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  Subjects -> TRANSPORTATION (Total: 172 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (22 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (6 journals)
    - SHIPS AND SHIPPING (34 journals)
    - TRANSPORTATION (96 journals)

TRANSPORTATION (96 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 90)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4)
Archives of Transport     Open Access   (Followers: 18)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 12)
Cities in the 21st Century     Open Access   (Followers: 13)
Economics of Transportation     Partially Free   (Followers: 12)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 11)
European Transport Research Review     Open Access   (Followers: 19)
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: 9)
IFAC-PapersOnLine     Open Access  
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 7)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 9)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 3)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 9)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 7)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 10)
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: 11)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 12)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 15)
International Journal of Transportation Science and Technology     Open Access   (Followers: 9)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 12)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 208)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 11)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 2)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 5)
Journal of Transport & Health     Hybrid Journal   (Followers: 8)
Journal of Transport and Land Use     Open Access   (Followers: 21)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 11)
Journal of Transport Geography     Hybrid Journal   (Followers: 22)
Journal of Transport History     Hybrid Journal   (Followers: 11)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 6)
Journal of Transportation Security     Hybrid Journal   (Followers: 1)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 12)
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     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: 18)
Open Journal of Safety Science and Technology     Open Access   (Followers: 9)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 1)
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: 15)
Promet : Traffic &Transportation     Open Access  
Public Transport     Hybrid Journal   (Followers: 17)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 5)
Revista Transporte y Territorio     Open Access   (Followers: 1)
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 10)
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: 1)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 5)
Transport     Hybrid Journal   (Followers: 14)
Transport and Telecommunication Journal     Open Access   (Followers: 4)
Transport in Porous Media     Hybrid Journal   (Followers: 1)
Transport Problems     Open Access   (Followers: 1)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 8)
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: 13)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 4)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 32)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 29)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 21)
Transportation Research Procedia     Open Access   (Followers: 5)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 32)
Transportation Science     Full-text available via subscription   (Followers: 19)
TRANSPORTES     Open Access   (Followers: 5)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 5)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 2)
Transportrecht     Unknown  
Travel Behaviour and Society     Full-text available via subscription   (Followers: 8)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 1)
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  [3175 journals]
  • Day-to-day modal choice with a Pareto improvement or zero-sum revenue
           scheme
    • Authors: Ren-Yong Guo; W.Y. Szeto
      Pages: 1 - 25
      Abstract: Publication date: April 2018
      Source:Transportation Research Part B: Methodological, Volume 110
      Author(s): Ren-Yong Guo, W.Y. Szeto
      We investigate the day-to-day modal choice of commuters in a bi-modal transportation system comprising both private transport and public transit. On each day, commuters adjust their modal choice, based on the previous day's perceived travel cost and intraday toll or subsidy of each mode, to minimize their perceived travel cost. Meanwhile, the transportation authority sets the number of bus runs and the tolls or subsidies of two modes on each day, based on the previous day's modal choice of commuters, to simultaneously reduce the daily total actual travel cost of the transportation system and achieve a Pareto improvement or zero-sum revenue target at a stationary state. The evolution process of the modal choice of commuters, associated with the strategy adjustment process of the authority, is formulated as a dynamical system model. We analyze several properties of the dynamical system with respect to its stationary point and evolutionary trajectory. Moreover, we introduce new concepts of Pareto improvement and zero-sum revenue in a day-to-day dynamic setting and propose the two targets’ implementations in either a prior or a posterior form. We show that, although commuters have different perceived travel costs for using the same travel mode, the authority need not know the probability distribution of perceived travel costs of commuters to achieve the Pareto improvement target. Finally, we give a set of numerical examples to show the properties of the model and the implementation of the toll or subsidy schemes.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.01.014
      Issue No: Vol. 110 (2018)
       
  • Service-oriented train timetabling with collaborative passenger flow
           control on an oversaturated metro line: An integer linear optimization
           approach
    • Authors: Jungang Shi; Lixing Yang; Jing Yang; Ziyou Gao
      Pages: 26 - 59
      Abstract: Publication date: April 2018
      Source:Transportation Research Part B: Methodological, Volume 110
      Author(s): Jungang Shi, Lixing Yang, Jing Yang, Ziyou Gao
      With the drastic increase of travel demands in urban areas, more and more metro lines are nowadays suffering from oversaturated situations, leading to the accumulation of passengers on platforms with potential accident risks. To further improve the service quality and reduce accident risks, this paper proposes an effective method for collaboratively optimizing the train timetable and accurate passenger flow control strategies on an oversaturated metro line. Through considering the dynamic characteristics of passenger flow, a rigorous integrated integer linear programming model is firstly formulated to minimize the total passenger waiting time at all of involved stations, in which the train timetable provides a service-oriented operation plan and optimal passenger flow control is imposed to avoid congestion on platforms within the transportation capacities. To solve the problem of interest efficiently, a hybrid algorithm, which combines an improved local search and CPLEX solver, is designed to search for high-quality solutions. Finally, two sets of numerical experiments, including a small-scale case and a real-world instance with operation data of the Beijing metro system, are implemented to demonstrate the performance and effectiveness of the proposed approaches.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.02.003
      Issue No: Vol. 110 (2018)
       
