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  Subjects -> TRANSPORTATION (Total: 168 journals)
    - AIR TRANSPORT (8 journals)
    - AUTOMOBILES (22 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (6 journals)
    - SHIPS AND SHIPPING (32 journals)
    - TRANSPORTATION (95 journals)

TRANSPORTATION (95 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 81)
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: 9)
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: 198)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 12)
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: 8)
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: 14)
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: 12)
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: 31)
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  [3034 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)
       
  • 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
           transit
    • 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
           optimization
    • 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
           lines
    • 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
           pricing
    • 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
           structure✰,✰✰
    • 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
           approach
    • 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)
       
  • Deficit function related to public transport: 50 year retrospective, new
           developments, and prospects
    • Authors: Tao Liu; Avishai (Avi) Ceder
      Pages: 1 - 19
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Tao Liu, Avishai (Avi) Ceder
      The Deficit Function (DF), with its graphical concept and modelling, was introduced 50 years ago by Linis and Maksim (1967) under the title of “On the problem of constructing routes.” Since then, there have been many developments in the understanding of the theoretical, methodological and application aspects of the DF concept. This work, for the first time, makes a comprehensive and thorough retrospective examination of the major developments of DF modelling and applications in public transport (PT) planning and operations over the past 50 years, introduces some new developments, and offers future research directions. It is shown and proven that the graphical DF concept helps in creating efficient PT vehicle schedules, timetables, crew duties, networks of routes, bus rapid transit systems, and operational parking spaces. For instance, in one large bus company the total number of vehicles and crew duties were reduced by 6% to 12% and 8% to 15%, respectively. This work intends to stimulate further use of the DF concept as a bridge between the world of researchers and the world of practitioners.

      PubDate: 2017-02-05T15:21:38Z
      DOI: 10.1016/j.trb.2017.01.015
      Issue No: Vol. 100 (2017)
       
  • Taxi market equilibrium with third-party hailing service
    • Authors: Xinwu Qian; Satish V. Ukkusuri
      Pages: 43 - 63
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Xinwu Qian, Satish V. Ukkusuri
      With the development and deployment of new technologies, the oligopolistic taxi industry is transforming into a shared market with coexistence of both traditional taxi service (TTS) and app-based third-party taxi service (ATTS). The ATTS is different from TTS in both entry policy and fare setting, and brings competition into the market. To account for the revolution of the taxi industry, in this study, we analyze the characteristics of the TTS and ATTS, model the taxi market as a multiple-leader-follower game at the network level, and investigate the equilibrium of taxi market with competition (TMC Equilibrium). In particular, passengers are modeled as the leaders who seek to minimize their travel cost associated with taxi rides. Followers involve TTS and ATTS drivers, who compete for passengers to maximize their revenue. The network model captures selfish behavior of passengers and drivers in the taxi market, and we prove the existence of TMC Equilibrium for the proposed model using variational inequality formulations. An iterative algorithm is further developed to find the TMC Equilibrium, which corresponds to the strongly stationary point of the multi-leader-follower game. Based on numerical results, it is observed that fleet size and pricing policy are closely associated with the level of competition in the market and may have significant impact on total passengers cost, average waiting time, and fleet utilization.

      PubDate: 2017-02-12T04:53:32Z
      DOI: 10.1016/j.trb.2017.01.012
      Issue No: Vol. 100 (2017)
       
  • Urban intermodal terminals: The entropy maximising facility location
           problem
    • Authors: Collins Teye; Michael G H Bell; Michiel C J Bliemer
      Pages: 64 - 81
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Collins Teye, Michael G H Bell, Michiel C J Bliemer
      An important problem confronting port cities is where and how to accommodate port growth. Larger ships combined with increased container throughput require more yard space and generate more traffic, straining the urban fabric in the vicinity of the port. A promising solution to this problem is the development of urban intermodal container terminals (IMTs) that interface with both road and rail (or possibly inland waterway) networks. This raises two linked choices; where to locate the intermodal terminals and what will be their likely usage by multiple shippers, each having a choice of whether or not to use the IMT as part of an intermodal transport chain. The use of an IMT by a shipper indicates the shipper's choice of intermodal transport, which comprises a combined use of a high capacity mode (rail or barge between the port and the IMT) and trucks (between the IMT and the cargo origin or destination). The overall problem therefore comprises a mode choice problem embedded within a facility location problem. This paper employs the method of entropy maximisation to combine a logit mode choice model with a facility location model, leading to a non-linear mixed integer programming model. The principal features of the entropy maximising facility location model are illustrated by small and large numerical examples.

