers to the provision of travel service from the nearest public transportation node to a home or other destination. Last-Mile Transportation System (LMTS), which has recently emerged, provide on-demand shared transportation. We consider an LMTS with multiple passenger types—adults, senior citizens, children, and students. The LMTS designer determines the price for the passengers, last-mile service vehicle capacity, and service fleet size (number of vehicles) for each last-mile region to maximize the social welfare generated by the LMTS. The level of last-mile service (in terms of passenger waiting time) is approximated by using a batch arrival, batch service, multi-server queueing model. The LMTS designer's optimal decisions and optimal social welfare are obtained by solving a constrained nonlinear optimization problem. Our model is implemented in numerical experiments by using real data from Singapore. We show the optimal annual social welfare gained is large. We also analyze a counterpart LMTS in which the LMTS designer sets an identical price for all passenger types. We find that in the absence of price discounts for special groups of passengers, social welfare undergoes almost no change, but the consumer surplus of passengers in special groups suffers significantly.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.008
      Issue No: Vol. 107 (2017)
  • Coordinating assignment and routing decisions in transit vehicle
           schedules: A variable-splitting Lagrangian decomposition approach for
           solution symmetry breaking
    • Authors: Huimin Niu; Xuesong Zhou; Xiaopeng Tian
      Pages: 70 - 101
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Huimin Niu, Xuesong Zhou, Xiaopeng Tian
      This paper focuses on how to coordinate a critical set of assignment and routing decisions in a class of multiple-depot transit vehicle scheduling problems. The assignment decision aims to assign a set of transit vehicles from their current locations to trip tasks in a given timetable, where the routing decision needs to route different vehicles to perform the assigned tasks and return to the depot or designated layover locations. When applying the general purpose solvers and task-oriented Lagrangian relaxation framework for real world instances, a thorny issue is that different but indistinguishable vehicles from the same depot or similar locations could commit to the same set of tasks. This inherent solution symmetry property causes extremely difficult computational barriers for effectively eliminating identical solutions, and the lower bound solutions could contain many infeasible vehicle-to-task matches, leading to large optimality gaps. To systematically coordinate the assignment and routing decisions and further dynamically break symmetry during the solution search process, we adopt a variable-splitting approach to introduce task-specific and vehicle-distinguishable Lagrangian multipliers and then propose a sequential assignment process in order to enhance the solution quality for the augmented models with tight formulations. We conduct the numerical experiments to offer the managerial interpretation and examine solution quality of the proposed approach in a wider range of applications.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.003
      Issue No: Vol. 107 (2017)
  • Incorporating free-floating car-sharing into an activity-based dynamic
           user equilibrium model: A demand-side model
    • Authors: Qing Li; Feixiong Liao; Harry J.P. Timmermans; Haijun Huang; Jing Zhou
      Pages: 102 - 123
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Qing Li, Feixiong Liao, Harry J.P. Timmermans, Haijun Huang, Jing Zhou
      Free-floating car-sharing (FFC) has recently received increasing attention due to the flexibility in mobility services. Existing studies related to FFC mainly focus on the analysis of operational management and user preferences. Efforts to model the dynamic choices of free-floating shared cars (SCs) in individuals’ daily multi-modal multi-activity trip chains have still been rare. This study proposes a tolerance-based dynamic user equilibrium model of activity-travel scheduling that formulates free-floating SC as an alternative transport mode for conducting daily activities. The model embeds the choice of SC into daily trip chains by extending the state-of-the-art multi-state supernetwork representation. The dynamic traffic flows and supply-demand interactions of SCs are captured endogenously. Moreover, traveler heterogeneity and different pricing schemes are taken into account. A path-flow swapping method is suggested to solve the tolerance-based dynamic user equilibrium model. Numerical examples of various scenarios demonstrate that fleet size, distribution, and rental-parking price of FFC significantly influence the choice of SC and activity-travel pattern.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.011
      Issue No: Vol. 107 (2017)
  • Strategic Evacuation Network Design (SEND) under cost and time
    • Authors: Halit Üster; Xinghua Wang; Justin T. Yates
      Pages: 124 - 145
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Halit Üster, Xinghua Wang, Justin T. Yates
      In this study, we pose and analyze an evacuation network design problem to provide a planning tool to help with high-level design decisions involved in strategic preparedness for large scale evacuations. In doing so, while incorporating evacuation time considerations, we also take a cost perspective in designing an effective evacuation network. Both the network design and the associated cost considerations in evacuation planning are commonly ignored in the literature due to a focus on evacuation time and the associated flow routing objective. We propose a mathematical model for Strategic Evacuation Network Design (SEND) that prescribes shelter regions and capacities, intermediate locations that support/supply for en route evacuees as well as road segments and their capacities under evacuation time constraints. To solve our model, we devise an efficient Benders Decomposition based approach enhanced with surrogate constraints, strengthened Benders cuts, heuristics, and the use of multi-cuts. We apply our methodology to solve test instances developed based on real data from Central Texas. We demonstrate by our analysis that the resulting approach does not only provide us with a means to design evacuation networks but also serves as a tool to study the trade-offs involved in design and operational performance measures as it captures the essence of high-level interactions between them.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.010
      Issue No: Vol. 107 (2017)
  • Stochastic modeling of breakdown at freeway merge bottleneck and traffic
           control method using connected automated vehicle
    • Authors: Youngjun Han; Soyoung Ahn
      Pages: 146 - 166
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Youngjun Han, Soyoung Ahn
      This paper proposes a novel breakdown probability model based on microscopic driver behavior for a freeway merge bottleneck. Extending Newell's car following model to describe the transition from free-flow to congested regimes, two elements of breakdown, trigger and propagation, are derived in terms of vehicle headway. Combining these elements, a general breakdown probability is derived in terms of various parameters related to driver behavior and traffic conditions – other than flow – that can be treated as constants or stochastic with probability distributions. The proposed model is validated with real data. It was found that the theoretical breakdown probability distribution accords well with the empirical counterpart within reasonable ranges of parameter values. Our model suggests that the breakdown probability (i) increases with flow (both mainline and merging) as expected, and the merging spacing, (ii) decreases with the merging speed and aggressive driver characteristics, and interestingly, (iii) increases with the deviation in headway. A proactive traffic control method to achieve uniform headway is developed considering low penetration rates of connected automated vehicle technologies.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.007
      Issue No: Vol. 107 (2017)
  • Capacity allocation in vertically integrated rail systems: A bargaining
    • Authors: Ahmadreza Talebian; Bo Zou; Ahmad Peivandi
      Pages: 167 - 191
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Ahmadreza Talebian, Bo Zou, Ahmad Peivandi
      This paper presents a game-theoretic bargaining approach to allocating rail line capacity in vertically integrated systems. A passenger rail agency negotiates with the host freight railroad to determine train schedules and the associated payment. The objective on the passenger side is to maximize utility, i.e., revenue minus costs of passenger train operations, passenger schedule delay and en-route delay; the freight side minimizes the costs of train departure delay, en-route delay, loss of demand, and track maintenance. Bargaining in both complete and incomplete information settings are considered; the latter arises because the freight railroad may withhold its private cost information. With complete information, we find that the equilibrium payments proposed by the passenger rail agency and the host freight railroad will each be invariant to who initiates the payment bargaining, although the actual payment does depend on who is the initiator. The equilibrium schedule maximizes system welfare. With incomplete information, the passenger rail agency may choose between pooling and separating equilibrium strategies while proposing a payment, depending on its prior belief about the cost type of the freight railroad; whereas the host freight railroad will adopt strategies that do not reveal its cost type. To identify equilibrium schedules, a pooling equilibrium is constructed along with conditions for the existence of equilibrium schedules. We further conduct numerical experiments to obtain additional policy-relevant insights.