  • Joint production–inventory–location problem with multi-variate
           normal demand
    • Authors: Mehrdad Shahabi; Amirmahdi Tafreshian; Avinash Unnikrishnan; Stephen D. Boyles
      Pages: 60 - 78
      Abstract: Publication date: April 2018
      Source:Transportation Research Part B: Methodological, Volume 110
      Author(s): Mehrdad Shahabi, Amirmahdi Tafreshian, Avinash Unnikrishnan, Stephen D. Boyles
      This paper develops a mixed integer nonlinear programming formulation for the production–inventory–location problem with correlated demands across the retailers. Several structural results for special cases of the problem are derived and studied. A solution method based on the outer approximation of the nonlinear terms is developed to solve the problem. The efficiency of the proposed model and solution approach is investigated through extensive numerical studies. Ignoring correlations can increase the total costs of a production–location–inventory system. Accounting for correlations may lead to changes in supply chain configuration. The effect of capacity on computational times was more pronounced in lower correlations than higher correlations. In addition, we show that the efficiency of the solution method increases significantly for two special cases – when all products have the same holding cost and when the number of orders for different products at each warehouse is constrained to be the same.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.02.002
      Issue No: Vol. 110 (2018)
       
  • Conditional value-at-risk (CVaR) methodology to optimal train
           configuration and routing of rail hazmat shipments
    • Authors: S. Davod Hosseini; Manish Verma
      Pages: 79 - 103
      Abstract: Publication date: April 2018
      Source:Transportation Research Part B: Methodological, Volume 110
      Author(s): S. Davod Hosseini, Manish Verma
      Hazardous materials (hazmat) incidents are rare though the consequences could be catastrophic. The low probability–high consequence nature of such events mandate that a risk-averse plan be implemented for routing hazmat shipments. We propose a conditional value-at-risk (CVaR) methodology for routing rail hazmat shipments, using the best train configuration, over a given railroad network using the pre-defined train services such that the transport risk as measured by CVaR is minimized. Freight train derailment records were analyzed to model the behavior of railroad accidents, and to estimate conditional probabilities. The proposed methodology was used to study several problem instances generated using the realistic network of a railroad operator, and to demonstrate that the proposed methodology is superior to other measures for risk-averse routing of hazmat shipments and versatile enough to yield routes based on risk preferences of the decision makers.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.02.004
      Issue No: Vol. 110 (2018)
       
  • Marginal cost pricing for system optimal traffic assignment with recourse
           under supply-side uncertainty
    • Authors: Tarun Rambha; Stephen D. Boyles; Avinash Unnikrishnan; Peter Stone
      Pages: 104 - 121
      Abstract: Publication date: April 2018
      Source:Transportation Research Part B: Methodological, Volume 110
      Author(s): Tarun Rambha, Stephen D. Boyles, Avinash Unnikrishnan, Peter Stone
      Transportation networks are often subject to fluctuations in supply-side parameters such as capacity and free-flow travel time due to factors such as incidents, poor weather, and bottlenecks. In such scenarios, assuming that network arcs exist in a finite number of states with different delay functions with different probabilities, a marginal cost pricing scheme that leads to a socially optimal outcome is proposed. The suggested framework makes the behavioral assumption that travelers do not just choose paths but follow routing policies that respond to en route information. Specifically, it is assumed that travelers are fully-rational and that they compute the optimal online shortest path assuming full-reset. However, such policies may involve cycling, which is unrealistic in practice. Hence, a network transformation that helps restrict cycles up to a certain length is devised and the problem is reformulated as a convex optimization problem with symmetric delay functions. The results of numerical tests on the Sioux Falls test network are presented using the Frank–Wolfe algorithm.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.02.008
      Issue No: Vol. 110 (2018)
       
  • Managing rail transit peak-hour congestion with a fare-reward scheme
    • Authors: Hai Yang; Yili Tang
      Pages: 122 - 136
      Abstract: Publication date: April 2018
      Source:Transportation Research Part B: Methodological, Volume 110
      Author(s): Hai Yang, Yili Tang
      This paper describes a new fare-reward scheme for managing a commuter's departure time choice in a rail transit bottleneck, which aims to incentivize a shift in departure time to the shoulder periods of the peak hours to relieve queuing congestion at transit stations. A framework of the rail transit bottleneck is provided and the user equilibrium with a uniform-fare and the social optimum with service run-dependent fares are determined. A fare-reward scheme (FRS) is then introduced that rewards a commuter with one free trip during shoulder periods after a certain number of paid trips during the peak hours. For a given number of peak-hour commuters and ex-ante uniform fare, the FRS determines the free fare intervals and the reward ratio (the ratio of the free trips to the total number of trips, which is equivalent to the ratio of the number of rewarded commuters to the total number of commuters on each day during the peak hours). The new fare under the FRS is determined so that the transit operator's revenue remains unchanged before and after introducing the FRS. Our study indicates that, depending on the original fare, FRS results in an optimal reward ratio up to 50% and yields a reduction of system total time costs and average equilibrium trip costs by at least 25% and 20%, respectively.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.02.005
      Issue No: Vol. 110 (2018)
       