      PubDate: 2017-02-12T04:53:32Z
      DOI: 10.1016/j.trb.2017.01.014
      Issue No: Vol. 100 (2017)
       
  • Offset optimization in signalized traffic networks via semidefinite
           relaxation
    • Authors: Samuel Coogan; Eric Kim; Gabriel Gomes; Murat Arcak; Pravin Varaiya
      Pages: 82 - 92
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Samuel Coogan, Eric Kim, Gabriel Gomes, Murat Arcak, Pravin Varaiya
      We study the problem of selecting offsets of the traffic signals in a network of signalized intersections to reduce queues of vehicles at all intersections. The signals in the network have a common cycle time and a fixed timing plan. It is assumed that the exogenous demands are constant or periodic with the same period as the cycle time and the intersections are under-saturated. The resulting queuing processes are periodic. These periodic processes are approximated by sinusoids. The sinusoidal approximation leads to an analytical expression of the queue lengths at every intersection as a function of the demands and the vector of offsets. The optimum offset vector is the solution of a quadratically constrained quadratic program (QCQP), which is solved via its convex semidefinite relaxation. Unlike existing techniques, our approach accommodates networks with arbitrary topology and scales well with network size. We illustrate the result in two case studies. The first is an academic example previously proposed in the literature, and the second case study consists of an arterial corridor network in Arcadia, California.

      PubDate: 2017-02-19T05:43:49Z
      DOI: 10.1016/j.trb.2017.01.016
      Issue No: Vol. 100 (2017)
       
  • Modeling airport capacity choice with real options
    • Authors: Yi-bin Xiao; Xiaowen Fu; Tae H. Oum; Jia Yan
      Pages: 93 - 114
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Yi-bin Xiao, Xiaowen Fu, Tae H. Oum, Jia Yan
      This study models airport capacity choice when a real option for expansion can be purchased. Facing demand uncertainty, an airport first determines the capacity for immediate investment (the prior capacity) and the size of the land or other resources to be reserved for possible future expansion (the reserve). Once demand is observed, the airport can use a portion of the reserve to build extra capacity and set airport charge. Our analytical results show that if demand uncertainty is low and capacity and reserve costs are relatively high, an airport will not acquire a real option for expansion. Otherwise, it can use an expansion option to improve its expected profit or social welfare. Both the magnitude of profit or welfare gain and the optimal size of the reserve increase with demand uncertainty. A higher reserve cost leads to a larger prior capacity and a smaller reserve, whereas a higher capital cost leads to lower prior capacity. A profit-maximizing airport would choose a smaller prior capacity and reserve than would a welfare-maximizing airport. Competition within the airline market promotes airport capacity investment and the adoption of real options by profit-maximizing airports, whereas airport commercial services increase prior capacity but not the reserve.

      PubDate: 2017-02-19T05:43:49Z
      DOI: 10.1016/j.trb.2017.02.001
      Issue No: Vol. 100 (2017)
       