      PubDate: 2017-12-18T07:36:11Z
      DOI: 10.1016/j.trb.2017.12.001
      Issue No: Vol. 107 (2017)
  • Stochastic travel demand estimation: Improving network identifiability
           using multi-day observation sets
    • Authors: Yudi Yang; Yueyue Fan; Roger J.B. Wets
      Pages: 192 - 211
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Yudi Yang, Yueyue Fan, Roger J.B. Wets
      Stochastic travel demand estimation is essential to support many resilience and reliability based transportation network analyses. The problem of estimating travel demand based on sensor data often results in an ill-posed inverse problem, where solution uniqueness cannot be ensured. To overcome this challenge, effective utilization of more information/data, preferably from reliable sources, becomes critical. Conventional demand estimation methods often sacrifice system structural information during the process of compressing sensor data into its statistics. Loss of structural information, which captures critical relation between observed and estimated parameters, inevitably causes more dependence on unrealistic assumptions and unreliable data. Our model is designed to preserve all structural information contained from different observation sets and allow it to directly contribute to the identification of population parameters of travel demand. The proposed hierarchical framework integrates two traditionally distinctive identification problems, mean demand estimation and trip table reconstruction. Through mathematical analyses and numerical experiments, we show that the proposed framework improves parameter identifiability and leads to better estimation quality compared to conventional methods. The proposed framework is also flexible to accommodate a wide variety of travel behavior assumptions and estimation principles. As an example among many possible alternatives, Wardrop equilibrium based traffic assignment and generalized least square are implemented and tested using a case study based on a moderately large network.

      PubDate: 2017-12-27T07:47:07Z
      DOI: 10.1016/j.trb.2017.10.007
      Issue No: Vol. 107 (2017)
  • Advancements in continuous approximation models for logistics and
           transportation systems: 1996–2016
    • Authors: Sina Ansari; Mehmet Başdere; Xiaopeng Li; Yanfeng Ouyang; Karen Smilowitz
      Pages: 229 - 252
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Sina Ansari, Mehmet Başdere, Xiaopeng Li, Yanfeng Ouyang, Karen Smilowitz
      Continuous approximation (CA) is an efficient and parsimonious technique for modeling complex logistics problems. In this paper, we review recent studies that develop CA models for transportation, distribution and logistics problems with the aim of synthesizing recent advancements and identifying current research gaps. This survey focuses on important principles and key results from CA models. In particular, we consider how these studies fill the gaps identified by the most recent literature reviews in this field. We observe that CA models are used in a wider range of applications, especially in the areas of facility location and integrated supply chain management. Most studies use CA as an alternative and a complement to discrete solution approaches; however, CA can also be used in combination with discrete approaches. We conclude with promising areas of future work.

      PubDate: 2017-12-27T07:47:07Z
      DOI: 10.1016/j.trb.2017.09.019
      Issue No: Vol. 107 (2017)
  • Crowd behaviour and motion: Empirical methods
    • Authors: Milad Haghani; Majid Sarvi
      Pages: 253 - 294
      Abstract: Publication date: January 2018
      Source:Transportation Research Part B: Methodological, Volume 107
      Author(s): Milad Haghani, Majid Sarvi
      Introduction The safety of humans in crowded environments has been recognised as an important and rapidly growing research area with significant implications for urban planning, event management, building design, fire safety engineering and rescue service to name a few. This stream of research is aimed at guiding safe designs and effective evacuation plans by simulating emergency scenarios and estimating measures such as total evacuation time. A large body of research has also been dedicated to the development of modelling tools with the capability to identify (and thus prevent) circumstances that lead to crowd discomfort, crashes or disasters in mass gatherings and public facilities. It has, however, been argued that the empirical knowledge in this area has lagged behind the theoretical developments and computational capabilities. This has left the descriptive power of the existing models for reproducing the natural behaviour of humans questionable given that in many cases there is a lack of reliable and well-conditioned data for model validation or calibration purposes. Methods With the vast majority of the empirical knowledge in this fast-growing and interdisciplinary field being very recent, a survey of the existing literature is still missing. Here, we gather together the existing empirical knowledge in this area in a comprehensive review (based on surveying more than 160 studies restricted to those published in peer-reviewed journals since 1995) in order to help bridge this gap. We introduce for the first time a categorisation system of the relevant data collection techniques by recognising seven general empirical approaches. We also differentiate between various aspects of human behaviour pertinent to crowd behaviour by putting them into perspective in terms of three general levels of “decision making”. We also discuss the advantages and disadvantages offered by each data collection technique. Major gaps and poorly-explored topics in the current literature are discussed. Findings and applications Our major conclusion is that the empirical evidence in this area is largely disperse and even in some cases mixed and contradictory, requiring a more unified system of terminologies and problem definitions as well as unified measurement methods in order for the findings of different studies to become replicable and comparable. We also showed that the existing body of empirical studies display a clear imbalance in addressing various aspects of human behaviour with certain (but crucial) aspects (such as “pre-movement time” and “choice of activity”) being poorly understood (as opposed to our knowledge and amount of data about “walking behaviour” for example). Our review also revealed that previous studies have predominantly displayed a stronger tendency to study the behaviour based on aggregate measures as opposed to individual-level data collection attempts. We hope that this collection of findings sets clearer avenues for advancing the knowledge in this area, guides future experiment designs and helps researchers form better-informed hypotheses and choose most suitable data collection methods for their question in hand.
      Graphical abstract image

