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  Subjects -> TRANSPORTATION (Total: 169 journals)
    - AIR TRANSPORT (8 journals)
    - AUTOMOBILES (22 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (6 journals)
    - SHIPS AND SHIPPING (33 journals)
    - TRANSPORTATION (95 journals)

TRANSPORTATION (95 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 83)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 2)
Archives of Transport     Open Access   (Followers: 16)
Botswana Journal of Technology     Full-text available via subscription  
Case Studies on Transport Policy     Hybrid Journal   (Followers: 10)
Cities in the 21st Century     Open Access   (Followers: 13)
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: 10)
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: 2)
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: 9)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 10)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 11)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 14)
International Journal of Transportation Science and Technology     Full-text available via subscription   (Followers: 10)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
International Journal of Vehicular Technology     Open Access   (Followers: 4)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 11)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 5)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 199)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 11)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 1)
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: 21)
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: 15)
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 & 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: 15)
Open Journal of Safety Science and Technology     Open Access   (Followers: 7)
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: 12)
Public Transport     Hybrid Journal   (Followers: 18)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 4)
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: 13)
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: 26)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 12)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 3)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 32)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 29)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 20)
Transportation Research Procedia     Open Access   (Followers: 4)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 34)
Transportation Science     Full-text available via subscription   (Followers: 20)
TRANSPORTES     Open Access   (Followers: 5)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 5)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 2)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 5)
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]   [29 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0191-2615
   Published by Elsevier Homepage  [3043 journals]
  • A two-stage stochastic optimization model for scheduling electric vehicle
           charging loads to relieve distribution-system constraints
    • Authors: Fei Wu; Ramteen Sioshansi
      Pages: 354 - 376
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Fei Wu, Ramteen Sioshansi
      Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival times and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. We demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. We also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.

      PubDate: 2017-05-26T09:34:30Z
      DOI: 10.1016/j.trd.2017.04.035
      Issue No: Vol. 53 (2017)
  • Discrete-time day-to-day dynamic congestion pricing scheme considering
           multiple equilibria
    • Authors: Linghui Han; David Z.W. Wang; Hong K. Lo; Chengjuan Zhu; Xingju Cai
      Pages: 1 - 16
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Linghui Han, David Z.W. Wang, Hong K. Lo, Chengjuan Zhu, Xingju Cai
      In this study, we focus on the discrete-time day-to-day dynamic congestion pricing scheme which varies the toll on a day-to-day basis and aims to drive the traffic system to a given objective traffic equilibrium state. As is well known, due to the asymmetric nature of the travel cost functions, multiple equilibria exist. In this case, without external force, the traffic system cannot converge to the traffic equilibrium state as desired by traffic management through a day-to-day adjustment process if the initial traffic state does not fall into its attraction domain (Bie and Lo, 2010). Therefore, it is imperative for traffic management to propose a traffic control measure to ensure the desired traffic state can be achieved regardless of the initial traffic state. Previous studies on the day-to-day dynamic congestion pricing, either worked on continues-time day-to-day pricing scheme, or took the form of discrete-time day-to-day pricing scheme but did not guarantee the convergence to the desired objective traffic state for the cases when multiple traffic equilibria exist. Both are undesirable. This study aims to develop a discrete-time day-to-day pricing scheme so as to direct the traffic evolution to reach the desired equilibrium from any initial traffic state when multiple traffic equilibria exist. Based on the very general formulation of day-to-day traffic dynamics model, we present a general formulation of such day-to-day pricing schemes and propose a method to obtain one specific road pricing scheme. Moreover, we present rigorous proofs and numerical tests to verify the proposed pricing scheme.

      PubDate: 2017-06-27T03:32:32Z
      DOI: 10.1016/j.trb.2017.06.006
      Issue No: Vol. 104 (2017)
  • Determining optimal locations for charging stations of electric
           car-sharing systems under stochastic demand
    • Authors: Georg Brandstätter; Michael Kahr; Markus Leitner
      Pages: 17 - 35
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Georg Brandstätter, Michael Kahr, Markus Leitner
      In this article, we introduce and study a two-stage stochastic optimization problem suitable to solve strategic optimization problems of car-sharing systems that utilize electric cars. By combining the individual advantages of car-sharing and electric vehicles, such electric car-sharing systems may help to overcome future challenges related to pollution, congestion, or shortage of fossil fuels. A time-dependent integer linear program and a heuristic algorithm for solving the considered optimization problem are developed and tested on real world instances from the city of Vienna, as well as on grid-graph-based instances. An analysis of the influence of different parameters on the overall performance and managerial insights are given. Results show that the developed exact approach is suitable for medium sized instances such as the ones obtained from the inner districts of Vienna. They also show that the heuristic can be used to tackle very-large-scale instances that cannot be approached successfully by the integer-programming-based method.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.009
      Issue No: Vol. 104 (2017)
  • An agent-based day-to-day adjustment process for modeling ‘Mobility as a
           Service’ with a two-sided flexible transport market
    • Authors: Shadi Djavadian; Joseph Y.J. Chow
      Pages: 36 - 57
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Shadi Djavadian, Joseph Y.J. Chow
      Due to advances in communications technologies and social networks, flexible mobility systems such as taxi, carpool and demand responsive transit have gained interest among practitioners and researchers as a solution to address such problems as the ``first/last mile problem". While recent research has modeled these systems using agent-based stochastic day-to-day processes, they assume only traveler adjustment under a one-sided market setting. What if such systems are naturally ``two-sided markets" like Uber or AirBnB?In this study, we explore flexible transport services in the framework of two-sided markets, and extend an earlier day-to-day adjustment process to include day-to-day adjustment of the service operator(s) as the seller and the built environment as the platform of a two-sided market. We use the Ramsey pricing criterion for social optimum to show that a perfectly matched state from a day-to-day process is equivalent to a social optimum. A case study using real data from Oakville, Ontario, as a first/last mile problem example demonstrates the sensitivity of the day-to-day model to operating policies. Computational experiments confirm the existence of locally stable states. More importantly, the experiments show the existence of thresholds from which network externalities cause two-sided and one-sided market equilibria to diverge.
      Graphical abstract image