  • Impact of government subsidy on BOT contract design: Price, demand, and
           concession period
    • Authors: Fan Wang; Minghua Xiong; Baozhuang Niu; Xiaopo Zhuo
      Pages: 137 - 159
      Abstract: Publication date: April 2018
      Source:Transportation Research Part B: Methodological, Volume 110
      Author(s): Fan Wang, Minghua Xiong, Baozhuang Niu, Xiaopo Zhuo
      Private provision of logistics infrastructure through build-operate-transfer (BOT) contracts has become increasingly popular worldwide. These contracts involve incentive conflicts between private sector concerning profit and government concerning social welfare. To coordinate the incentive conflicts, the government usually subsidizes the private sector in practice. In this paper, we propose a stylized model to illustrate how to design an optimal BOT contract with government subsidy. We first derive optimal subsidy levels for the government to obtain optimal social welfare, given concession periods. We further observe that there exist both a substitution effect and a complementary effect between the concession period and the subsidy level. For the former (latter), the subsidy is decreasing (increasing) in the concession period, and the substitution effect can be strengthened if the government has subsidy budget constraint. Interestingly, we find that the private sector does not always prefer the longest concession period. A concession period less than the lifetime of the infrastructure may be more beneficial for the private sector. In contrast, the government's preferred concession period can be either zero or the longest concession period, depending on the unit construction cost and the government's inefficiency cost. We further find that, the incentives of the government and the private sector over the concession period can be aligned when the unit construction cost is low and the government's inefficiency cost is high. We also find that their incentives over the infrastructure's capacity utilization are always aligned throughout the BOT periods.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.02.006
      Issue No: Vol. 110 (2018)
       
  • Mathematical programming framework for modeling and comparing
           network-level pavement maintenance strategies
    • Authors: James C. Chu; Kai-Hsiang Huang
      Pages: 1 - 25
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): James C. Chu, Kai-Hsiang Huang
      This study proposes a mathematical programming framework to model and quantitatively compare different maintenance strategies for network-level highway pavements. The study develops mixed-integer linear programming models for various maintenance strategies that are commonly adopted in practice and in the literature. In developing these models, traffic, pavement age, and maintenance actions with heterogeneous effects are considered. The strategies include optimization-based, worst-first, best-first, and threshold-based strategies. To demonstrate the flexibility of the framework and present a practical situation in which engineering judgment is sometimes incorporated in pavement maintenance strategies, we further develop a mixed strategy. A solution procedure combining the off-shelf mixed-integer programming solver, greedy algorithms, and Lagrangian relaxation algorithms is developed to efficiently solve the models. Finally, a numerical example of a hypothetical network is established. Different maintenance strategies are applied given different budget levels, traffic loadings, and initial pavement conditions. The results of the numerical example are reasonable, and they provide insights into the efficient implementation of maintenance strategies. Results also show that the framework has the potential to aid maintenance agencies in evaluating maintenance strategies before they are implemented, improving pavement conditions, and reducing the budget for transportation infrastructure.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.005
      Issue No: Vol. 109 (2018)
       
  • The identical-path truck platooning problem
    • Authors: Nils Boysen; Dirk Briskorn; Stefan Schwerdfeger
      Pages: 26 - 39
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): Nils Boysen, Dirk Briskorn, Stefan Schwerdfeger
      Platooning has been identified as a promising way to reduce the carbon footprint and fuel consumption of freight transportation. Recent technological developments connecting a platoon via digital data transmission even allow that the driver of the front truck controls all (unmanned) follower vehicles. Existing research mainly focuses on the technological and safety aspects of controlling the trucks and their distances. However, the efficiency of platooning is not only dependent on the aerodynamic drag, which considerably reduces with decreasing inter-vehicle distance; it is also influenced by the platoon formation process. To explore the impact of this and other neglected aspects on the efficiency of platooning (i.e., the diffusion of platooning technology, maximum platoon lengths, and the trucks’ willingness-to-wait for partners) a basic scheduling problem for the platoon building process along a single path is investigated. By differentiating problem characteristics, e.g., the objective function, we derive different problem settings for which a detailed analysis of computational complexity is provided. Efficient algorithms are derived and applied to explore the impact of the diffusion of platooning technology, the maximum platoon length, and the tightness of time windows. Our results show that these factors can considerably reduce the positive effects of truck platooning, and, thus, the benefit may diminish.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.006
      Issue No: Vol. 109 (2018)
       
  • Shared parking problem: A novel truthful double auction mechanism approach
    • Authors: Haohan Xiao; Meng Xu; Ziyou Gao
      Pages: 40 - 69
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): Haohan Xiao, Meng Xu, Ziyou Gao
      Considering a parking platform with multiple slot demanders and multiple slot suppliers, this paper addresses two truthful double auction mechanisms for shared parking problem, where the demanders targeted by the proposed mechanisms are with flexible schedules and for non-work activities, and the suppliers are with the typical daily ‘driving go out early and come back at dusk’ pattern. To provide flexible match schemes and increase the trading scale, we allow “all-or-nothing” principle for demanders and “one-to-many” principle for suppliers. Based on the parking slot allocation rule and the transaction payment rule, we first relax the single output restriction (suppliers can only submit bids on a single unit of one commodity) and propose a “demander competition padding method (DC-PM)” auction mechanism, which is used to solve potential budget deficit. To avoid the likely distorted social welfare resulted by the DC-PM auction mechanism and to add budget surplus, we further modify the parking slot allocation rule and the transaction payment rule in the DC-PM auction mechanism, and propose a “modified demander competition padding method (MDC-PM)” auction mechanism. Three economical properties of both auction mechanisms, i.e. incentive compatibility, individual rationality and budget balance, are proved. Numerical experiments show that the proposed two auction mechanisms can realize asymptotic efficiency as both demanders and suppliers approach infinity. Moreover, the DC-PM auction mechanism is superior to the MDC-PM auction mechanism with respect to participants’ utilities and can maintain the strict lexicographic allocation order, and the MDC-PM auction mechanism outperforms the DC-PM auction mechanism in terms of welfare efficiency and platform's payoff. Issues of managerial implications for shared parking problem are further discussed in this paper.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.008
      Issue No: Vol. 109 (2018)
       