      PubDate: 2017-12-27T07:47:07Z
      DOI: 10.1016/j.trb.2017.06.017
      Issue No: Vol. 107 (2017)
  • Highway traffic state estimation per lane in the presence of connected
    • Authors: Nikolaos Bekiaris-Liberis; Claudio Roncoli; Markos Papageorgiou
      Pages: 1 - 28
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Nikolaos Bekiaris-Liberis, Claudio Roncoli, Markos Papageorgiou
      A model-based traffic state estimation approach is developed for per-lane density estimation as well as on-ramp and off-ramp flows estimation for highways in presence of connected vehicles. Three are the basic ingredients of the developed estimation scheme: (1) a data-driven version of the conservation-of-vehicles equation (in its time- and space-discretized form); (2) the utilization of position and speed information from connected vehicles’ reports, as well as total flow measurements obtained from a minimum number (sufficient for the observability of the model) of fixed detectors, such as, for example, at the main entry and exit of a given highway stretch; and (3) the employment of a standard Kalman filter. Furthermore, necessary and sufficient conditions for the (strong) structural observability of the introduced model are established (properties, which are rarely studied in the literature on traffic estimation), which yield the fixed detectors requirements needed for the proper operation of the developed estimation scheme. The performance of the estimation scheme is evaluated for various penetration rates of connected vehicles utilizing real microscopic traffic data collected within the Next Generation SIMulation (NGSIM) program. It is shown that the estimation performance is satisfactory, in terms of a suitable metric, even for low penetration rates of connected vehicles. The sensitivity of the estimation performance to variations of the model parameters (two in total) is also quantified, and it is shown that, overall, the estimation scheme is little sensitive to the model parameters.

      PubDate: 2017-11-16T13:06:14Z
      DOI: 10.1016/j.trb.2017.11.001
      Issue No: Vol. 106 (2017)
  • A heuristic method for a congested capacitated transit assignment model
           with strategies
    • Authors: Esteve Codina; Francisca Rosell
      Pages: 293 - 320
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Esteve Codina, Francisca Rosell
      This paper addresses the problem of solving the congested transit assignment problem with strict capacities. The model under consideration is the extension made by Cominetti and Correa (2001), for which the only solution method capable of resolving large transit networks is the one proposed by Cepeda et al. (2006). This transit assignment model was recently formulated by the authors as both a variational inequality problem and a fixed point inclusion problem. As a consequence of these results, this paper proposes an algorithm for solving the congested transit assignment problem with strict line capacities. The proposed method consists of using an MSA-based heuristic for finding a solution for the fixed point inclusion formulation. Additionally, it offers the advantage of always obtaining capacity-feasible flows with equal computational performance in cases of moderate congestion and with greater computational performance in cases of highly congested networks. A set of computational tests on realistic small- and large-scale transit networks under various congestion levels are reported, and the characteristics of the proposed method are analyzed.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.07.008
      Issue No: Vol. 106 (2017)
  • A metaheuristic for the multimodal network flow problem with product
           quality preservation and empty repositioning
    • Authors: M. SteadieSeifi; N.P. Dellaert; W. Nuijten; T. Van Woensel
      Pages: 321 - 344
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): M. SteadieSeifi, N.P. Dellaert, W. Nuijten, T. Van Woensel
      We study a transportation planning problem with multiple transportation modes, perishable products, and management of Reusable Transport Items (RTIs). This problem is inspired by the European horticultural chain. We present a Mixed Integer Programming (MIP) optimization model which is an extension of the Fixed-charge Capacitated Multicommodity Network Flow Problem (FCMNFP). The MIP integrates dynamic allocation, flow, and repositioning of the RTIs in order to find the trade-off between product freshness requirements, and operational circumstances and costs. We furthermore propose an Adaptive Large Neighborhood Search (ALNS) algorithm with new neighborhoods, and intensification and diversification strategies. We then provide detailed computational analysis on its properties, compare its results with a state-of-the-art MIP solver, and provide practical insights.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.07.007
      Issue No: Vol. 106 (2017)
  • The morning commute problem with ridesharing and dynamic parking charges
    • Authors: Rui Ma; H.M. Zhang
      Pages: 345 - 374
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Rui Ma, H.M. Zhang
      This paper studies the traffic flow patterns in a single bottleneck corridor with a dynamic ridesharing mode and dynamic parking charges. Schemes with different ridesharing payments and shared parking prices are investigated. Besides the scheme with constant parking charges and ridesharing payments, dynamic parking charges and ridesharing payments are derived to achieve congestion-free traffic in the corridor. With the dynamic ridesharing ratios, it is found that genuinely nonlinear departure rates and travel time functions can be generated in certain ridesharing cases, which was not observed in the traditional ADL model (Arnott et al., 1990) for the morning commute problems without ridesharing or with constant ridesharing ratios. Moreover, comparing different configurations of ridesharing arrangements and parking charges, the results show that constant parking charges with constant ridesharing payments may not significantly improve system performance over the traditional morning commute with solo-drivers, while dynamic parking charges with properly selected constant ridesharing payments can achieve better system performance in terms of vehicle-miles-traveled, vehicle-hours-traveled and total travel costs, by encouraging ridesharing and spreading vehicular demand over time to eliminate queuing delays.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.07.002
      Issue No: Vol. 106 (2017)
  • Planning of parking enforcement patrol considering drivers’ parking
           payment behavior
    • Authors: Chao Lei; Qian Zhang; Yanfeng Ouyang
      Pages: 375 - 392
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Chao Lei, Qian Zhang, Yanfeng Ouyang
      This paper focuses on improving the effectiveness of parking enforcement patrol by optimizing the schedule of visit at each parking lot and the routing plan of patrol vehicles. Meanwhile, individual parking driver makes his/her parking payment decision based on knowledge of the patrol visit frequencies. Game-theoretic models are proposed to capture the interactions among the parking enforcement agency and parking drivers. We first develop a discrete formulation of the problem in the form of a mixed-integer program and propose a Lagrangian relaxation based solution approach. For large-scale instances, we also develop a continuum approximation model that can be reduced to a simpler non-linear optimization problem. A series of numerical experiments are conducted to show that, for small problem instances, both modeling approaches can yield reasonable solutions, although the continuum approximation approach is able to produce a solution within a much shorter time. For large-scale instances, the discrete model incurs prohibitive computational burdens, while the continuum approximation approach still provides a near-optimum solution effectively. We also discuss impacts of various system parameters, as well as the performance of different policy options (e.g., whether to allow multiple parking tickets to be issued to a vehicle with a long time of parking violation).