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.015
      Issue No: Vol. 104 (2017)
  • Investigation of the traffic congestion during public holiday and the
           impact of the toll-exemption policy
    • Authors: Yue Bao; Feng Xiao; Zaihan Gao; Ziyou Gao
      Pages: 58 - 81
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Yue Bao, Feng Xiao, Zaihan Gao, Ziyou Gao
      Traffic congestion has long been a noticeable issue worldwide. Besides congestion caused by the daily commuters, congestion during public holidays is also very typical. The traffic volume often has a sharp increase during public holidays, which puts a heavy burden on the road capacity and results in severe congestion. This is especially true for the beginning and ending of the holidays. The situation is even worse under some government policies designed initially to benefit people, e.g. the highway toll-exemption during public holidays in China. The focus of this paper is to model the evolution of traffic congestion caused by the demand from residential place to the famous resorts during public holidays. The research questions include: (1) how do tourists tradeoff between schedule delay, queuing time and the overcrowding of the resort' and (2) the impact of the toll-exemption policy during public holidays on tourists’ departure time choices and the social welfare. By adopting the bottleneck model, we obtain the cumulative departure curves of tourists during public holidays. Closed-form results of tourists’ departure time variation with the toll-exemption policy are obtained, as well as the resulting social efficiency loss, which is significant for the management of the traffic mobility during public holidays.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.05.011
      Issue No: Vol. 104 (2017)
  • Resilient facility location against the risk of disruptions
    • Authors: Guodong Yu; William B. Haskell; Yang Liu
      Pages: 82 - 105
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Guodong Yu, William B. Haskell, Yang Liu
      In this paper, we consider an uncapacitated facility location problem (RUFL) with random facility disruptions. We develop risk-averse optimization formulations to compute resilient location and customer assignment solutions for two cases (i.e., under either independent or correlated disruptions), where the risks are expressed through a family of risk measures including conditional value-at-risk (CVaR) and absolute-semideviation (ASD). The risk-averse RUFL with independent facility disruptions is to control the risks at each individual customer and modeled as a mixed-integer nonlinear programming, which is challenging to be solved. In response, we develop a branch-and-cut algorithm combined with augmented Lagrangian decomposition for globally optimizing the problem. As for the risk-averse RUFL with correlated facility disruptions, we propose a scenario-based model to minimize the total fixed costs and risks across the entire customer set. The resulting formulation is a pure MILP and a Lagrangian decomposition scheme is proposed for computational aspects in large-scale cases. Our numerical results show that the risk-averse models outperform the classic risk-neutral models in improving the reliability. Experiments demonstrate that our proposed algorithms perform well. To conclude, we extract managerial insights that suggest important guidelines for controlling risk in the face of disruption.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.014
      Issue No: Vol. 104 (2017)
  • Simultaneous estimation of states and parameters in Newell’s simplified
           kinematic wave model with Eulerian and Lagrangian traffic data
    • Authors: Zhe Sun; Wen-Long Jin; Stephen G. Ritchie
      Pages: 106 - 122
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Zhe Sun, Wen-Long Jin, Stephen G. Ritchie
      The traffic state estimation process estimates various traffic states from available data in a road network and provides valuable information for travelers and decision makers to improve both travel experience and system performance. In many existing methods, model parameters and initial states have to be given in order to estimate traffic states, which limits the accuracy of the results as well as their transferability to different locations and times. In this paper, we propose a new framework to simultaneously estimate model parameters and traffic states for a congested road segment based on Newell’s simplified kinematic wave model (Newell, 1993). Given both Eulerian traffic count data and Lagrangian vehicle reidentification data, we formulate a single optimization problem in terms of the initial number of vehicles and model parameters. Then we decouple the optimization problem such that the initial number of vehicles can be analytically solved with a closed-form formula, and the model parameters, including the jam density and the shock wave speed in congested traffic, can be computed with the Gauss-Newton method. Based on Newell’s model, we can calculate individual vehicles’ trajectories as well as the average densities, speeds, and flow-rates inside the road segment. We also theoretically show that the optimization problem can have multiple solutions under absolutely steady traffic conditions. We apply the proposed method to the NGSIM datasets, verifying the validity of the method and showing that this method yields better results in the estimation of average densities than existing methods.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.012
      Issue No: Vol. 104 (2017)
  • A predictive-control framework to address bus bunching
    • Authors: Matthias Andres; Rahul Nair
      Pages: 123 - 148
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Matthias Andres, Rahul Nair
      Busy bus routes often suffer from buses not arriving at regular intervals but in bunches at bus stops. In this paper we study this bus bunching phenomenon and address it by a combination of data-driven headway prediction and dynamic holding strategies, which allow to modulate buses’ dwell times at stops to reduce the headway deviation. We formulate time headways as time series and compare several prediction methods by testing on data from a busy bus route in Dublin. Furthermore we review and extend an analytical model of an artificial bus route and discuss stability properties and dynamic holding strategies using both data available at the time and predicted headway data. In a numerical simulation we illustrate how the combination of two simple concepts lead to a promising strategy to reduce bus bunching.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.013
      Issue No: Vol. 104 (2017)
  • Train timetabling by skip-stop planning in highly congested lines
    • Authors: Feng Jiang; Valentina Cacchiani; Paolo Toth
      Pages: 149 - 174
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Feng Jiang, Valentina Cacchiani, Paolo Toth
      We study the problem of scheduling passenger trains in a highly congested railway double-track line with the aim of increasing the number of scheduled trains. A feasible timetable of the trains currently scheduled in the network is given. Additional trains should be scheduled to meet the increasing passenger demand. To achieve this goal, we are allowed to increase the dwelling time of some trains at some stations, to let them stop at some additional stations and even to skip a few stops. Thereby, we need to take explicitly into account the deceleration and acceleration times that are needed by the train when it stops at a station. This problem integrates the choice of the train schedule with the choice of the train stops, the latter being usually made in the Line Planning process. To solve this problem, we propose a heuristic algorithm, extended from a previous method to include the new features of the studied application, and show its performance on real-world instances of the Chinese high-speed JingHu corridor (between Beijing and Shanghai) involving up to 387 trains.

      PubDate: 2017-07-21T10:44:54Z
      DOI: 10.1016/j.trb.2017.06.018
      Issue No: Vol. 104 (2017)
  • Modelling bus bunching and holding control with vehicle overtaking and
           distributed passenger boarding behaviour
    • Authors: Weitiao Wu; Ronghui Liu; Wenzhou Jin
      Pages: 175 - 197
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Weitiao Wu, Ronghui Liu, Wenzhou Jin
      Headway fluctuation and bus bunching are commonly observed in transit operations, while holding control is a proven strategy to reduce bus bunching and improve service reliability. A transit operator would benefit from an accurate forecast of bus propagation in order to effectively control the system. To this end, we propose an ‘ad-hoc’ bus propagation model taking into account vehicle overtaking and distributed passenger boarding (DPB) behaviour. The latter represents the dynamic passenger queue swapping among buses when bunching at bus stops occurs and where bus capacity constraints are explicitly considered. The enhanced bus propagation model is used to build the simulation environment where different holding control strategies are tested. A quasi first-depart-first-hold (FDFH) rule is applied to the design of schedule- and headway-based holding control allowing for overtaking, with the objective to minimise the deviation from the targeted headway. The effects of control strategies are tested in an idealised bus route under different operational setting and in a real bus route in Guangzhou. We show that when the combined overtaking and queue-swapping behaviour are considered, the control strategies can achieve better headway regularity, less waiting time and less on-board travel time than their respective versions without overtaking and DPB. The benefit is even greater when travel time variability is higher and headway is smaller, suggesting that the control strategies are preferably deployed in high-frequency service.

      PubDate: 2017-07-21T10:44:54Z
      DOI: 10.1016/j.trb.2017.06.019
      Issue No: Vol. 104 (2017)
  • Speed optimization over a path with heterogeneous arc costs
    • Authors: Qie He; Xiaochen Zhang; Kameng Nip
      Pages: 198 - 214
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Qie He, Xiaochen Zhang, Kameng Nip
      The speed optimization problem over a path aims to find a set of speeds over each arc of the given path to minimize the total cost, while respecting the time-window constraint at each node and speed limits over each arc. In maritime transportation, the cost represents fuel cost or air pollutant emissions, so study of this problem has significant economic and environmental impacts. To accommodate different fuel and emission models, we allow the dependence of the cost on the speed to be a general continuously differentiable and strictly convex function, and different across the arcs. We develop an efficient algorithm that is able to solve instances of 1000 nodes in less than a second. The algorithm is 20 to 100 times faster than a general convex optimization solver on test instances and requires much less memory. The solutions found at intermediate steps of our algorithm also provide some insights to ship planners on how to balance the operating cost and service quality.