  • Pooling stated and revealed preference data in the presence of RP
           endogeneity
    • Authors: John Paul Helveston; Elea McDonnell Feit; Jeremy J. Michalek
      Pages: 70 - 89
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): John Paul Helveston, Elea McDonnell Feit, Jeremy J. Michalek
      Pooled discrete choice models combine revealed preference (RP) data and stated preference (SP) data to exploit advantages of each. SP data is often treated with suspicion because consumers may respond differently in a hypothetical survey context than they do in the marketplace. However, models built on RP data can suffer from endogeneity bias when attributes that drive consumer choices are unobserved by the modeler and correlated with observed variables. Using a synthetic data experiment, we test the performance of pooled RP–SP models in recovering the preference parameters that generated the market data under conditions that choice modelers are likely to face, including (1) when there is potential for endogeneity problems in the RP data, such as omitted variable bias, and (2) when consumer willingness to pay for attributes may differ from the survey context to the market context. We identify situations where pooling RP and SP data does and does not mitigate each data source’s respective weaknesses. We also show that the likelihood ratio test, which has been widely used to determine whether pooling is statistically justifiable, (1) can fail to identify the case where SP context preference differences and RP endogeneity bias shift the parameter estimates of both models in the same direction and magnitude and (2) is unreliable when the product attributes are fixed within a small number of choice sets, which is typical of automotive RP data. Our findings offer new insights into when pooling data sources may or may not be advisable for accurately estimating market preference parameters, including consideration of the conditions and context under which the data were generated as well as the relative balance of information between data sources.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.010
      Issue No: Vol. 109 (2018)
       
  • Continuous approximation for demand balancing in solving large-scale
           one-commodity pickup and delivery problems
    • Authors: Chao Lei; Yanfeng Ouyang
      Pages: 90 - 109
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): Chao Lei, Yanfeng Ouyang
      The one-commodity pickup and delivery problem (1-PDP) has a wide range of applications in the real world, e.g., for repositioning bikes in large cities to guarantee the sustainable operations of bike-sharing systems. It remains a challenge, however, to solve the problem for large-scale instances. This paper proposes a hybrid modeling framework for 1-PDP, where a continuum approximation (CA) approach is used to model internal pickup and delivery routing within each of multiple subregions, while matching of net surplus or deficit of the commodity out of these subregions is addressed in a discrete model with a reduced problem size. The interdependent local routing and system-level matching decisions are made simultaneously, and a Lagrangian relaxation based algorithm is developed to solve the hybrid model. A series of numerical experiments are conducted to show that the hybrid model is able to produce a good solution for large-scale instances in a short computation time.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.009
      Issue No: Vol. 109 (2018)
       
  • Designing parking facilities for autonomous vehicles
    • Authors: Mehdi Nourinejad; Sina Bahrami; Matthew J. Roorda
      Pages: 110 - 127
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): Mehdi Nourinejad, Sina Bahrami, Matthew J. Roorda
      Autonomous vehicles will have a major impact on parking facility designs in the future. Compared to regular car-parks that have only two rows of vehicles in each island, future car-parks (for autonomous vehicles) can have multiple rows of vehicles stacked behind each other. Although this multi-row layout reduces parking space, it can cause blockage if a certain vehicle is barricaded by other vehicles and cannot leave the facility. To release barricaded vehicles, the car-park operator has to relocate some of the vehicles to create a clear pathway for the blocked vehicle to exit. The extent of vehicle relocation depends on the layout design of the car-park. To find the optimal car-park layout with minimum relocations, we present a mixed-integer non-linear program that treats each island in the car-park as a queuing system. We solve the problem using Benders decomposition for an exact answer and we present a heuristic algorithm to find a reasonable upper-bound of the mathematical model. We show that autonomous vehicle car-parks can decrease the need for parking space by an average of 62% and a maximum of 87%. This revitalization of space that was previously used for parking can be socially beneficial if car-parks are converted into commercial and residential land-uses.
      Graphical abstract image

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.017
      Issue No: Vol. 109 (2018)
       