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.07.001
      Issue No: Vol. 106 (2017)
  • Robust uncapacitated hub location
    • Authors: Carlos Armando Zetina; Ivan Contreras; Jean-François Cordeau; Ehsan Nikbakhsh
      Pages: 393 - 410
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Carlos Armando Zetina, Ivan Contreras, Jean-François Cordeau, Ehsan Nikbakhsh
      In this paper we present robust counterparts for uncapacitated hub location problems in which the level of conservatism can be controlled by means of a budget of uncertainty. We study three particular cases for which the parameters are subject to interval uncertainty: demand, transportation cost, and both simultaneously. We present mixed integer programming formulations for each of these cases and a branch-and-cut algorithm to solve the latter. We present computational results to evaluate the performance of the proposed formulations when solved with a general purpose solver and study the structure of the solutions to each of the robust counterparts. We also compare the performance between solutions obtained from a commensurable stochastic model and those from our robust counterparts in both risk neutral and worst-case settings.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.06.008
      Issue No: Vol. 106 (2017)
  • Co-Evolutionary path optimization by Ripple-Spreading algorithm
    • Authors: Xiao-Bing Hu; Ming-Kong Zhang; Qi Zhang; Jian-Qin Liao
      Pages: 411 - 432
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Xiao-Bing Hu, Ming-Kong Zhang, Qi Zhang, Jian-Qin Liao
      Static path optimization (SPO) is a foundation of computational intelligence, but in reality, the routing environment is usually time-varying (e.g., moving obstacles, spreading disasters and uncertainties). Thanks to scientific and technical advances in many relevant domains nowadays, changes in the routing environment are often more or less predictable. This study mainly focuses on path optimization in a given dynamic routing environment (POGDRE). A common practice to deal with dynamic routing environment is to conduct online re-optimization (OLRO), i.e., at each time t, environmental parameters are measured/predicted first, and then the best path is re-calculated by resolving SPO based on the newly measured/predicted environmental parameters. In theory, POGDRE is equivalent to time-dependent path optimization (TDPO), which is usually resolved as SPO on a time-expanded hypergraph (TEHG) with a significantly enlarged size. In other words, during a single online run of OLRO-based methods or a single run of TEHG-based methods, the route network is actually fixed and static. Inspired by the multi-agent co-evolving nature reflected in many methods of evolutionary computation, this paper proposes a methodology of co-evolutionary path optimization (CEPO) to resolve the POGDRE. Distinguishing from OLRO and TEHG methods, in CEPO, future routing environmental parameters keep changing during a single run of optimization on a network of original size. In other words, the routing environment co-evolves with the path optimization process within a single run. This paper then reports a ripple-spreading algorithm (RSA) as a realization of CEPO to resolve the POGDRE with both optimality and efficiency. In just a single run of RSA, the optimal actual travelling trajectory can be achieved in a given dynamic routing environment. Simulation results clearly demonstrate the effectiveness and efficiency of the proposed CEPO and RSA for addressing the POGDRE.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.06.007
      Issue No: Vol. 106 (2017)
  • Dynamic optimal real-time algorithm for signals (DORAS): Case of isolated
           roadway intersections
    • Authors: Xiubin Bruce Wang; Xiaowei Cao; Changjun Wang
      Pages: 433 - 446
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Xiubin Bruce Wang, Xiaowei Cao, Changjun Wang
      This paper studies intersection signal control in which traffic arrivals from all approaches along with the queues are assumed known. The control policy minimizes the overall intersection delay by deciding the green intervals for signal phases dynamically as driven by real-time traffic but subject to a set of constraints such as min/max green time for each phase. This paper models intersection vehicle delay by assuming continuous vehicle arrival and departure, and presents the optimal condition for green signal switch. Prior to this work, there does not appear to have been a continuous model on optimal control applied to the general intersection. Two numerical algorithms are proposed: optimum based (DORAS) and queue-based heuristic (DORAS-Q) respectively. Numerical tests are conducted via discrete simulation using an actual intersection data covering peak, mid-day and mid-night hours, respectively. Comparison is conducted between actuated, DORAS, DORAS-Q and OPAC III. The tests show that the latter three methods all perform significantly better than the actuated.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.06.005
      Issue No: Vol. 106 (2017)
  • The optimal time to evacuate: A behavioral dynamic model on Louisiana
           resident data
    • Authors: Nayel Urena Serulle; Cinzia Cirillo
      Pages: 447 - 463
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Nayel Urena Serulle, Cinzia Cirillo
      Understanding what affects the decision process leading to evacuation of a population at risk from the threat of a disaster is of upmost importance to successfully implement emergency planning policies. Literature on this is broad; however, the vast majority of behavioral models is limited to conventional structures, such as aggregate participation rate models or disaggregate multinomial logit models. This research introduces a dynamic discrete choice model that takes into account the threat's characteristics and the population's expectation of them. The proposed framework is estimated using Stated Preference (SP) evacuation data collected from Louisiana residents. The results indicate that the proposed dynamic discrete choice model outperforms sequential logit, excels in incorporating demographic information of respondents, a key input in policy evaluation, and yields significantly more accurate predictions of the decision and timing to evacuate.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.06.004
      Issue No: Vol. 106 (2017)
  • Exogenous priority rules for the capacitated passenger assignment problem
    • Authors: Stefan Binder; Yousef Maknoon; Michel Bierlaire
      Pages: 19 - 42
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Stefan Binder, Yousef Maknoon, Michel Bierlaire
      We propose a novel algorithm for the capacitated passenger assignment problem in public transportation where exogenous priority lists define the order in which passengers are assigned. Separating explicitly theses rules from the assignment procedure allows for a great deal of flexibility to model various priority rules. When the actual rules are endogenous, the framework can easily be embedded in a fixed-point specification. Computational experiments are performed on a realistic case study based on the morning rush hours of the timetable of Canton Vaud, Switzerland. The algorithm is able to assign the demand in very low computational times. The results provide evidences that the ordering of the passengers does not have a significant impact on aggregate performance indicators (such as average delay and level of unsatisfied demand), but that the variability at the individual passenger level is substantial. Thanks to its flexibility, our framework can easily be implemented by a railway operator who wishes to evaluate the effects of different policies in terms of passenger priorities.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.022
      Issue No: Vol. 105 (2017)
  • A subjective capacity evaluation model for single-track railway system
           with δ-balanced traffic and λ-tolerance level
    • Authors: Feng Li; Ziyou Gao; David Z.W. Wang; Ronghui Liu; Tao Tang; Jianjun Wu; Lixing Yang
      Pages: 43 - 66
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Feng Li, Ziyou Gao, David Z.W. Wang, Ronghui Liu, Tao Tang, Jianjun Wu, Lixing Yang
      In this paper, we propose a method to measure the capacity of single-track railway corridors subject to a given degree of balance between the two directional traffic loads and a permitted overall delay level. We introduce the concepts of δ-balance degree and λ-tolerance level to reflect the subjective measures of the railway administrator for capacity evaluation. A train balance scheduling problem with initial departure time choice of trains is embedded into the measure of railway capacity. The combined scheduling and capacity evaluation method is formulated as a 0-1 mixed integer programming model, and solved using a simple dichotomization-based heuristic method. A highly efficient heuristic procedure based on the concept of compaction pattern is developed to solve the train balance scheduling problem, and the numerical results demonstrate that the method yields high-quality solutions close to the optimal ones using the CPLEX solver. The two-way traffic loading capacity of a single-track railway corridor is analyzed in detail under different tolerance levels and balance degrees. The transition regions of traffic loading capacity are identified, and provide a useful decision support tool for the railway administrators in dealing with train rescheduling requests under disturbance or disruption scenarios.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.020
      Issue No: Vol. 105 (2017)
  • A new solution framework for the limited-stop bus service design problem
    • Authors: Guillermo Soto; Homero Larrain; Juan Carlos Muñoz
      Pages: 67 - 85
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Guillermo Soto, Homero Larrain, Juan Carlos Muñoz
      Limited-stop services are a key element to the successful operation of bus rapid transit corridors. In this study, we present a framework for addressing the limited-stop service design problem over a corridor, and formally introduce a family of subproblems involved in its solution. Using a bi-level optimization approach, we introduce a method of designing these services while considering bus capacity, transfers, and two behavioral models for passengers: deterministic and stochastic. The algorithm and its variants were tested on nine scenarios with up to 80 stops. Working with deterministic passenger assignment, our model solved the problem in a small fraction of the time required by a benchmark algorithm. We use this algorithm to show that neglecting transfers can lead to suboptimal solutions. We finally show that although it makes the problem much harder, working with stochastic assignment leads to more realistic and robust solutions.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.026
      Issue No: Vol. 105 (2017)
  • Exact and approximate route set generation for resilient partial
           observability in sensor location problems
    • Authors: Marco Rinaldi; Francesco Viti
      Pages: 86 - 119
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Marco Rinaldi, Francesco Viti
      Sensor positioning is a fundamental problem in transportation networks, as the location of sensors strongly determines how traffic flows are observable and hence manageable. This paper aims to develop a methodology to determine sensor locations on a network such that an optimal trade-off solution is found between the amount of sensors installed and the resilience of the sensor set. In particular, we propose exact and heuristic solutions for identifying the optimal route sets such that no other route would include any additional information for finding optimal full and partial observability solutions. This is an important contribution to sensor location problems, as route-based link flow inference problems have non-unique solutions, strongly depending on the used link-route information. The properties of the new methodology are analyzed and illustrated through different case studies, and the advantages of the algorithms are quantified both for full and for partial observability solutions. Due to the route sets found by our approach, we are able to find full observability solutions characterized by a small number of sensors, while yet being efficient also in terms of partial observability. We perform validation tests on both small and real-life sized network instances.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.007
      Issue No: Vol. 105 (2017)
  • An approach to transportation network analysis via transferable utility
    • Authors: Yuval Hadas; Giorgio Gnecco; Marcello Sanguineti
      Pages: 120 - 143
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Yuval Hadas, Giorgio Gnecco, Marcello Sanguineti
      Network connectivity is an important aspect of any transportation network, as the role of the network is to provide a society with the ability to easily travel from point to point using various modes. A basic question in network analysis concerns how “important” each node is. An important node might, for example, greatly contribute to short connections between many pairs of nodes, handle a large amount of the traffic, generate relevant information, represent a bridge between two areas, etc. In order to quantify the relative importance of nodes, one possible approach uses the concept of centrality. A limitation of classical centrality measures is the fact that they evaluate nodes based on their individual contributions to the functioning of the network. The present paper introduces a game theory approach, based on cooperative games with transferable utility. Given a transportation network, a game is defined taking into account the network topology, the weights associated with the arcs, and the demand based on an origin-destination matrix (weights associated with nodes). The network nodes represent the players in such a game. The Shapley value, which measures the relative importance of the players in transferable utility games, is used to identify the nodes that have a major role. For several network topologies, a comparison is made with well-known centrality measures. The results show that the suggested centrality measures outperform the classical ones, and provide an innovative approach for transportation network analysis.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.029
      Issue No: Vol. 105 (2017)
  • Multi-periodic train timetabling using a period-type-based Lagrangian
           relaxation decomposition
    • Authors: Wenliang Zhou; Junli Tian; Lijuan Xue; Min Jiang; Lianbo Deng; Jin Qin
      Pages: 144 - 173
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Wenliang Zhou, Junli Tian, Lijuan Xue, Min Jiang, Lianbo Deng, Jin Qin
      To provide passengers with strict regularity of train operation, this research is devoted to modeling and solving the multi-periodic train timetabling problem to simultaneously optimize operation periods, arrival times, and departure times of all period types of trains on a double-track rail network. Based on the construction of a weighted directed graph, a multi-path searching model, namely, a 0-1 linear programming model, is built to minimize the total travel time of all period-types of trains subject to many operational constraints, including station parking capacity and train minimum load factors. After decomposing this model by introducing some Lagrangian multipliers to relax its complicated constraints, a solution algorithm, including a multi-path simultaneous searching sub-algorithm for each period-type of train, is designed to optimize both the feasible and dual solutions, which correspond to the upper and lower bounds, respectively. Finally, the performance, convergence, sensitivity, and practicability of our method are analyzed using many instances on both a small rail network and the high-speed railway between Beijing and Shanghai in China.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.005
      Issue No: Vol. 105 (2017)
  • Dynamic equilibrium at a congestible facility under market power
    • Authors: Erik T. Verhoef; Hugo E. Silva
      Pages: 174 - 192
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Erik T. Verhoef, Hugo E. Silva
      This paper studies equilibrium and optimum at a congested facility when firms have market power; e.g., when a few airlines jointly use a congested airport. Unlike most of the previous literature, we characterize the equilibrium in terms of timing of arrivals in a continuous-time congestion model when firms simultaneously schedule services. Using the Henderson-Chu dynamic model of flow congestion in a multiple-firm setting, we find that a stable and unique Nash equilibrium in pure strategies always exists. Importantly, it also exists in cases where it fails to exist under bottleneck congestion (notably when the value of schedule late exceeds the value of travel delays). We find that symmetric firms schedule arrivals inefficiently, and strongly concentrated around the desired arrival time so that the peak is shorter and delays are higher than socially optimal. We show that when firms are asymmetric in terms of output, all firms schedule vehicles in the peak center, around the desired arrival time, with arrival windows increasing with firm size such that a smaller firm's window is always fully contained in a larger firm's window and only the largest firm operates in the early and late shoulders. Furthermore, for any pair of asymmetric firms, the larger firm has a higher instantaneous arrival rate at any moment where both firms schedule arrivals. Our results also show that even though self-internalization can be substantial, there is scope for decentralizing the first-best outcome through time-varying tolls.