  • A branch-and-price algorithm for the vehicle routing problem with roaming
           delivery locations
    • Authors: Gizem Ozbaygin; Oya Ekin Karasan; Martin Savelsbergh; Hande Yaman
      Pages: 115 - 137
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Gizem Ozbaygin, Oya Ekin Karasan, Martin Savelsbergh, Hande Yaman
      We study the vehicle routing problem with roaming delivery locations in which the goal is to find a least-cost set of delivery routes for a fleet of capacitated vehicles and in which a customer order has to be delivered to the trunk of the customer’s car during the time that the car is parked at one of the locations in the (known) customer’s travel itinerary. We formulate the problem as a set-covering problem and develop a branch-and-price algorithm for its solution. The algorithm can also be used for solving a more general variant in which a hybrid delivery strategy is considered that allows a delivery to either a customer’s home or to the trunk of the customer’s car. We evaluate the effectiveness of the many algorithmic features incorporated in the algorithm in an extensive computational study and analyze the benefits of these innovative delivery strategies. The computational results show that employing the hybrid delivery strategy results in average cost savings of nearly 20% for the instances in our test set.

      PubDate: 2017-02-19T05:43:49Z
      DOI: 10.1016/j.trb.2017.02.003
      Issue No: Vol. 100 (2017)
       
  • A model of pedestrian delay at unsignalized intersections in urban
           networks
    • Authors: Yinan Zheng; Lily Elefteriadou
      Pages: 138 - 155
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Yinan Zheng, Lily Elefteriadou
      Delay is an important performance measure for pedestrian crossings considering their interactions with other road users. This study provides an improved analytical model to mathematically estimate pedestrian delay using renewal theory, which considers driver yielding and vehicle platooning. A generalized model is first provided to accommodate different traffic flow and driver behavior assumptions. Then the proposed model is developed on the basis of a mixture of free traffic and platooned traffic with consideration of driver yielding behaviors to better replicate field conditions in an urban setting. A second application using the HCM 2010 assumptions is also derived to compare it to the HCM 2010 model. Lastly, field data were collected and used for validation from two locations: Gainesville, FL and Washington, D.C. A simulation via MATLAB is performed to evaluate the model results for a variety of cases. The comparisons to the field data as well as the simulation confirm the applicability and accuracy of the proposed model. It is also found that the current HCM 2010 model overestimates the pedestrian delay compared with field data.

      PubDate: 2017-02-26T02:02:49Z
      DOI: 10.1016/j.trb.2017.01.018
      Issue No: Vol. 100 (2017)
       
  • Optimal transportation and shoreline infrastructure investment planning
           under a stochastic climate future
    • Authors: Ali Asadabadi; Elise Miller-Hooks
      Pages: 156 - 174
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Ali Asadabadi, Elise Miller-Hooks
      This paper studies the problem of optimal long-term transportation investment planning to protect from and mitigate impacts of climate change on roadway performance. The problem of choosing the extent, specific system components, and timing of these investments over a long time horizon (e.g., 40–60 years) is modeled as a multi-stage, stochastic, bi-level, mixed-integer program wherein cost-effective investment decisions are taken in the upper level. The effects of possible episodic precipitation events on experienced travel delays are estimated from solution of a lower-level, traffic equilibrium problem. The episodic events and longer-term sea level changes exist on different time scales, making their integration a crucial element in model development. The optimal investment strategy is obtained at a Stackelberg equilibrium that is reached upon solution to the bilevel program. A recursive noisy genetic algorithm (rNGA), designed to address large-scale applications, is proposed for this purpose. The rNGA seeks the optimal combination of investment decisions to take now given only probabilistic information on the predicted sea level rise trend for a long planning horizon and associated likely extreme climatic events (in terms of their frequencies and intensities) that might arise over that planning period. The proposed solution method enables the evaluation of decisions concerning where, when and to what level to make infrastructure investments. The proposed rNGA has broad applicability to more general multi-stage, stochastic, bilevel, nonconvex, mixed integer programs that arise in many applications. The proposed solution methodology is demonstrated on an example representing a portion of the Washington, D.C. Greater Metropolitan area adjacent to the Potomac River.