  • A matheuristic for transfer synchronization through integrated timetabling
           and vehicle scheduling
    • Authors: João Paiva Fonseca; Evelien van der Hurk; Roberto Roberti; Allan Larsen
      Pages: 128 - 149
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): João Paiva Fonseca, Evelien van der Hurk, Roberto Roberti, Allan Larsen
      Long transfer times often add unnecessary inconvenience to journeys in public transport systems. Synchronizing relevant arrival and departure times through small timetable modifications could reduce excess transfer times, but may also directly affect the operational costs, as the timetable defines the set of feasible vehicle schedules. Therefore better results in terms of passenger service, operational costs, or both, could be obtained by solving these problems simultaneously. This paper addresses the tactical level of the integrated timetabling and vehicle scheduling problem as a bi-objective mixed integer programming problem that minimizes transfer costs and operational costs. Given an initial non-cyclical timetable, and time-dependent service times and passenger demand, the weighted sum of transfer time cost and operational costs is minimized by allowing modifications to the timetable that respect a set of headway constraints. Timetable modifications consist of shifts in departure time and addition of dwell time at intermediate stops with transfer opportunities. A matheuristic is proposed that iteratively solves the mathematical formulation of the integrated timetabling and vehicle scheduling problem allowing timetable modifications for a subset of timetabled trips only, while solving the full vehicle scheduling problem. We compare different selection strategies for defining the sub-problems. Results for a realistic case study of the Greater Copenhagen area indicate that the matheuristic is able to find better feasible solutions faster than a commercial solver and that allowing the addition of dwell time creates a larger potential for reducing transfer costs.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.012
      Issue No: Vol. 109 (2018)
       
  • Solving for equilibrium in the basic bathtub model
    • Authors: Richard Arnott; Joshua Buli
      Pages: 150 - 175
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): Richard Arnott, Joshua Buli
      The basic (identical individuals) bathtub model has an unfamiliar mathematical structure, with a delay differential equation with an endogenous delay at its core. The early papers on the model circumvented this complication by making approximating assumptions, but without solution of the proper model it is unclear how accurate the results are. More recent work has either considered special cases that can be solved analytically using familiar methods, or has turned to generic computational solution. This paper develops a customized method for computational solution of equilibrium in the basic bathtub model with smooth preferences that exploits the mathematical structure of the problem. An inner loop solves numerically for the entry rate, conditional on the equilibrium utility level, by verifying a trip distance condition. An outer loop uses the computed start time from the inner loop to solve for the population that commutes over the rush hour, then lowers the equilibrium utility level to repeat the inner loop for a new level of utility. One result in that, even though tastes and the congestion technology are smooth, the entry rate and exit rate functions exhibit discontinuities at breakpoints. Another result is that, depending on the form of tastes and the congestion technology, the user cost curve as a function of population and may be backward bending.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2017.12.003
      Issue No: Vol. 109 (2018)
       
  • Exact loading and unloading strategies for the static multi-vehicle bike
           repositioning problem
    • Authors: W.Y. Szeto; C.S. Shui
      Pages: 176 - 211
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): W.Y. Szeto, C.S. Shui
      This study investigates a bike repositioning problem (BRP) that determines the routes of the repositioning vehicles and the loading and unloading quantities at each bike station to firstly minimize the positive deviation from the tolerance of total demand dissatisfaction (TDD) and then service time. The total demand dissatisfaction of a bike-sharing system in this study is defined as the sum of the difference between the bike deficiency and unloading quantity of each station in the system. Two service times are considered: the total service time and the maximum route duration of the fleet. To reduce the computation time to solve the loading and unloading sub-problem of the BRP, this study examines a novel set of loading and unloading strategies and further proves them to be optimal for a given route. This set of strategies is then embedded into an enhanced artificial bee colony algorithm to solve the BRP. The numerical results demonstrate that a larger fleet size may not lead to a lower total service time but can effectively lead to a lower maximum route duration at optimality. The results also illustrate the trade-offs between the two service times, between total demand dissatisfaction and total service time, and between the number of operating vehicles provided and the TDD. Moreover, the results demonstrate that the optimal values of the two service times can increase with the TDD and introducing an upper bound on one service time can reduce the optimal value of the other service time.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.01.007
      Issue No: Vol. 109 (2018)
       
  • Stability analysis methods and their applicability to car-following models
           in conventional and connected environments
    • Authors: Jie Sun; Zuduo Zheng; Jian Sun
      Pages: 212 - 237
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): Jie Sun, Zuduo Zheng, Jian Sun
      The paper comprehensively reviews major methods for analysing local and string stability of car-following (CF) models. Specifically, three types of CF models are considered: basic, time-delayed, and multi-anticipative/cooperative CF models. For each type, notable methods in the literature for analysing its local stability and string stability have been reviewed in detail, including the characteristic equation based method (e.g., root extracting, the root locus method, the Routh–Hurwitz criterion, the Nyquist criterion and the Hopf bifurcation method), Lyapunov criterion, the direct transfer function based method, and the Laplace transform based method. In addition, consistency and applicability of stability criteria obtained using some of these methods are objectively compared with the simulation result from a series of numerical experiments. Finally, issues, challenges, and research needs of CF models’ stability analysis in the era of connected and autonomous vehicles are discussed.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.01.013
      Issue No: Vol. 109 (2018)
       