      PubDate: 2017-09-06T23:31:02Z
      DOI: 10.1016/j.trb.2017.08.028
      Issue No: Vol. 105 (2017)
  • Group-based hierarchical adaptive traffic-signal control part I:
    • Authors: Seunghyeon Lee; S.C. Wong; Pravin Varaiya
      Pages: 376 - 397
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Seunghyeon Lee, S.C. Wong, Pravin Varaiya
      A group-based adaptive traffic-control method for isolated signalized junctions is developed that includes a hierarchical structure comprising tactical and local levels of signal timing optimization. The control method optimizes the signal timings in adaptive traffic-control systems, and takes full advantage of flexible new technologies to incorporate the most up-to-date traffic information, as collected in real time. The definitions, combinations, and sequencing of the cycle structure stages are generated automatically using a procedure for optimizing the signal-timing plans in response to online data from traffic detectors. This new method provides a wider search space and improves the efficiency of the signal-control systems, thus improving the junction performance, minimizing delays, and maximizing capacity in real time. A multi-resolution strategy is proposed for updating the elements of the signal plans cycle-by-cycle and adjusting the current green signal timing second-by-second. The group-based variables and parameters for the proactive global-optimization method utilize lane-based predictive traffic-flow information, such as arrival and discharge rates, expressed as the slopes of polygonal delay formulas. Therefore, there is a high degree of flexibility in the tactical identification of the optimal signal plan in response to the real-time predicted traffic information, the objective function of the polygonal delay formula, and the direct differential equations for the adaptive group-based variables. The reactive local signal-control policy, which is formed based on the max-pressure strategy, is developed to locally adjust the current green signal time and to accommodate delicate demand fluctuations second-by-second at the fine-resolution level. The most appropriate cycle-structure for the tactical level of control is identified using a group-based global-optimization procedure that takes advantage of the latest available information. In part II of this study (Lee et al. 2017), the effectiveness of the proposed methods is validated based on the actualized mathematical frameworks, computer simulations, and a case study, using the appropriate computer programs.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.009
      Issue No: Vol. 104 (2017)
  • A linear framework for dynamic user equilibrium traffic assignment in a
           single origin-destination capacitated network
    • Authors: Nam H. Hoang; Hai L. Vu; Manoj Panda; Hong K. Lo
      Abstract: Publication date: Available online 11 December 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Nam H. Hoang, Hai L. Vu, Manoj Panda, Hong K. Lo
      The dynamic traffic assignment (DTA) problem has been studied intensively in the literature. However, there is no existing linear framework to solve the user equilibrium (UE) DTA problem. In this paper, we develop a novel linear programming framework to solve the UE-DTA problem in a dynamic capacity network that exploits the linkage between the UE and system optimal (SO) solutions underpinned by a first-in-first-out (FIFO) principle. This important property enables us to develop an incremental loading method to obtain the UE solutions efficiently by solving a sequence of linear programs. The proposed solution methodology possesses several nice properties such as a predictable number of iterations before reaching the UE solution, and a linear system of equations to be solved in each of the iterations. In contrast to the related iterative methods, such as Frank–Wolfe algorithm, successive average (MSA) or projection and their extensions where the purpose of iteration is to seek the solution convergence, whereas ours is to solve a linear problem over multiple iterations but only for a single unit of demand in each iteration. Furthermore, we provide a theoretical proof that in the limit, the SO objective can be used to obtain the UE solution as the system time step goes to zero given the satisfaction of the FIFO constraint. We show via numerical examples the significant improvements in the obtained UE solutions both in terms of accuracy and computational complexity.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.013
  • Reliable sensor location for object positioning and surveillance via
    • Authors: Kun An; Siyang Xie; Yanfeng Ouyang
      Abstract: Publication date: Available online 6 December 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Kun An, Siyang Xie, Yanfeng Ouyang
      Object positioning and surveillance has been playing an important role in various indoor location-aware applications. Signal attenuation or blockage often requires multiple local sensors to be used jointly to provide coverage and determine object locations via mobile devices. The deployment of sensors has a significant impact on the accuracy of positioning and effectiveness of surveillance. In this paper, we develop a reliable sensor location model that aims at optimizing the location of sensors so as to maximize the accuracy of object positioning/surveillance under the risk of possible sensor disruptions. We formulate the problem as a mixed-integer linear program and develop solution approaches based on a customized Lagrangian relaxation algorithm with an embedded approximation subroutine. A series of hypothetical examples and a real-world Wi-Fi access point design problem for Chicago O’Hare Airport Terminal 5 are used to demonstrate the applicability of the model and solution algorithms. Managerial insights are also presented.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.012
  • On joint railway and housing development: Housing-led versus railway-led
    • Authors: Fai Hong
      Abstract: Publication date: December 2017
      Source:Transportation Research Part B: Methodological, Volume 106
      Author(s): Ka Fai Ng, Hong K. Lo
      This paper develops a time-dependent framework to analyze the revenues and costs of housing and railway developments over time in a Transit Oriented Development, explicitly capturing the housing and railway development phasing. A bi-level mathematical program is formulated, in which the upper level optimizes the housing supply and railway development over time based on the perspective of a joint housing and railway developer, versus that of consumers and that of government. At the lower level, a nested logit framework is formulated to model the combined bid-rent process, residents’ location and travel choices in each period. Under certain assumptions, this study derives analytically the lead-lag relationships between housing development and railway development, based on the initial housing and transport conditions, as well as the stakeholders’ perspectives. The development strategies are generally different among the stakeholders, whilst possible win-win situations, in terms of developer profitability and consumer surplus, are identified under certain low housing density conditions, leading to a social optimum. This study also conducts sensitivity analyses to extend the results to multiple time periods and heterogeneous income classes, revealing that, for profitability, the joint developer may introduce housing development phasing that segregates residents of different income classes.