      PubDate: 2017-07-21T10:44:54Z
      DOI: 10.1016/j.trb.2017.07.004
      Issue No: Vol. 104 (2017)
  • Modeling the dynamics of congestion in large urban networks using the
           macroscopic fundamental diagram: User equilibrium, system optimum, and
           pricing strategies
    • Authors: Mahyar Amirgholy; H. Oliver Gao
      Pages: 215 - 237
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Mahyar Amirgholy, H. Oliver Gao
      The macroscopic fundamental diagram (MFD) is introduced in recent studies to present the relationship between the flow and the density of the network in large urban regions (neighborhoods). The MFD can be also rescaled to approximate network outflow as a function of the vehicular accumulation of the system in the morning commute problem. In this research, we develop a bathtub model (macro-scale traffic congestion model) by combining Vickrey's (1969) model of dynamic congestion with the MFD to formulate the user equilibrium over the peak as an ordinary differential equation (ODE). This problem can be solved numerically to estimate the exact solution of the morning commute problem. Alternatively, the morning commute problem can be solved analytically by approximating the solution of the ODE using a well-behaved function. Here, we present a quadratic and also a linear approximation of the equilibrium solution for a semi-quadratic MFD, considering that the declining part of the MFD is shown to be well estimated by a quadratic function. To optimize the system, we present pricing strategies for network users (dynamic tolling) and employers inside the region (dynamic taxing) that can minimize the generalized cost of the system by keeping the outflow maximized over the peak. Finally, we compare the exact and the approximate solutions of the problem, and also the proposed pricing strategies of the region in a numerical example.

      PubDate: 2017-07-27T06:31:09Z
      DOI: 10.1016/j.trb.2017.07.006
      Issue No: Vol. 104 (2017)
  • A fast simulation algorithm for multiple moving bottlenecks and
           applications in urban freight traffic management
    • Authors: Michele D. Simoni; Christian G. Claudel
      Pages: 238 - 255
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Michele D. Simoni, Christian G. Claudel
      Moving bottlenecks are moving capacity restrictions that affect traffic flows, and they can be used to describe the effects of buses and trucks in transportation networks. The computation of solutions associated with the presence of moving bottlenecks is complex, since they both influence and are influenced by surrounding traffic. In this study, we propose a fast numerical scheme that can efficiently compute the solutions to an arbitrary number of moving (and fixed) bottlenecks, for a stretch of road modeled by the Lighthill–Whitham–Richards (LWR) model. Several different moving bottlenecks can be simulated endogenously all together by means of an algorithm based on a semi-analytic Lax–Hopf formula. Since the numerical scheme is semi-analytic and requires a very low number of operations, it can be employed for traffic estimation problems where fast and accurate solutions are required. We demonstrate the capabilities of the method by implementing two alternative traffic management strategies designed to minimize the negative impacts of trucks and buses in urban environments.

      PubDate: 2017-07-27T06:31:09Z
      DOI: 10.1016/j.trb.2017.06.010
      Issue No: Vol. 104 (2017)
  • On the stochastic fundamental diagram for freeway traffic: Model
           development, analytical properties, validation, and extensive applications
    • Authors: Xiaobo Qu; Jin Zhang; Shuaian Wang
      Pages: 256 - 271
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Xiaobo Qu, Jin Zhang, Shuaian Wang
      In this research, we apply a new calibration approach to generate stochastic traffic flow fundamental diagrams. We first prove that the percentile based fundamental diagrams are obtainable based on the proposed model. We further prove the proposed model has continuity, differentiability and convexity properties so that it can be easily solved by Gauss–Newton method. By selecting different percentile values from 0 to 1, the speed distributions at any given densities can be derived. The model has been validated based on the GA400 data and the calibrated speed distributions perfectly fit the speed-density data. This proposed methodology has wide applications. First, new approaches can be proposed to evaluate the performance of calibrated fundamental diagrams by taking into account not only the residual but also ability to reflect the stochasticity of samples. Secondly, stochastic fundamental diagrams can be used to develop and evaluate traffic control strategies. In particular, the proposed stochastic fundamental diagram is applicable to model and optimize the connected and automated vehicles at the macroscopic level with an objective to reduce the stochasticity of traffic flow. Last but not the least, this proposed methodology can be applied to generate the stochastic models for most regression models with scattered samples.

      PubDate: 2017-07-27T06:31:09Z
      DOI: 10.1016/j.trb.2017.07.003
      Issue No: Vol. 104 (2017)
  • Risky weighting in discrete choice
    • Authors: Baibing Li; David A. Hensher
      Pages: 1 - 21
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Baibing Li, David A. Hensher
      This paper presents a new approach to discrete choice analysis for risky prospects. Conventional discrete choice analysis focuses on riskless prospects and does not deal with the scenario where the alternatives that the decision-makers choose from are associated with risk. In this paper, we investigate decision-makers’ risk perception and choice behaviour in choice experiments when they are facing several risky prospects. We propose a broad class of cumulative risky weighting functions, upon which a unified cumulative risky weighting function is developed. We show that this unified cumulative risky weighting function includes several existing cumulative risky weighting functions as special cases. We then develop a multivariate method for choice analysis with risky prospects to account for decision-makers’ individual-specific risk perception and the impact of various factors on the value function respectively. We illustrate the developed method using an empirical study on road tolling in Australia.

      PubDate: 2017-05-21T09:26:15Z
      DOI: 10.1016/j.trb.2017.04.014
      Issue No: Vol. 102 (2017)
  • An optimal stopping approach to managing travel-time uncertainty for
           time-sensitive customer pickup
    • Authors: Neža Vodopivec; Elise Miller-Hooks
      Pages: 22 - 37
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Neža Vodopivec, Elise Miller-Hooks
      In dynamic vehicle routing, it is common to respond to real-time information with immediate updates to routes and fleet management. However, even if routes are updated continuously, in practice, some decisions once made are difficult to reverse. At times, it may thus be valuable to wait for additional information before acting on a decision. We use the theory of optimal stopping to determine the optimal timing of a recourse action when vehicles are likely to miss customer deadlines due to travel-time stochasticities and backup services are available. The factors involved in making this decision – that is, the likelihood that the primary vehicle will arrive late, the location of the backup vehicle, and value of waiting for additional travel-time information – each change dynamically over time. We develop a recourse model that accounts for this complexity. We formulate the optimal recourse policy as a stochastic dynamic program. Properties of the optimal policy are derived analytically, and its solution is approximated with a binomial lattice method used in the pricing of American options. Finally, we develop a two-stage stochastic optimization approach to show how the opportunity to take recourse dynamically might be integrated into a priori scheduling and routing. The framework is demonstrated for a stochastic dial-a-ride application in which taxis serve as backup to ridesharing vehicles.