  • New matrix-based methods for the analytic evaluation of the multivariate
           cumulative normal distribution function
    • Authors: Chandra R. Bhat
      Pages: 238 - 256
      Abstract: Publication date: March 2018
      Source:Transportation Research Part B: Methodological, Volume 109
      Author(s): Chandra R. Bhat
      In this paper, we develop a new matrix-based implementation of the Mendell and Elston (ME) analytic approximation to evaluate the multivariate normal cumulative distribution (MVNCD) function, using an LDLT decomposition method followed by a rank 1 update of the LDLT factorization. Our implementation is easy to code for individuals familiar with matrix-based coding. Further, our new matrix-based implementation for the ME algorithm allows us to efficiently write the analytic matrix-based gradients of the approximated MVNCD function with respect to the abscissae and correlation parameters, an issue that is important in econometric model estimation. In addition, we propose four new analytic methods for approximating the MVNCD function. The paper then evaluates the ability of the multiple approximations for individual MVNCD evaluations as well as multinomial probit model estimation. As expected, in our tests for evaluating individual MVNCD functions, we found that the traditional GHK approach degrades rapidly as the dimensionality of integration increases. Concomitant with this degradation in accuracy is a rapid increase in computational time. The analytic approximation methods are also much more stable across different numbers of dimensions of integration, and even the simplest of these methods is superior to the GHK-500 beyond seven dimensions of integration. Based on all the evaluation results in this paper, we recommend the new Two-Variate Bivariate Screening (TVBS) method proposed in this paper as the evaluation approach for MVNCD function evaluation.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.01.011
      Issue No: Vol. 109 (2018)
       
  • User equilibrium of a single-entry traffic corridor with continuous
           scheduling preference
    • Authors: Chuan-Yao Li; Hai-Jun Huang
      Pages: 21 - 38
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Chuan-Yao Li, Hai-Jun Huang
      The flow congestion model provides a realistic form of depicting congestion by considering the spatial dynamic characteristics of traffic flow. For reducing the complication of analysis, previous studies adopted the α − β − γ preference of travel time, arrival early and late penalties. This handling method destroys the continuity of user equilibrium (UE) inflow rate as pointed out by Li and Huang (2017). In this paper, we investigate the single-entry traffic corridor with continuous scheduling preference (CSP) and develop a customized method to find the computational solution of UE flow pattern. Analytical and numerical results show that the introduction of CSP lets inflow rate of early arrivals first increase then decrease. This extends the knowledge given by classical bottleneck model and flow congestion model with α − β − γ preference. Another finding is that, even though the introduction of CSP can smooth inflow rate at departure time of the punctual commuter and make the UE flow pattern more stable, a series of shock waves still exist.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.010
      Issue No: Vol. 108 (2018)
       
  • Automatic identification of near-stationary traffic states based on the
           PELT changepoint detection
    • Authors: Qinglong Yan; Zhe Sun; Qijian Gan; Wen-Long Jin
      Pages: 39 - 54
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Qinglong Yan, Zhe Sun, Qijian Gan, Wen-Long Jin
      The existence of stationary states during peak periods has been an underlying assumption of many studies on analysis, operations, control, and management of transportation networks. In Cassidy (1998), a method was proposed to manually identify near-stationary states by visually inspecting transformed curves of cumulative total vehicle counts and occupancies. Such near-stationary states are important for calibrating fundamental diagrams, identifying active bottlenecks and incidents, and quantifying capacity drop magnitudes. To the best of our knowledge, however, there lacks an automatic method that can be applied to efficiently identify near-stationary states from a large amount of data. In this study, we attempt to fill this gap. We start with definitions of steady, stationary, and equilibrium states and discuss their relations. Then we present a novel four-step method for automatically identifying near-stationary states from raw loop-detector data: first, the raw data are pre-processed to obtain healthy datasets, fill in missing values, and normalize averaged vehicle counts and occupancies to the same scale; second, daily time series are partitioned into multiple candidate intervals based on the pruned exact linear time (PELT) changepoint detection method; third, the characteristics of the candidate intervals are calculated; and finally, near-stationary states are selected based on modified Cassidy’s gap and duration criteria. We further close the loop by presenting an algorithm to automatically determine the penalty threshold in the second step and the gap threshold in fourth step to ensure the quantity as well as the quality of identified near-stationary states. In a case study, we apply the proposed method to identify near-stationary states from a large set of 30-s raw loop-detector data at a freeway mainline station. We verify the validity of identified near-stationary states both directly and indirectly. The results show that the identified near-stationary states are valid with high quality and the calibrated triangular fundamental diagram is well-fitted and physically meaningful. We finally conclude by discussing some future improvements and potential applications.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.007
      Issue No: Vol. 108 (2018)
       
  • A multivariate heterogeneous-dispersion count model for asymmetric
           interdependent freeway crash types
    • Authors: Ghasak I.M.A. Mothafer; Toshiyuki Yamamoto; Venkataraman N. Shankar
      Pages: 84 - 105
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Ghasak I.M.A. Mothafer, Toshiyuki Yamamoto, Venkataraman N. Shankar
      A multivariate count model is developed by introducing a simple and practical formula. The formulation begins with a modification of the standard ordered response model to adopt the count outcomes nature. This modification is accomplished by introducing a non-linear asymmetric interdependence structure among the error terms using the copula-based model. To avoid simulation maximum-likelihood for evaluating the multi-outcome density, we utilize the composite marginal likelihood (CML) approach. The proposed copula-based model with the CML approach allows for asymmetric (tail) dependency without a need for a simulation mechanism. Non-parametric graphical techniques with the empirical copula as well as conventional goodness-of-fit statistics are utilized to guide copula selection. In addition, unobserved heterogeneity across observations is also addressed through a heterogeneous dispersion parameter in the proposed model. The heterogeneous dispersion parameter model is a suitable alternative to random parameter count models in that captures heterogeneity in variance, while allowing for closed form while the latter needs numerical integration or simulation. We apply these techniques to study the interdependence structure among four types of traffic crashes using three years (2005–2007) of cross-sectional crash data record for 274 multilane freeway segments in the State of Washington, USA. These four categories of crash types are the rear end; sideswipe; fixed objects and other crash types. The empirical results show a significant presence of unobserved heterogeneous dependency across these types of crashes. The results indicate the important role of unobserved heterogeneity in variance and covariance structure estimation. An important outcome of this result is that it can affect inference on the relative impact of roadway geometrics on crash occurrence. For example, we find that horizontal curve related parameters on freeway segments substantially increase the joint likelihood of rear-end, sideswipe, fixed objects and other crash types, when compared to the characteristics of vertical curves.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.008
      Issue No: Vol. 108 (2018)
       