      PubDate: 2017-12-12T10:59:18Z
  • Interactive online machine learning approach for activity-travel survey
    • Authors: Toru Seo; Takahiko Kusakabe; Hiroto Gotoh; Yasuo Asakura
      Abstract: Publication date: Available online 1 December 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Toru Seo, Takahiko Kusakabe, Hiroto Gotoh, Yasuo Asakura
      This article proposes a framework for an interactive activity-travel survey method, implementable on mobile devices such as smartphones. The proposed method was developed to reduce the burden (i.e., frequency of questions) on respondents in long-term behavioral surveys, without relying on external data sources. The method employs an online travel context estimation model and an online machine learning method as interactive processes. The estimation model is used for automatically estimating travel contexts during surveys, while the online machine learning method is used for dynamically updating the estimation model, based on answers from respondents. The proposed method was examined by simulations using data obtained from a past probe person survey. The results suggest that the frequency of inputs by respondents in surveys can be significantly reduced, while maintaining high accuracy of the obtained data. For example, the method successfully estimated certain types of trips (e.g., commuting) and the behaviors of certain respondents (e.g., those whose activity-travel pattern is recurrent) because of the learning process and reduced survey burden on them. Meanwhile, although the method could not always precisely estimate some other types of trips, it eventually obtained accurate results because of the interaction process. Therefore, the proposed method could be useful to reduce the burden on respondents in long-term surveys, while maintaining high data quality and capturing traveler heterogeneity.