      PubDate: 2017-02-26T02:02:49Z
      DOI: 10.1016/j.trb.2016.12.023
      Issue No: Vol. 100 (2017)
       
  • A time allocation model considering external providers
    • Authors: Jorge Rosales-Salas; Sergio R. Jara-Díaz
      Pages: 175 - 195
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Jorge Rosales-Salas, Sergio R. Jara-Díaz
      Time use models have advanced significantly during the last decade: their theoretical approach has been refined, functional forms have improved and new constraints have been incorporated, among other aspects. However, there is an incipient development of an issue of great importance: the role and influence of external agents on individual time allocation and the recognition of unpaid/domestic work as a distinctive area of research. In this paper we introduce domestic production and the potential domestic work substitution by external providers in a time use model, improving its formulation and the interpretation of the values of time. We take into account the marginal utility of domestic activities, their cost - either if self-produced or hired - and the relation between the domestic output and domestic work hours considering the difference in skills between providers and household members. A stochastic system of equations is proposed and estimated using three Dutch time use and expenses data sets, from which the values of leisure and work are computed and analyzed. Comparative results show that a model with no consideration of hired domestic providers overestimates the values of leisure.

      PubDate: 2017-02-28T02:04:10Z
      DOI: 10.1016/j.trb.2017.01.019
      Issue No: Vol. 100 (2017)
       
  • Towards vehicle automation: Roadway capacity formulation for traffic mixed
           with regular and automated vehicles
    • Authors: Danjue Chen; Soyoung Ahn; Madhav Chitturi; David A. Noyce
      Pages: 196 - 221
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Danjue Chen, Soyoung Ahn, Madhav Chitturi, David A. Noyce
      This paper provides formulations of traffic operational capacity in mixed traffic, consisting of automated vehicles (AVs) and regular vehicles, when traffic is in equilibrium. The capacity formulations take into account (1) AV penetration rate, (2) micro/mesoscopic characteristics of regular and automated vehicles (e.g., platoon size, spacing characteristics), and (3) different lane policies to accommodate AVs such as exclusive AV and/or RV lanes and mixed-use lanes. A general formulation is developed to determine the valid domains of different lane policies and more generally, AV distributions across lanes with respect to demand, as well as optimal solutions to accommodate AVs.

      PubDate: 2017-03-11T02:33:02Z
      DOI: 10.1016/j.trb.2017.01.017
      Issue No: Vol. 100 (2017)
       
  • A dynamic taxi traffic assignment model: A two-level continuum
           transportation system approach
    • Authors: Jiancheng Long; W.Y. Szeto; Jie Du; R.C.P. Wong
      Pages: 222 - 254
      Abstract: Publication date: June 2017
      Source:Transportation Research Part B: Methodological, Volume 100
      Author(s): Jiancheng Long, W.Y. Szeto, Jie Du, R.C.P. Wong
      This paper proposes a two-level continuum transportation system approach to modeling a dynamic taxi traffic assignment (DTTA) problem in a dense network with real-time traffic information provision and three types of vehicles, including private cars, occupied taxis, and vacant taxis. The proposed approach treats the dense network as a continuum in the first level, in which private car and occupied taxi drivers are free to choose their paths in a two-dimensional continuous space. The proposed approach also divides the modeling region into many identical squares to form a cell-based network in the second level, in which the cells are classified into two categories: target cell with an acceptable expected rate of return (EROR) to vacant taxi drivers and non-target cell with an unacceptable EROR. The EROR associated with a cell is the ratio of the cumulative expected profit of a taxi driver who successfully picks up a customer during the customer search that starts from that cell to the sum of expected search time for this customer and expected occupied travel time to serve this customer. Based on the cell-based network, we develop a cell-based intervening opportunity model to capture the fact that vacant taxi drivers can meet a customer on the way to their destination zones and estimate the EROR. Each vacant taxi driver has a mixed strategy to determine his/her customer-search direction according to the EROR: Each vacant taxi driver in a target cell selects its neighbor cells with maximum EROR, and each vacant taxi driver in a non-target cell selects the travel time-based shortest path to his/her target cell. Meanwhile, each private car driver chooses the path that minimizes his/her own generalized travel cost, and each occupied taxi driver chooses the path that minimizes his/her customer's generalized in-vehicle travel cost. In our model, traffic density in the system is governed by the conservation law (CL), and the flow directions of different vehicles are determined by the path-choice strategies of their drivers, which are captured by Hamilton–Jacobi (HJ) equations. Both the proposed CL and HJ equations can be solved by the Lax–Friedrichs scheme, which forms the backbone of the developed solution algorithm. Finally, numerical examples and a case study are used to demonstrate the properties of the model, the performance of the solution algorithm, and the value of using our methodology for estimating network performance.