  • Demand imbalances and multi-period public transport supply
    • Authors: Daniel Hörcher; Daniel J. Graham
      Pages: 106 - 126
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Daniel Hörcher, Daniel J. Graham
      This paper investigates multi-period public transport supply, i.e. networks in which capacity cannot be differentiated between links and time periods facing independent but nonidentical demand conditions. This setting is particularly relevant in public transport, as earlier findings on multi-period road supply cannot be applied when the user cost function, defined as the sum of waiting time and crowding costs, is nonhomogeneous. The presence of temporal, spatial and directional demand imbalances is unavoidable in a public transport network. It is not obvious, however, how the magnitude of demand imbalances may affect its economic and financial performance. We show in a simple back-haul setting with elastic demand, controlling for total willingness to pay in the network, that asymmetries in market size reduce the attainable social surplus of a service, while variety in maximum willingness to pay leads to higher aggregate social surplus and lower subsidy under efficient pricing. The analysis of multi-period supply sheds light on the relationship between urban structure, daily activity patterns, and public transport performance.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.009
      Issue No: Vol. 108 (2018)
       
  • Pruning algorithm for the least expected travel time path on stochastic
           and time-dependent networks
    • Authors: A. Arun Prakash
      Pages: 127 - 147
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): A. Arun Prakash
      This study addresses the problem of determining the path with the least expected travel time on stochastic and time-dependent networks. The Bellman’s optimality principle is not applicable to this problem —because of its non-linear objective function— making it difficult to solve. In this light, we propose a pruning-based algorithm that progressively determines subpaths from the source and eliminates those that are non-optimal. The algorithm uses a novel bi-level, bounds-based pruning criterion to determine whether subpath can belong to the optimal path. We show that the pruning criterion is valid and that the algorithm terminates with an exact solution. Computational experiments demonstrate that the algorithm can successfully solve the problem even on large real-world networks and that its practical computational complexity is polynomial. Finally, we show that the pruning algorithm outperforms the existing non-dominance based procedure by a factor proportional to the network size on medium-sized networks and more so on large-sized networks. This work has the potential to aid in a wider application of stochastic time-dependent networks for modeling and analysis.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.015
      Issue No: Vol. 108 (2018)
       
  • Solving the block-to-train assignment problem using the heuristic approach
           based on the genetic algorithm and tabu search
    • Authors: Jie Xiao; Joern Pachl; Boliang Lin; Jiaxi Wang
      Pages: 148 - 171
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Jie Xiao, Joern Pachl, Boliang Lin, Jiaxi Wang
      After the railroad blocking plan is generated, the block-to-train assignment problem determines which train services to be offered, how many trains of each service to be dispatched (service frequency) and which blocks to be carried by which train services. An integer programming optimization model is defined to solve the block-to-train assignment problem. The model aims to maximize the total cost savings of the whole railroad network compared to the single-block train service plan, where each block is allocated to a direct train service. The objective function includes the service design cost savings, the train operation cost savings, the car-hour consumption savings in the accumulation process, the car-hour consumption savings in the attachment and detachment operations and the waiting car-hour consumption savings. Furthermore, the model is improved to a path-based formulation, which has far fewer decision variables and is easier to solve for real-world problems. A heuristic approach based on the genetic algorithm and tabu search is developed to solve the path-based formulation. The model and approach are tested first in a small network to compare with the optimal solution obtained through the enumeration method and the solution obtained from commercial optimization software. Then the model and approach are applied to a real larger railroad sub-network in China.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.014
      Issue No: Vol. 108 (2018)
       
  • An optimization model to measure utility of joint and solo activities
    • Authors: Mahdieh Allahviranloo; Kay Axhausen
      Pages: 172 - 187
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Mahdieh Allahviranloo, Kay Axhausen
      The choice of ‘dining out with friends’ or ‘wrapping up unfinished tasks at work’ depends on the utility/satisfaction gained from performing each activity while being constrained by time and physical resources. In fact, such parameters as ‘type’, ‘time of day’, ‘duration’, ‘location’, ‘companionship’, and etc. are defining factors in quantifying the utility of activities - a challenging problem which has been the focus of research for many years. This paper proposes a methodology to estimate the parameters of utility distributions for joint and solo activities, along with the penalty values associated with the deviation of activity start time and duration from their modal values. The study utilizes travel survey data collected in Frauenfeld, Switzerland, over the period of six weeks in 2003. The proposed model is a bi-level optimization model, where the upper level maximizes the accuracy of the activity scheduling on the aggregate level and is measured using the outputs of lower level optimization models. Each lower level model is a variation of pickup and delivery problem and schedules activities for each individual in the population using the parameters of utility distribution and penalty values generated by the Genetic Algorithm. The results indicate that travelers are trying to be more consistent with their arrival time to work, school and pickup/drop off activities: the associated penalty values for deviation from the modal value for arrival time to work and school activities are high. Additionally, significant differences in the parameters of the estimated utility distribution for joint and solo activities are observed, reflecting the fact that utility gained from joint and solo activities are different and needs more in-depth investigation. The proposed methodology has the potential to be applied to any multiday travel survey data, which due to advances made in handheld smart devices and mobile applications are becoming more convenient to collect.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.004
      Issue No: Vol. 108 (2018)
       