      PubDate: 2017-12-12T10:59:18Z
      DOI: 10.1016/j.trb.2017.11.009
  • Random taste heterogeneity in discrete choice models: Flexible
           nonparametric finite mixture distributions
    • Authors: Akshay Vij; Rico Krueger
      Abstract: Publication date: Available online 10 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Akshay Vij, Rico Krueger
      This study proposes a mixed logit model with multivariate nonparametric finite mixture distributions. The support of the distribution is specified as a high-dimensional grid over the coefficient space, with equal or unequal intervals between successive points along the same dimension; the location of each point on the grid and the probability mass at that point are model parameters that need to be estimated. The framework does not require the analyst to specify the shape of the distribution prior to model estimation, but can approximate any multivariate probability distribution function to any arbitrary degree of accuracy. The grid with unequal intervals, in particular, offers greater flexibility than existing multivariate nonparametric specifications, while requiring the estimation of a small number of additional parameters. An expectation maximization algorithm is developed for the estimation of these models. Multiple synthetic datasets and a case study on travel mode choice behavior are used to demonstrate the value of the model framework and estimation algorithm. Compared to extant models that incorporate random taste heterogeneity through continuous mixture distributions, the proposed model provides better out-of-sample predictive ability. Findings reveal significant differences in willingness to pay measures between the proposed model and extant specifications. The case study further demonstrates the ability of the proposed model to endogenously recover patterns of attribute non-attendance and choice set formation.

      PubDate: 2017-11-16T13:06:14Z
      DOI: 10.1016/j.trb.2017.10.013
  • Planning of truck platoons: A literature review and directions for future
    • Authors: Anirudh Kishore; Bhoopalam Niels Agatz Rob Zuidwijk
      Abstract: Publication date: Available online 10 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Anirudh Kishore Bhoopalam, Niels Agatz, Rob Zuidwijk
      A truck platoon is a set of virtually linked trucks that drive closely behind one another using automated driving technology. Benefits of truck platooning include cost savings, reduced emissions, and more efficient use of road capacity. To fully reap these benefits in the initial phases of technology deployment, careful planning of platoons based on trucks’ itineraries and time schedules is required. This paper provides a framework to classify various new transportation planning problems that arise in truck platooning, surveys relevant operations research models for these problems in the literature and identifies directions for future research.

      PubDate: 2017-11-16T13:06:14Z
  • Fundamental diagrams of airport surface traffic: Models and applications
    • Authors: Lei Yang; Suwan Yin; Ke Han; Jack Haddad; Minghua Hu
      Abstract: Publication date: Available online 8 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Lei Yang, Suwan Yin, Ke Han, Jack Haddad, Minghua Hu
      This paper reveals and explores the flow characteristics of airport surface network on both mesoscopic and macroscopic levels. We propose an efficient modeling approach based on the cell transmission model for simulating the spatio-temporal evolution of flow and congestion on taxiway and apron networks. The existence of link-based fundamental diagram that expresses the functional relationship between link density and flow is demonstrated using empirical data collected in Guangzhou Baiyun airport. The proposed CTM-based network model is shown to be an efficient and accurate method capable of supporting air traffic prediction and decision support. In addition, using both CTM-based simulation and empirical data, we further reveal the existence of an aggregate relationship between traffic density and runway throughput, which is referred to as macroscopic fundamental diagram (MFD) in the literature of road traffic. The MFD on the airport surface is analyzed in depth, and utilized to devise several robust off-block control strategies under uncertainties, which are shown to significantly outperform existing off-block control methods.

      PubDate: 2017-11-09T06:47:03Z
      DOI: 10.1016/j.trb.2017.10.015
  • A practical method to test the validity of the standard Gumbel
           distribution in logit-based multinomial choice models of travel behavior
    • Authors: Xin Ye; Venu M. Garikapati; Daehyun You; Ram M. Pendyala
      Abstract: Publication date: Available online 8 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Xin Ye, Venu M. Garikapati, Daehyun You, Ram M. Pendyala
      Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basis of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.

      PubDate: 2017-11-09T06:47:03Z
      DOI: 10.1016/j.trb.2017.10.009
  • Daily berth planning in a tidal port with channel flow control
    • Authors: Lu Zhen; Zhe Liang; Dan Zhuge; Loo Hay Lee; Ek Peng Chew
      Abstract: Publication date: Available online 7 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Lu Zhen, Zhe Liang, Dan Zhuge, Loo Hay Lee, Ek Peng Chew
      This paper studies an operational-level berth allocation and quay crane assignment problem (daily berth planning) considering tides and channel flow control constraints. An integer programming model is proposed for this problem. Then a column generation solution approach is developed on a set partitioning based reformulation of the original model. Computational study is conducted on 30 test cases constructed from real-world data to validate efficiency of the proposed solution approach. Results show that this simple but practical solution approach can optimally solve the daily berthing planning problem instances with up to 80 vessels, 40 berths, and 120 quay cranes within one hour, which is reasonable and acceptable for the real-world applications. The proposed decision model and the solution approach could be potentially useful for some tidal ports with (or without) navigation channels.

      PubDate: 2017-11-09T06:47:03Z
      DOI: 10.1016/j.trb.2017.10.008
  • A real-time algorithm to solve the peer-to-peer ride-matching problem in a
           flexible ridesharing system
    • Authors: Neda Masoud; R. Jayakrishnan
      Abstract: Publication date: Available online 2 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Neda Masoud, R. Jayakrishnan
      Real-time peer-to-peer ridesharing is a promising mode of transportation that has gained popularity during the recent years thanks to the wide-spread use of smart phones, mobile application development platforms, and online payment systems. An assignment of drivers to riders, known as the ride-matching problem, is a central component of a peer-to-peer ridesharing system. In this paper we discuss the features of a flexible ridesharing system and propose an algorithm to optimally solve the ride-matching problem in a flexible ridesharing system in real-time. We generate random instances of the problem, and perform sensitivity analysis over some of the important parameters in a ridesharing system. Furthermore, we discuss two novel approaches to increase the performance of a ridesharing system.

      PubDate: 2017-11-09T06:47:03Z
      DOI: 10.1016/j.trb.2017.10.006
  • First-order traffic flow models incorporating capacity drop: Overview and
           real-data validation
    • Authors: Maria Kontorinaki; Anastasia Spiliopoulou; Claudio Roncoli; Markos Papageorgiou
      Abstract: Publication date: Available online 2 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Maria Kontorinaki, Anastasia Spiliopoulou, Claudio Roncoli, Markos Papageorgiou
      First-order traffic flow models of the LWR (Lighthill-Whitham-Richards) type are known for their simplicity and computational efficiency and have, for this reason, been widely used for various traffic engineering tasks. However, these first-order models are not able to reproduce significant traffic phenomena of great interest, such as the capacity drop and stop-and-go waves. This paper presents an overview of modeling approaches, which introduce the ability to reflect the capacity-drop phenomenon into discretized LWR-type first-order traffic flow models; and also proposes a new approach. The background and main characteristics of each approach are analyzed with particular emphasis on the practical applicability of such models for traffic simulation, management and control. The presented modeling approaches are tested and validated using real data from a motorway network in the U.K.