      PubDate: 2017-05-21T09:26:15Z
      DOI: 10.1016/j.trb.2017.04.017
      Issue No: Vol. 102 (2017)
  • Analysis of an idealized system of demand adaptive paired-line hybrid
    • Authors: Peng Will Chen; Yu Marco Nie
      Pages: 38 - 54
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Peng Will Chen, Yu Marco Nie
      This paper proposes and analyzes a new transit system that integrates the traditional fixed-route service with a demand-adaptive service. The demand-adaptive service connects passengers from their origin/destination to the fixed-route service in order to improve accessability. The proposed hybrid design is unique in that it operates the demand-adaptive service with a stable headway to cover all stops along a paired fixed-route line. Pairing demand-adaptive vehicles with a fixed-route line simplifies the complexity of on-demand routing, because the vehicles can follow a more predictable path and can be dispatched on intervals coordinated with the fixed-route line. The design of the two services are closely coupled to minimize the total system cost, which incudes both the transit agency’s operating cost and the user cost. The optimal design model is formulated as a mixed integer program and solved using a commercially available metaheuristic. Numerical experiments are conducted to compare the demand adaptive paired-line hybrid transit (DAPL-HT) system with two related transit systems that may be considered its special cases: a fixed-route system and a flexible-route system. We show that the DAPL-HT system outperforms the other two systems under a wide range of demand levels and in various scenarios of input parameters. A discrete-event simulation model is also developed and applied to confirm the correctness of the analytical results.

      PubDate: 2017-05-21T09:26:15Z
      DOI: 10.1016/j.trb.2017.05.004
      Issue No: Vol. 102 (2017)
  • Detecting dominance in stated choice data and accounting for
           dominance-based scale differences in logit models
    • Authors: Michiel C.J. Bliemer; John M. Rose; Caspar G. Chorus
      Pages: 83 - 104
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Michiel C.J. Bliemer, John M. Rose, Caspar G. Chorus
      Stated choice surveys have been used for several decades to estimate preferences of agents using choice models, and are widely applied in the transportation domain. Different types of experimental designs that underlie such surveys have been used in practice. In unlabelled experiments, where all alternatives are described by the same generic utility function, such designs may suffer from choice tasks containing a dominant alternative. Also in labelled experiments with alternative specific attributes and constants such dominance may occur, but to a lesser extent. We show that dominant alternatives are problematic because they affect scale and may bias parameter estimates. We propose a new measure based on minimum regret to calculate dominance and automatically detect such choice tasks in an experimental design or existing dataset. This measure is then used to define a new experimental design type that removes dominance and ensures the making of trade-offs between attributes. Finally, we propose a new regret-scaled multinomial logit model that takes the level of dominance within a choice task into account. Results using simulated and empirical data show that the presence of dominant alternatives can bias model estimates, but by making scale a function of a smooth approximation of normalised minimum regret we can properly account for scale differences without the need to remove choice tasks with dominant alternatives from the dataset.

      PubDate: 2017-05-21T09:26:15Z
      DOI: 10.1016/j.trb.2017.05.005
      Issue No: Vol. 102 (2017)
  • Quantitative analyses of highway franchising under build-operate-transfer
           scheme: Critical review and future research directions
    • Authors: Qiang Meng; Zhaoyang Lu
      Pages: 105 - 123
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Qiang Meng, Zhaoyang Lu
      Private provision of the public highways through the build-operate-transfer (BOT) scheme has become popular worldwide. Studies published in dozens of academic journals have investigated various kinds of cases of BOT highway projects. However, there appears to be a lack of systematic and critical overview on what specific problems and research methodologies these studies proposed and used for quantitatively analyzing the BOT highway projects. Therefore, this study critically reviews the relevant traffic oriented quantitative studies, which mainly focus on the determination of fundamental design factors for a BOT highway project in the planning stage. The existing studies are thoroughly examined according to the characters of BOT highway projects. To conclude, this study points out the limitations of the current studies and provides some tangible future research directions with practical relevance.

      PubDate: 2017-05-26T09:34:30Z
      DOI: 10.1016/j.trb.2017.05.009
      Issue No: Vol. 102 (2017)
  • Air traffic flow management under uncertainty using chance-constrained
    • Authors: J. Chen; L. Chen; D. Sun
      Pages: 124 - 141
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): J. Chen, L. Chen, D. Sun
      In order to efficiently balance traffic demand and capacity, optimization of Air Traffic Flow Management (ATFM) relies on accurate predictions of future capacity states. However, these predictions are inherently uncertain due to factors, such as weather. This paper presents a novel computationally efficient algorithm to address uncertainty in ATFM by using a chance-constrained optimization method. First, a chance-constrained model is developed based on a previous deterministic Integer Programming optimization model of ATFM to include probabilistic sector capacity constraints. Then, to efficiently solve such a large-scale chance-constrained optimization problem, a polynomial approximation-based approach is applied. The approximation is based on the numerical properties of the Bernstein polynomial, which is capable of effectively controlling the approximation error for both the function value and gradient. Thus, a first-order algorithm is adopted to obtain a satisfactory solution, which is expected to be optimal. Numerical results are reported in order to evaluate the polynomial approximation-based approach by comparing it with the brute-force method. Moreover, since there are massive independent approximation processes in the polynomial approximation-based approach, a distributed computing framework is designed to carry out the computation for this method. This chance-constrained optimization method and its computation platform are potentially helpful in their application to several other domains in air transportation, such as airport surface operations and airline management under uncertainties.

      PubDate: 2017-05-30T19:38:02Z
      DOI: 10.1016/j.trb.2017.05.014
      Issue No: Vol. 102 (2017)
  • Design of energy-Efficient timetables in two-way railway rapid transit
    • Authors: David Canca; Alejandro Zarzo
      Pages: 142 - 161
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): David Canca, Alejandro Zarzo
      A methodology to design energy-efficient timetables in Rapid Railway Transit Networks is presented. Using an empirical description of the train energy consumption as a function of running times, the timetable design problem is modelled as a Mixed Integer Non-Linear optimization problem (MINLP) for a complete two-way line. In doing so, all the services in both directions along a certain planning horizon are considered while attending a known passengers’ demand. The MINLP formulation, which depends on train loads, is fully linearised supposing train loads are fixed. A sequential Mixed Integer Linear solving procedure is then used to solve the timetabling optimization problem with unknown train loads. The proposed methodology emphasizes the need of considering all the services running during the planning horizon when designing energy-efficient timetables, as consequence of the relationship among train speeds, frequency and fleet size of each line. Moreover, the convenience of considering the energy consumption as part of a broad objective function that includes other relevant costs is pointed out. Otherwise, passengers and operators could face up to an increase in the whole cost and a decrease in the quality of service. A real data scenario, based on the C-2 Line of the Madrid Metropolitan Railways, is used to illustrate the proposed methodology and to discuss the differences between the energy-efficient solutions and those obtained when considering operation and acquisition costs.