      PubDate: 2017-04-30T06:18:27Z
      DOI: 10.1016/j.trb.2017.02.005
      Issue No: Vol. 100 (2017)
       
  • 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
       
  • Networked traffic state estimation involving mixed fixed-mobile sensor
           data using Hamilton-Jacobi equations
    • Authors: Edward S. Canepa; Christian G. Claudel
      Abstract: Publication date: Available online 17 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Edward S. Canepa, Christian G. Claudel
      Nowadays, traffic management has become a challenge for urban areas, which are covering larger geographic spaces and facing the generation of different kinds of traffic data. This article presents a robust traffic estimation framework for highways modeled by a system of Lighthill Whitham Richards equations that is able to assimilate different sensor data available. We first present an equivalent formulation of the problem using a Hamilton–Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton–Jacobi equation are linear ones. We then pose the problem of estimating the traffic density given incomplete and inaccurate traffic data as a Mixed Integer Program. We then extend the density estimation framework to highway networks with any available data constraint and modeling junctions. Finally, we present a travel estimation application for a small network using real traffic measurements obtained obtained during Mobile Century traffic experiment, and comparing the results with ground truth data.

      PubDate: 2017-06-20T04:28:12Z
      DOI: 10.1016/j.trb.2017.05.016
       
  • A train rescheduling model integrating speed management during disruptions
           of high-speed traffic under a quasi-moving block system
    • Authors: Peijuan Xu; Francesco Corman; Qiyuan Peng; Xiaojie Luan
      Abstract: Publication date: Available online 10 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Peijuan Xu, Francesco Corman, Qiyuan Peng, Xiaojie Luan
      Chinese high-speed railways faced a fast development in recent years. Their performances are still confronted with disruptions unavoidably, which impact on the reliability of the traffic and passenger satisfaction. This paper presents a rescheduling model which is able to solve the critical problem of effective disruption management (namely, fast and dynamic train speed adaptation, supervision of braking and changing train sequence due to incidents, warnings or alarms), and consider in detail the signalling and safety systems based on a quasi-moving block system with variable headways. We integrate the modelling of efficient traffic management measures and the supervision of speed, braking and headway in one general job-shop model. We use a commercial solver with a custom-designed two-step method to speed up the procedure in order to solve instances from real-world high-speed networks in China quickly. Overall, the approach guarantees the resolution of the traffic control and speed management within few minutes of computation time. The output demonstrates that the proposed approach can achieve a reduction of train delays by 70% compared to the solution determined by keeping the order of the original timetable, and get the optimality for more than 90% of instances with a realistic case.