      PubDate: 2017-11-09T06:47:03Z
      DOI: 10.1016/j.trb.2017.10.014
  • Dynamic programming-based multi-vehicle longitudinal trajectory
           optimization with simplified car following models
    • Authors: Yuguang Wei; Cafer Avcı; Jiangtao Liu; Baloka Belezamo; Nizamettin Aydın; Pengfei(Taylor) Li; Xuesong Zhou
      Abstract: Publication date: Available online 2 November 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Yuguang Wei, Cafer Avcı, Jiangtao Liu, Baloka Belezamo, Nizamettin Aydın, Pengfei(Taylor) Li, Xuesong Zhou
      Jointly optimizing multi-vehicle trajectories is a critical task in the next-generation transportation system with autonomous and connected vehicles. Based on a space-time lattice, we present a set of integer programming and dynamic programming models for scheduling longitudinal trajectories, where the goal is to consider both system-wide safety and throughput requirements under supports of various communication technologies. Newell's simplified linear car following model is used to characterize interactions and collision avoidance between vehicles, and a control variable of time-dependent platoon-level reaction time is introduced in this study to reflect various degrees of vehicle-to-vehicle or vehicle-to-infrastructure communication connectivity. By adjusting the lead vehicle's speed and platoon-level reaction time at each time step, the proposed optimization models could effectively control the complete set of trajectories in a platoon, along traffic backward propagation waves. This parsimonious multi-vehicle state representation sheds new lights on forming tight and adaptive vehicle platoons at a capacity bottleneck. We examine the principle of optimality conditions and resulting computational complexity under different coupling conditions.

      PubDate: 2017-11-09T06:47:03Z
      DOI: 10.1016/j.trb.2017.10.012
  • A mixed traffic capacity analysis and lane management model for connected
           automated vehicles: A Markov chain method
    • Authors: Amir Ghiasi; Omar Hussain; Zhen (Sean) Qian; Xiaopeng Li
      Abstract: Publication date: Available online 31 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Amir Ghiasi, Omar Hussain, Zhen (Sean) Qian, Xiaopeng Li
      The projected rapid growth of the market penetration of connected and autonomous vehicle technologies (CAV) highlights the need for preparing sufficient highway capacity for a mixed traffic environment where a portion of vehicles are CAVs and the remaining are human-driven vehicles (HVs). This study proposes an analytical capacity model for highway mixed traffic based on a Markov chain representation of spatial distribution of heterogeneous and stochastic headways. This model captures not only the full spectrum of CAV market penetration rates but also all possible values of CAV platooning intensities that largely affect the spatial distribution of different headway types. Numerical experiments verify that this analytical model accurately quantifies the corresponding mixed traffic capacity at various settings. This analytical model allows for examination of the impact of different CAV technology scenarios on mixed traffic capacity. We identify sufficient and necessary conditions for the mixed traffic capacity to increase (or decrease) with CAV market penetration rate and platooning intensity. These theoretical results caution scholars not to take CAVs as a sure means of increasing highway capacity for granted but rather to quantitatively analyze the actual headway settings before drawing any qualitative conclusion. This analytical framework further enables us to build a compact lane management model to efficiently determine the optimal number of dedicated CAV lanes to maximize mixed traffic throughput of a multi-lane highway segment. This optimization model addresses varying demand levels, market penetration rates, platooning intensities and technology scenarios. The model structure is examined from a theoretical perspective and an analytical approach is identified to solve the optimal CAV lane number at certain common headway settings. Numerical analyses illustrate the application of this lane management model and draw insights into how the key parameters affect the optimal CAV lane solution and the corresponding optimal capacity. This model can serve as a useful and simple decision tool for near future CAV lane management.

      PubDate: 2017-11-02T00:43:01Z
      DOI: 10.1016/j.trb.2017.09.022
  • A real-time conflict solution algorithm for the train rescheduling problem
    • Authors: Andrea Bettinelli; Alberto Santini; Daniele Vigo
      Abstract: Publication date: Available online 28 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Andrea Bettinelli, Alberto Santini, Daniele Vigo
      We consider the real-time resolution of conflicts arising in real-world train management applications. In particular, given a nominal timetable for a set of trains and a set of modifications due to delays or other resources unavailability, we are aiming at defining a set of actions which must be implemented to grant safety, e.g., to avoid potential conflicts such as train collisions or headway violations, and restore quality by reducing the delays. To be compatible with real-time management, the required actions must be determined in a few seconds, hence specialized fast heuristics must be used. We propose a fast and effective parallel algorithm that is based on an iterated greedy scheduling of trains on a time-space network. The algorithm uses several sortings to define the initial train dispatching rule and different shaking methods between iterations. The performance is further enhanced by using various sparsification methods for the time-space network. The best algorithm configuration is determined through extensive experiments, conducted on a set of instances derived from real-world networks and instances from the literature. The resulting heuristic proved able to consistently resolve the existing conflicts and obtaining excellent solution quality within just two seconds of computing time on a standard personal computer, for instances involving up to 151 trains and two hours of planning time horizon.

      PubDate: 2017-11-02T00:43:01Z
      DOI: 10.1016/j.trb.2017.10.005
  • Benders-and-Price approach for electric vehicle charging station location
           problem under probabilistic travel range
    • Authors: Chungmok Lee; Jinil Han
      Abstract: Publication date: Available online 28 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Chungmok Lee, Jinil Han
      This paper investigates the optimal locations for refueling stations for electric vehicles. Electric vehicles have been successfully introduced into the market. However, their use seems to be limited to urban transport since recharging facilities are readily available only near home and work. Planning recharging infrastructure for electric vehicles is highly relevant because this will enable longer trips, including inter-state travel which requires multiple battery charges. Among various models to determine optimal locations of recharging stations, a flow refueling location model (FRLM) is considered in this study. It determines locations for recharging stations to maximize the flow that can travel between origin and destination pairs by refueling at built facilities. FRLM is extended by introducing a probabilistic consideration of the travel range which might vary depending on various factors including road conditions. We develop a mixed integer nonlinear programming formulation and propose a Benders-and-Price algorithm by combining the Benders decomposition and column generation to solve the proposed formulation. The proposed algorithm is validated using extensive computational experiments on two transport networks, including a real-life Texas highway network.

      PubDate: 2017-11-02T00:43:01Z
      DOI: 10.1016/j.trb.2017.10.011
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