      PubDate: 2017-06-05T04:03:51Z
      DOI: 10.1016/j.trb.2017.05.012
      Issue No: Vol. 102 (2017)
  • Doubly dynamics for multi-modal networks with park-and-ride and adaptive
    • Authors: Wei Liu; Nikolas Geroliminis
      Pages: 162 - 179
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Wei Liu, Nikolas Geroliminis
      This paper models and controls a multi-region and multi-modal transportation system, given that the travelers can adjust their mode choices from day to day, and the within-day traffic dynamics in the network also evolve over days. In particular, it considers that the city network can be partitioned into two regions (center and periphery). There are park-and-ride facilities located at the boundary between the city center region and the periphery. Travelers can either drive to the city center, or take public transit, or drive to the park-and-ride facilities and then transfer to the public transit. Travelers can “learn” from their travel experience, as well as real-time information about traffic conditions, thus will adjust their choices accordingly. It follows that the dynamic traffic pattern (within-day) in the city network will evolve over (calendar) time (day-to-day). To improve traffic efficiency in the network, an adaptive mechanism, which does not need detailed travelers’ behavioral characteristics, is developed to update parking pricing (or congestion pricing) from period to period (e.g., one period can be one month). The developed doubly dynamics methodological framework coupled with a feedback pricing mechanism unfolds and influences equilibrium system characteristics that traditional static day-to-day models cannot observe. The proposed adaptive pricing approach is practical for implementation in large-scale networks as the variables involved can be observed in real life with monitoring techniques. Also, it can contribute to reduce total social cost effectively, as shown in the numerical experiments.

      PubDate: 2017-06-05T04:03:51Z
      DOI: 10.1016/j.trb.2017.05.010
      Issue No: Vol. 102 (2017)
  • A stochastic program approach for path reconstruction oriented sensor
           location model
    • Authors: Chenyi Fu; Ning Zhu; Shoufeng Ma
      Pages: 210 - 237
      Abstract: Publication date: August 2017
      Source:Transportation Research Part B: Methodological, Volume 102
      Author(s): Chenyi Fu, Ning Zhu, Shoufeng Ma
      Path flow identification is of particular interest for a number of traffic applications, such as OD demand estimation, link flow inference, and toll freeway revenue management. Optimal positioning of active sensors can help to identify path flows. Due to the stochastic nature of transportation systems, we propose a scenario based two stage stochastic programming framework which considers the uncertainty of the link-path matrix. The first stage model aims to minimize the total traffic sensor installation cost and the expected penalty for uncovered and undifferentiated paths. The second stage model attempts to minimize uncovered and undifferentiated paths for a given sensor location pattern and a specific scenario. In addition, a mean risk measure is also incorporated into the two stage stochastic programming framework, and consequently a mean risk two stage stochastic programming model is proposed. Both models have the same structure, where the first stage and second stage decision variables are binary. The second stage decision variable can be relaxed to a continuous variable without changing the nature of the model. To solve the two stochastic programming models, a branch and bound based integer L-shaped algorithm is presented. Finite steps convergence is guaranteed for the algorithm. To handle the problem with a large number of scenarios, a sampling technique is introduced, and the confidence bound is analyzed with respect to the scenario size. Extensive numerical experiments are conducted to verify the effectiveness of the proposed models and algorithm. The most important numerical results are as follows: (i) the stochastic programming framework is capable of capturing the reality more efficiently and accurately, (ii) the path differentiation factor is more critical than the path coverage factor in determining the sensor placement pattern, and (iii) in the partial parameter setting case, the mean risk based stochastic programming model results in a significantly different sensor placement pattern compared to the normal stochastic programming model. The study contributes to practical sensor placement design.

      PubDate: 2017-06-05T04:03:51Z
      DOI: 10.1016/j.trb.2017.05.013
      Issue No: Vol. 102 (2017)
  • Scalable space-time trajectory cube for path-finding: A study using big
           taxi trajectory data
    • Authors: Lin Yang; Mei-Po Kwan; Xiaofang Pan; Bo Wan; Shunping Zhou
      Pages: 1 - 27
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Lin Yang, Mei-Po Kwan, Xiaofang Pan, Bo Wan, Shunping Zhou
      Route planning is an important daily activity and has been intensively studied owing to their broad applications. Extracting the driving experience of taxi drivers to learn about the best routes and to support dynamic route planning can greatly help both end users and governments to ease traffic problems. Travel frequency representing the popularity of different road segments plays an important role in experience-based path-finding models and route computation. However, global frequency used in previous studies does not take into account the dynamic space-time characteristics of origins and destinations and the detailed travel frequency in different directions on the same road segment. This paper presents the space-time trajectory cube as a framework for dividing and organizing the trajectory space in terms of three dimensions (origin, destination, and time). After that, space-time trajectory cube computation and origin-destination constrained experience extraction methods are proposed to extract the fine-grained experience of taxi drivers based on a dataset of real taxi trajectories. Finally, space-time constrained graph was generated by merging drivers’ experience with the road network to compute optimal routes. The framework and methods were implemented using a taxi trajectory dataset from Shenzhen, China. The results show that the proposed methods effectively extracted the driving experience of the taxi drivers and the entailed trade-off between route length and travel time for routes with high trajectory coverage. They also indicate that road segment global frequency is not appropriate for representing driving experience in route planning models. These results are important for future research on route planning or path finding methods and their applications in navigation systems.

      PubDate: 2017-04-01T17:32:04Z
      DOI: 10.1016/j.trb.2017.03.010
      Issue No: Vol. 101 (2017)
  • Bounded rationality can make parking search more efficient: The power of
           lexicographic heuristics
    • Authors: Merkouris Karaliopoulos; Konstantinos Katsikopoulos; Lambros Lambrinos
      Pages: 28 - 50
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Merkouris Karaliopoulos, Konstantinos Katsikopoulos, Lambros Lambrinos
      The search for parking space in busy urban districts is one of those routine human activities that are expected to benefit from the widespread adoption of pervasive sensing and radio communication technologies. Proposed parking assistance solutions combine sensors, either as part of fixed infrastructure or onboard vehicles, wireless networking technologies and mobile social applications running on smartphones to collect, share and present to drivers real-time information about parking demand and availability. One question that arises is how does (and should) the driver actually use such information to take parking decisions, e.g., whether to search for on-street parking space or drive to a parking lot and, in the latter case, which one. The paper is, hence, a performance analysis study that seeks to capture the highly behavioral and heuristic dimension of drivers’ decisions and its impact on the efficiency of the parking search process. To this end, and in sharp contrast with the existing literature, we model drivers as agents of bounded rationality and assume that their choices are directed by lexicographic heuristics, an instance of the fast and frugal heuristics developed in behavioral sciences such as psychology and biology. We analyze the performance of the search process under these heuristics and compare it against the predictions of normative game-theoretic models that assume fully rational strategically acting agents. We derive conditions under which the game-theoretic norms turn out to be more pessimistic than the simpler heuristic choice rules and show that these are fulfilled for a broad range of scenarios concerning the fees charged for the parking resources and their distance from the destinations of the drivers’ trips. The practical implications of these results for parking assistance solutions are identified and thoroughly discussed.