      PubDate: 2017-06-15T04:24:21Z
      DOI: 10.1016/j.trb.2017.05.008
       
  • When adjacent lane dependencies dominate the uncongested regime of the
           fundamental relationship
    • Authors: Balaji Ponnu; Benjamin Coifman
      Abstract: Publication date: Available online 10 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Balaji Ponnu, Benjamin Coifman
      This paper presents an empirical study of the fundamental relationship between speed, v, and flow, q, (denoted vqFR) under low flow in the uncongested regime. Using new analytical techniques to extract more information from loop detector data, the vqFR from a time of day HOV lane exhibits high v that slowly drops as q increases. This curve arises after binning several million vehicles by q and only considering those bins with q < 1200 vph. A surprising thing happens when further binning the data by the adjacent lane speed (v2): the vqFR expands in to a fan of curves that decrease in magnitude and slope with decreasing v2. Yet each curve in the fan continues to exhibit uncongested trends, ranging from a flat curve consistent with recent editions of the Highway Capacity Manual to downward sloping curves. It is shown that this behavior was not due to the HOV operations per se, the same behavior also arises in the non-HOV period when the lane serves all vehicles and it is also observed at another facility without any HOV restrictions. This dependency on the adjacent lane is absent from most traffic flow theories. Taking a broader view, four different factors appear to limit the speed a driver takes: (i) the roadway geometry, (ii) the posted speed limit, (iii) the vehicle ahead (car following), and (iv) traffic conditions in the adjacent lane. Whichever constraint is most binding determines the driver's speed. While the first three constraints are found in the literature, this work contributes the fourth, as per above. When the speed limit is the most binding constraint the uncongested regime of the vqFR is roughly flat with a near constant speed over a wide range of q. When the roadway geometry is the binding constraint, e.g., due to the lack of speed limits, drivers are able to travel fast enough to be sensitive to the vehicle ahead and exhibit lower v as q increases. Car following is by definition in the congested regime and thus, beyond the scope of this paper. Finally, the present work shows that as the adjacent lane moves slower, the uncongested drivers choose speeds below the speed limit and once more exhibit lower v as q increases. Although the chosen v is below the speed limit, the drivers continue to exhibit behavior consistent with the uncongested regime.

      PubDate: 2017-06-15T04:24:21Z
      DOI: 10.1016/j.trb.2017.05.006
       
  • Models for technology choice in a transit corridor with elastic demand
    • Authors: Luigi Moccia; Giovanni Giallombardo; Gilbert Laporte
      Abstract: Publication date: Available online 9 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Luigi Moccia, Giovanni Giallombardo, Gilbert Laporte
      We present two optimization models for a transit line under the assumption that the demand is elastic and can be approximated by a linear function of fare and passenger travel time components. These models can be used to strategically evaluate technology choices. We study the effect of demand elasticity on the technology choice by analytic and numerical comparison with some fixed demand models. We assume a range of objective functions having as two extrema the maximization of operator’s profit and the maximization of social welfare. We show both analytically and numerically that accounting for demand elasticity does not change the conclusions that can be derived by an equivalent fixed demand model. This invariance holds for a broad range of objective functions in the elastic case. The significant difference between the two objective function extrema lies in the proportions of captured demand.

      PubDate: 2017-06-10T04:13:35Z
      DOI: 10.1016/j.trb.2017.06.001
       
  • A game-theoretic model of car ownership and household time allocation
    • Authors: Mingzhu Yao; Donggen Wang; Hai Yang
      Abstract: Publication date: Available online 9 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Mingzhu Yao, Donggen Wang, Hai Yang
      The explosive growth of private cars in China and other developing countries has attracted a great deal of renewed research interest in car ownership. This paper investigates households’ car ownership decision-making process from the perspective of household time allocation. Applying the game-theoretic approach to capturing household members’ interactive decision-making mechanism, we propose a two-stage model that links household members’ short-term time allocation decisions to long-term car ownership decisions. The first stage models the bargaining of household members (e.g., husband and wife) over the car ownership decision, taking into consideration of government policies for regulating car ownership; and the second stage is a generalized Nash equilibrium model for activity-travel pattern analysis incorporating individuals’ interactions concerning activity participation. The existence and uniqueness of the generalized Nash equilibrium solution is examined, and a heuristic procedure that combines backwards induction and method of exhaustion is adopted to solve the two-stage game. The proposed model is applied to an empirical case study in Beijing, which demonstrates the applicability of the model in predicting car ownership and examining interactions between car ownership and household time allocation. The empirical model is applied to assess the impacts of plate-number-based vehicle usage rationing policies on car ownership and time allocation to travel and daily activities. Results show that the model can be applied to evaluate the car ownership impacts of car usage rationing policies.