      PubDate: 2017-04-01T17:32:04Z
      DOI: 10.1016/j.trb.2017.03.008
      Issue No: Vol. 101 (2017)
  • Traffic state estimation based on Eulerian and Lagrangian observations in
           a mesoscopic modeling framework
    • Authors: Aurélien Duret; Yufei Yuan
      Pages: 51 - 71
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Aurélien Duret, Yufei Yuan
      The paper proposes a model-based framework for estimating traffic states from Eulerian (loop) and/or Lagrangian (probe) data. Lagrangian-Space formulation of the LWR model adopted as the underlying traffic model provides suitable properties for receiving both Eulerian and Lagrangian external information. Three independent methods are proposed to address Eulerian data, Lagrangian data and the combination of both, respectively. These methods are defined in a consistent framework so as to be implemented simultaneously. The proposed framework has been verified on the synthetic data derived from the same underlying traffic flow model. Strength and weakness of both data sources are discussed. Next, the proposed framework has been applied to a freeway corridor. The validity has been tested using the data from a microscopic simulator, and the performance is satisfactory even for low rate of probe vehicles around 5%.
      Graphical abstract image

      PubDate: 2017-04-09T06:20:20Z
      DOI: 10.1016/j.trb.2017.02.008
      Issue No: Vol. 101 (2017)
  • Goal-based models for discrete choice analysis
    • Authors: A.A.J. Marley; J. Swait
      Pages: 72 - 88
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): A.A.J. Marley, J. Swait
      Goals direct decision making, from the most abstract levels of motivation to the multitudinous details of evaluation of options available for choice. However, the pervasive influence of goals in decision processes is generally not explicitly recognized at the level of demand model formulation and specification. In applied economics generally, and transportation specifically, demand models relate product/service attributes directly to behavior, using utility (or value) as a shorthand representation for the impact of goals. In this paper we argue that this is a limiting view that restricts our thinking about decision making and, hence, our representation and inference-making about that behavior. We support this argument by reinterpreting and/or extending various applications of hybrid models in transportation to a goal-based framework and formulating goal-based choice models which recognize that goals (1) are drivers of choice, (2) explain the choice of strategy, (3) are part of the constraint set and (4) contribute to explaining impacts of the decision context on the allocation of cognitive resources by the decision maker.

      PubDate: 2017-04-09T06:20:20Z
      DOI: 10.1016/j.trb.2017.03.005
      Issue No: Vol. 101 (2017)
  • Hub-airport congestion pricing and capacity investment
    • Authors: Ming Hsin Lin; Yimin Zhang
      Pages: 89 - 106
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Ming Hsin Lin, Yimin Zhang
      This study examines hub-airport congestion pricing and capacity investment using a simple hub-spoke network model, in which hub-carrier scheduling causes both schedule delays and congestion delays. The “fixed-proportion assumption” is removed. We find the following. (i) A public hub airport requires both per-flight charges, which must be movement-related but cannot be weight-related, and discriminatory per-local and per-connecting passenger charges to reach the first-best outcome. (ii) Either weight-related per-flight charges or the marginal-operating-cost (MOC) pricing on local and/or connecting passengers cannot reach the first-best. (iii) First-best charges can lead capacity investment to be socially efficient. However, weight-related per-flights charges result in under-investment, whereas the MOC pricing results in over-investment in runway capacity. (iv) Private hubs that charge positive movement-related per-flight charges subsidize passengers through per-passenger charges. Finally, (v) movement-related per-flight charges lead private hubs to overinvest, whereas weight-related per-flight charges lead to either over- or under-investment.

      PubDate: 2017-04-09T06:20:20Z
      DOI: 10.1016/j.trb.2017.03.009
      Issue No: Vol. 101 (2017)
  • Downtown parking supply, work-trip mode choice and urban spatial
    • Authors: Sofia F. Franco
      Pages: 107 - 122
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Sofia F. Franco
      This paper examines the effects of changes in downtown parking supply on urban welfare, modal choice decisions and urban spatial structure using a spatial general equilibrium model of a closed monocentric city with two transport modes, endogenous residential parking and a form of bottleneck congestion at the CBD. Our analysis shows that parking reforms at the CBD that increase delay congestion costs in the short-run such as parking supply limits can be welfare improving if other commuting externalities such as air pollution can be reduced. In addition, because parking limits can also change location decisions such as where to live and invest they may complement anti-sprawl policies efforts by leading to a more compact urban spatial structure in the long run. We also show that changes in downtown parking supply can have different spatial impacts on the market supply of residential parking by affecting urban residents’ location decisions. Finally, we investigate whether the self-financing theorem of transportation economics holds within the context of our spatial urban model.

      PubDate: 2017-04-09T06:20:20Z
      DOI: 10.1016/j.trb.2017.03.012
      Issue No: Vol. 101 (2017)
  • The cumulative capacitated vehicle routing problem with min-sum and
           min-max objectives: An effective hybridisation of adaptive variable
           neighbourhood search and large neighbourhood search
    • Authors: Jeeu Fong Sze; Said Salhi; Niaz Wassan
      Pages: 162 - 184
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Jeeu Fong Sze, Said Salhi, Niaz Wassan
      The cumulative capacitated vehicle routing problem (CCVRP) is a relatively new variant of the classical capacitated vehicle routing problem in which the objective is to minimise the sum of arrival times at customers (min-sum) instead of the total route distance. While the literature for the CCVRP is scarce, this problem has useful applications especially in the area of supplying humanitarian aid after a natural disaster. In this paper, a two-stage adaptive variable neighbourhood search (AVNS) algorithm that incorporates large neighbourhood search (LNS) as a diversification strategy is proposed. When tested on the benchmark data sets, the results show that the proposed AVNS is highly competitive in producing new best known solutions to more than half of the instances. An alternative but related objective that minimises the maximum arrival time (min-max) is also explored in this study demonstrating the flexibility and the effectiveness of the proposed metaheuristic. To the best of our knowledge, this is the first study that exploits the min-max objective of the CCVRP in addition to providing extensive computational results for a large number of instances for the min-sum. As a by-product of this study, managerial insights for decision making are also presented.

      PubDate: 2017-04-23T06:18:14Z
      DOI: 10.1016/j.trb.2017.04.003
      Issue No: Vol. 101 (2017)
  • A Nash equilibrium formulation of a tradable credits scheme for
           incentivizing transport choices: From next-generation public transport
           mode choice to HOT lanes
    • Authors: Salem Lahlou; Laura Wynter
      Pages: 185 - 212
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Salem Lahlou, Laura Wynter
      We consider a tradable credits scheme for binary transport games where one option is faster (or more comfortable) than the other, but its quality of service suffers when usage is high. Applications can be found in mode choice (public transit versus road transport), premium (i.e., express bus) versus ordinary public transit, and fast (e.g., high-occupancy toll, or HOT) versus regular lanes on expressways. We are motivated in particular by the choice between public transport and use of the road network as a privilege to be discouraged. In a future where GPS-based time-distance-place road charging exists, such next-generation transport management strategies become realizable as the choice to drive or not can be linked to a fixed fee toll, or indeed to a tradable credits scheme. When public transport payment uses the same smart card as the road usage fee (via tolls or tradable credits) usage of the two may be linked. In this setting, a public transport vs. road-use tradable credit scheme becomes feasible. In this case, individuals wishing to choose the faster option must obtain credits from other commuters via credit trading, rather than pay a direct toll or fee. Such a scheme creates a kind of equity, in the sense that lower-income commuters have an economic incentive to resort to the slower or less comfortable choice. We study the underlying market and its effects on individuals’ utilities; we use an atomic game framework so as to model explicitly the exchange process across users. The market we define determines the quantities of users choosing each option, as opposed to the prices themselves. Using the properties of potential games, we show that under mild assumptions, efficient Nash equilibria exist and can be reached using simple learning algorithms. We show that these equilibria can satisfy the transport authority’s requirements, and thus drive the transport system to a state where a desired proportion of individuals resort to each of the two options, when the scheme’s parameters are well tuned.

      PubDate: 2017-04-23T06:18:14Z
      DOI: 10.1016/j.trb.2017.03.014
      Issue No: Vol. 101 (2017)
  • On the distribution of individual daily driving distances
    • Authors: Patrick Plötz; Niklas Jakobsson; Frances Sprei
      Pages: 213 - 227
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Patrick Plötz, Niklas Jakobsson, Frances Sprei
      Plug-in electric vehicles (PEV) can reduce greenhouse gas emissions. However, the utility of PEVs, as well as reduction of emissions is highly dependent on daily vehicle kilometres travelled (VKT). Further, the daily VKT by individual passenger cars vary strongly between days. A common method to analyse individual daily VKT is to fit distribution functions and to further analyse these fits. However, several distributions for individual daily VKT have been discussed in the literature without conclusive decision on the best distribution. Here we analyse three two-parameter distribution functions for the variation in daily VKT with four sets of travel data covering a total of 190,000 driving days and 9.5 million VKT. Specifically, we look at overall performance of the distributions on the data using four goodness of fit measures, as well as the consequence of choosing one distribution over the others for two common PEV applications: the days requiring adaptation for battery electric vehicles and the utility factor for plug-in hybrid electric vehicles. We find the Weibull distribution to fit most vehicles well but not all and at the same time yielding good predictions for PEV related attributes. Furthermore, the choice of distribution impacts PEV usage factors. Here, the Weibull distribution yields reliable estimates for electric vehicle applications whereas the log-normal distribution yields more conservative estimates for PEV usage factors. Our results help to guide the choice of distribution for a specific research question utilising driving data and provide a methodological advancement in the application of distribution functions to longitudinal driving data.

      PubDate: 2017-04-30T06:18:27Z
      DOI: 10.1016/j.trb.2017.04.008
      Issue No: Vol. 101 (2017)
  • Robust routing and timetabling in complex railway stations
    • Authors: Sofie Burggraeve; Pieter Vansteenwegen
      Pages: 228 - 244
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Sofie Burggraeve, Pieter Vansteenwegen
      In nearly saturated station areas the limited capacity is one of the main reasons of delay propagation. Spreading the trains well in time and space in these areas has a big impact on the passenger robustness, i.e. the total travel time in practice of all passengers in the railway network in case of frequently occurring small delays. We focus on improving the performance in the bottleneck of the network in order to improve the performance of the whole railway network. This paper proposes a method that builds from scratch a routing plan and a cyclic timetable that optimizes the infrastructure occupation and the passenger robustness. An integer linear routing model assigns, without considering a timetable, every train to a route such that the maximal node usage is minimized and that the number of times that each node is used, is quadratically penalized. Thereafter, a mixed integer linear timetabling model assigns to each train the blocking times at which the nodes on its route, assigned by the routing model, are reserved and released. Different from other approaches is that we focus on the occupation of the railway infrastructure before constructing the timetable. The approach is validated on the complex railway station area of Brussels (Belgium). Our routing plan and timetable from scratch improve the passenger robustness up to 11% compared to a reference timetable and routing plan composed by the Belgian railway infrastructure manager Infrabel and by up to 2% compared to a reference timetable and routing plan from literature.

      PubDate: 2017-04-30T06:18:27Z
      DOI: 10.1016/j.trb.2017.04.007
      Issue No: Vol. 101 (2017)
  • Macroscopic urban dynamics: Analytical and numerical comparisons of
           existing models
    • Authors: Guilhem Mariotte; Ludovic Leclercq; Jorge A. Laval
      Pages: 245 - 267
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Guilhem Mariotte, Ludovic Leclercq, Jorge A. Laval
      Large-scale network modeling using the Macroscopic Fundamental Diagram (MFD) is widely based on the single-reservoir model, where the variation of the accumulation of circulating vehicles in the reservoir equals inflow minus outflow. However, inconsistent lags for information propagation between boundaries may be observed with this single accumulation-based model. For example, outflow is reacting too fast when inflow varies rapidly, whereas this information should be carried by vehicles that are never driving faster than the free-flow speed. To overcome this limitation, a trip-based model has been recently proposed, but whose solution cannot be obtained analytically. In this paper we compare both models under piecewise linear MFD and a piecewise constant demand. These assumptions allow to establish the exact solution of the accumulation-based model, and continuous approximations of the trip-based model at any order using Taylor series. Moreover, a flexible event-based simulation framework is implemented to solve the latter model, making it a promising tool to account for heterogeneity in distance traveled. Thanks to these resolution schemes we are able to measure the inaccuracy of the accumulation-based approach when the demand varies rapidly, and propose a validity domain for this model. Other applications with different trip lengths and supply limitations are also discussed.

      PubDate: 2017-05-04T01:13:02Z
      DOI: 10.1016/j.trb.2017.04.002
      Issue No: Vol. 101 (2017)
  • Dynamic macroscopic simulation of on-street parking search: A trip-based
    • Authors: Ludovic Leclercq; Alméria Sénécat; Guilhem Mariotte
      Pages: 268 - 282
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Ludovic Leclercq, Alméria Sénécat, Guilhem Mariotte
      This paper extends a trip-based aggregate dynamic traffic model to account for on-street parking search. The trip-based approach for a road network defined as a reservoir characterizes the internal traffic states by a macroscopic fundamental diagram (MFD) in speed while individualizing all vehicle travel distances. This paper first investigates distances to park for on-street parking based on real data in Lyon (France) and stochastic numerical experiments. An updated formulation compared to the existing literature is proposed for the relation between such distances and the parking occupancy. This new formulation is then incorporated into an event-based numerical scheme that solves the trip-based MFD model. The complete framework is able to account for different vehicle categories with respect to their parking strategies and to finely tune the related travel distances. Finally, the capabilities of the full framework are illustrated based on three different scenarios. The first two correspond to strategies with static and dynamic (reactive) switch of the demand from on- to off-street parking. While being very classical, they permit to demonstrate that the proposed model reacts as expected in such cases. The third scenario assesses the effect of a smart-parking technology that informs the users when a free parking spot is available on one of the downstream links at each intersection. In such a case, the model permits to estimate the benefit for the equipped users but also the impacts on all other vehicle categories. The three scenarios highlight that the proposed framework is versatile and can quickly provide a first assessment with a low calibration burden of different parking strategies or policies.
      Graphical abstract image

      PubDate: 2017-04-30T06:18:27Z
      DOI: 10.1016/j.trb.2017.04.004
      Issue No: Vol. 101 (2017)
  • Urban land use, sorting, and population density: A continuous logit model
    • Authors: Matthias Wrede
      Pages: 283 - 294
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Matthias Wrede
      This paper analyzes land use, sorting, and population density in a polycentric city. To this end, the paper develops a continuous spatial choice logit model of a closed polycentric city with multiple income classes and endogenous land use where households select their workplace and residence locations probabilistically. In contrast to the classic urban model with deterministic location choices, the continuous logit model predicts incomplete segregation of citizens who work in different business centers, and, therefore, cross commuting. The relative size of income elasticity of both land demand and commuting costs determines income sorting of individuals working in a particular business district. Due to heterogeneous preferences for residence locations and workplaces, this may not hold for the aggregate spatial pattern of multiple income classes. Finally, individual land use may decrease as distance between workplace and residence increases.