      PubDate: 2017-06-10T04:13:35Z
      DOI: 10.1016/j.trb.2017.05.015
       
  • Path-constrained traffic assignment: Modeling and computing network
           impacts of stochastic range anxiety
    • Authors: Chi Xie; Tong-Gen Wang; Xiaoting Pu; Ampol Karoonsoontawong
      Abstract: Publication date: Available online 7 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Chi Xie, Tong-Gen Wang, Xiaoting Pu, Ampol Karoonsoontawong
      It is notoriously known that range anxiety is one of the major barriers that hinder a wide adoption of plug-in electric vehicles, especially battery electric vehicles. Recent studies suggested that if the caused driving range limit makes any impact on travel behaviors, it more likely occurs on the tour or trip chain level than the trip level. To properly assess its impacts on travel choices and traffic congestion, this research is devoted to studying a new network equilibrium problem that implies activity location and travel path choices on the trip chain level subject to stochastic driving ranges. Convex optimization and variational inequality models are respectively constructed for characterizing the equilibrium conditions under both discretely and continuously distributed driving ranges. For deriving the equilibrium flow solutions for these problem cases, we suggested different adaptations of a well-known path-based algorithm—the projected gradient method. While the problem instance with a discrete number of driving ranges can be simply treated as a multi-class version of its deterministic counterpart, the one with continuous driving ranges poses a much more complicated situation. To overcome this arising modeling and algorithmic complication, we introduce a couple of newly defined variables, namely, path-indexed travel subdemand rate and traffic subflow rate, by which the demand and flow rates as well as their corresponding feasible path sets can be dynamically indexed in the solution process with reference to path lengths. An illustrative example with various types and forms of driving range distributions demonstrates the applicability of the proposed modeling and solution methods and various impacts of the heterogeneity of range anxiety on network flows and computational costs. The numerical analysis results from this example show that stochastic driving ranges confine network flows in a different way from deterministic or no driving ranges and the projected gradient procedure relying on dynamically indexed subdemand and subflow rates is generally preferable to its counterpart on pre-indexed ones for both the discrete and continuous driving range cases.

      PubDate: 2017-06-10T04:13:35Z
      DOI: 10.1016/j.trb.2017.04.018
       
  • Macroscopic modelling and robust control of bi-modal multi-region urban
           road networks
    • Authors: Konstantinos Ampountolas; Nan Zheng; Nikolas Geroliminis
      Abstract: Publication date: Available online 7 June 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Konstantinos Ampountolas, Nan Zheng, Nikolas Geroliminis
      The paper concerns the integration of a bi-modal Macroscopic Fundamental Diagram (MFD) modelling for mixed traffic in a robust control framework for congested single- and multi-region urban networks. The bi-modal MFD relates the accumulation of cars and buses and the outflow (or circulating flow) in homogeneous (both in the spatial distribution of congestion and the spatial mode mixture) bi-modal traffic networks. We introduce the composition of traffic in the network as a parameter that affects the shape of the bi-modal MFD. A linear parameter varying model with uncertain parameter the vehicle composition approximates the original nonlinear system of aggregated dynamics when it is near the equilibrium point for single- and multi-region cities governed by bi-modal MFDs. This model aims at designing a robust perimeter and boundary flow controller for single- and multi-region networks that guarantees robust regulation and stability, and thus smooth and efficient operations, given that vehicle composition is a slow time-varying parameter. The control gain of the robust controller is calculated off-line using convex optimisation. To evaluate the proposed scheme, an extensive simulation-based study for single- and multi-region networks is carried out. To this end, the heterogeneous network of San Francisco where buses and cars share the same infrastructure is partitioned into two homogeneous regions with different modes of composition. The proposed robust control is compared with an optimised pre-timed signal plan and a single-region perimeter control strategy. Results show that the proposed robust control can significantly: (i) reduce the overall congestion in the network; (ii) improve the traffic performance of buses in terms of travel delays and schedule reliability, and; (iii) avoid queues and gridlocks on critical paths of the network.

      PubDate: 2017-06-10T04:13:35Z
      DOI: 10.1016/j.trb.2017.05.007
       
  • 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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