      PubDate: 2017-05-04T01:13:02Z
      DOI: 10.1016/j.trb.2017.04.010
      Issue No: Vol. 101 (2017)
  • Construction cost estimation: A parametric approach for better estimates
           of expected cost and variation
    • Authors: Omar Swei; Jeremy Gregory; Randolph Kirchain
      Pages: 295 - 305
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Omar Swei, Jeremy Gregory, Randolph Kirchain
      As project planners continue to move towards frameworks such as probabilistic life-cycle cost analysis to evaluate competing transportation investments, there is a need to enhance the current cost-estimation approaches that underlie these models to enable improved project selection. This paper presents an approach for cost estimation that combines a maximum likelihood estimator for data transformations with least angle regression for dimensionality reduction. The authors apply the proposed method for 15 different pavement bid items across five states in the United States. The results from the study demonstrate that the proposed approach frequently leads to consistent parametric estimates that address the structural bias and heteroscedasticity that plague the current cost-estimation procedures. Both of these aspects are particularly important for large-scale construction projects, where traditional methods tend to systematically underestimate expected construction costs and overestimate the associated variance.

      PubDate: 2017-06-05T04:03:51Z
      DOI: 10.1016/j.trb.2017.04.013
      Issue No: Vol. 101 (2017)
  • Step tolling in an activity-based bottleneck model
    • Authors: Zhi-Chun Li; William H.K. Lam; S.C. Wong
      Pages: 306 - 334
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Zhi-Chun Li, William H.K. Lam, S.C. Wong
      This paper investigates the step tolling problem in an activity-based bottleneck model in which activity scheduling utilities of commuters at home and at work vary by the time of day. The commuters choose their departure times from home to work in the morning to maximize their own scheduling utility. Step tolling models with homogeneous and heterogeneous preferences are presented. The properties of the models and the optimal step toll schemes with constant and linear time-varying marginal activity utilities are analytically explored and compared. It was found that for a given number of toll steps the efficacy of a step toll in terms of queuing removal rate is higher in the activity-based bottleneck model with linear marginal utilities than in the conventional bottleneck model with constant marginal utilities, and ignoring the preference heterogeneity of commuters would underestimate the efficacy of a step toll.

      PubDate: 2017-05-11T01:20:58Z
      DOI: 10.1016/j.trb.2017.04.001
      Issue No: Vol. 101 (2017)
  • Crowd behaviour and motion: Empirical methods
    • Authors: Milad Haghani; Majid Sarvi
      Abstract: Publication date: Available online 5 July 2017
      Source:Transportation Research Part B: Methodological
      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.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.017
  • Special issue on “Green urban transportation”
    • Authors: W.Y. Szeto; Anthony Chen
      Abstract: Publication date: Available online 30 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): W.Y. Szeto, Anthony Chen

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.011
  • The optimal time to evacuate: A behavioral dynamic model on Louisiana
           resident data
    • Authors: Nayel Urena Serulle; Cinzia Cirillo
      Abstract: Publication date: Available online 29 June 2017
      Source:Transportation Research Part B: Methodological
      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: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.004
  • Co-Evolutionary path optimization by Ripple-Spreading algorithm
    • Authors: Xiao-Bing Hu; Ming-Kong Zhang; Qi Zhang; Jian-Qin Liao
      Abstract: Publication date: Available online 24 June 2017
      Source:Transportation Research Part B: Methodological
      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: 2017-06-27T03:32:32Z
      DOI: 10.1016/j.trb.2017.06.007
  • On joint railway and housing development: Housing-led versus railway-led
    • Authors: Fai Hong
      Abstract: Publication date: Available online 23 June 2017
      Source:Transportation Research Part B: Methodological
      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: 2017-06-27T03:32:32Z
  • Robust uncapacitated hub location
    • Authors: Carlos Armando Zetina; Ivan Contreras; Jean-François Cordeau; Ehsan Nikbakhsh
      Abstract: Publication date: Available online 23 June 2017
      Source:Transportation Research Part B: Methodological
      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: 2017-06-27T03:32:32Z
      DOI: 10.1016/j.trb.2017.06.008
  • Dynamic optimal real-time algorithm for signals (DORAS): Case of isolated
           roadway intersections
    • Authors: Xiubin Bruce Wang; Xiaowei Cao; Changjun Wang
      Abstract: Publication date: Available online 17 June 2017
      Source:Transportation Research Part B: Methodological
      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: 2017-06-20T04:28:12Z
      DOI: 10.1016/j.trb.2017.06.005
  • Stochastic user equilibrium traffic assignment with equilibrated parking
           search routes
    • Authors: Adam Pel; Emmanouil Chaniotakis
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Adam J. Pel, Emmanouil Chaniotakis
      In this paper we define and formulate the concept of parking search routes (PSR) where a driver visits a sequence of parking locations until the first vacant parking spot is found and in doing so may account for (expected) parking probabilities. From there we define and formulate the stochastic user equilibrium (SUE) traffic assignment in which no driver, by unilaterally changing its PSR, can lower its perceived expected generalized costs. Recognizing the interdependency between PSR flows, travel times and parking probabilities, we propose a queuing model in order to compute endogenous parking probabilities accounting for these factors as well as maximum admissible search times. To solve the SUE assignment with equilibrated PSR we propose a solution algorithm, including a method for PSR choice set generation. The model is implemented and applied both to a number of experimental cases to verify its properties and to a real-life setting to illustrate its usefulness in parking-related studies.

      PubDate: 2017-04-16T06:18:01Z
  • Rolling stock rescheduling in passenger railway transportation using
           dead-heading trips and adjusted passenger demand
    • Authors: Joris Wagenaar; Leo Kroon Ioannis Fragkos
      Abstract: Publication date: July 2017
      Source:Transportation Research Part B: Methodological, Volume 101
      Author(s): Joris Wagenaar, Leo Kroon, Ioannis Fragkos
      In this paper we introduce dead-heading trips and adjusted passenger demand in the Rolling Stock Rescheduling Problem (RSRP). Unfortunately, disruptions disturb passenger railway transportation on a daily basis. Such a disruption causes infeasibilities in the timetable, rolling stock circulation, and crew schedule. We propose a Mixed-Integer Linear Programming model to tackle the RSRP. This formulation includes the possibility of using dead-heading trips (moving empty trains) during, and after, a disruption. Furthermore, passenger flows are included to handle the adjusted passenger demand after the occurrence of a disruption. Many rolling stock rescheduling models are unable to cope with changing passenger demand. In this paper we include passenger demand on a more accurate level in the RSRP. We have tested the model on different cases from Netherlands Railways. The results show that dead-heading trips are useful to reduce the number of cancelled trips and that adjusted passenger demand has a large influence on the rescheduled circulation.

      PubDate: 2017-04-16T06:18:01Z
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