  • Mixed-integer programming model and branch-and-price-and-cut algorithm for
           urban bus network design and timetabling
    • Authors: James C. Chu
      Pages: 188 - 216
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): James C. Chu
      This study solves the simultaneous planning problem of network design and timetabling for urban bus systems. An innovative mixed-integer programming (MIP) model is formulated and a parallel branch-and-price-and-cut (BPC) algorithm is proposed to solve the problem. The key idea of the model formulation and the solution algorithm is to represent a bus timetable with a route and a dispatch pattern. An aggregation and greedy algorithm is developed to efficiently solve the pricing subproblem. The cuts of disaggregate coupling inequalities are dynamically added to strengthen the lower bound. A computational study is conducted to evaluate the performance of the proposed methodology. The comparison with alternative solution approaches indicates that the parallel BPC algorithm is superior to solving the MIP formulations with the off-the-shelf MIP solver. Different values of model parameters are also tested, and various statistics of operators and passengers are reported for the cases.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.013
      Issue No: Vol. 108 (2018)
       
  • Real-time multi-depot vehicle type rescheduling problem
    • Authors: Pablo C. Guedes; Denis Borenstein
      Pages: 217 - 234
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Pablo C. Guedes, Denis Borenstein
      The multiple-depot vehicle type rescheduling problem (MDVTRSP) is a dynamic extension of the classic multiple-depot vehicle scheduling problem (MDVSP), where a heterogeneous fleet is considered. The MDVTRSP consists of finding a new schedule given that a severe disruption occurred in previously scheduled trips very quickly, simultaneously minimizing the transportation costs and the deviations from the original plan. Although several mathematical formulations and solution methods have been developed for the robust MDVTRSP, the real time MDVTRSP is still unexplored. In this paper, we introduce a formulation of the problem and develop a heuristic solution method, employing time-space network, truncated column generation, and preprocessing procedures. The solution method has been implemented in several algorithm variants, combining different developed preprocessing methods. Computational experiments on randomly generated instances were performed to evaluate the performance of the developed algorithms. The best solutions concerning efficiency and efficacy were obtained by the variants considering state space reductions to accelerate the convergence process of the column generation. Solutions were obtained very quickly (in less than 150 seconds for large instances, considering up to 2500 trips, eight depots, and one breakdown. The developed heuristics also presented a good behavior for several simultaneous disruptions, solving the problem with a little increase (less than 8.5%, on average) in the required CPU time. A case study using data from a real-life small instance in Brazil also demonstrated the efficiency and efficacy of the approach when compared with manual planning strategies.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.012
      Issue No: Vol. 108 (2018)
       
  • Dynamic programming algorithms for selection of waste disposal ports in
           cruise shipping
    • Authors: Shuaian Wang; Lu Zhen; Dan Zhuge
      Pages: 235 - 248
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Shuaian Wang, Lu Zhen, Dan Zhuge
      The cruise industry has maintained a steady growth in the past 20 years. Due to the large number of cruise passengers and regulations on sea environment protection, determining at which ports to dispose of the waste generated onboard a cruise ship is a key decision to reduce the cost for a cruise company. We address four versions of the problem: the cruise itinerary is either static or dynamic and the amount of waste generated on each voyage leg is either deterministic or stochastic. We propose a polynomial-time solution algorithm for the static deterministic model, and the idea of the algorithm can also be used to solve the static stochastic model and the dynamic deterministic model. Second, we identify the structure of the optimal policy to the dynamic stochastic problem, based on which an efficient dynamic programming algorithm is developed. Extensive numerical experiments derived from problems of real-case scales demonstrate the efficiency of the proposed algorithms.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.016
      Issue No: Vol. 108 (2018)
       
  • Understanding many-to-many matching relationship and its correlation with
           joint response
    • Authors: Dapeng Zhang; Xiaokun (Cara) Wang
      Pages: 249 - 260
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Dapeng Zhang, Xiaokun (Cara) Wang
      Many-to-many matching relationship in a two-sided market has been widely observed in today's transportation activities. Observation of such matching relationship raises some interesting questions: what factors drive the matching of two agents' Is the formation of matching relationship related with joint behavior which may lead to different understandings of planning and operation' To answer these questions, econometric models may be the best methodology. However, to the authors’ best knowledge, there lacks a well-established econometric model to explain the observed data that contains matching relationship in a two-sided transportation market. Therefore, this paper proposes an innovative ordinal joint response model to bridge the gap. The proposed model consists of two regression equations: the first uses a latent dependent variable to disentangle the many-to-many matching relationship; the second specifies an ordered probit equation to investigate the ordinal outcome of joint behavior. Error terms of the two equations are assumed correlated to capture the correlation of the matching process and joint behavior. An example of airline-airport matching is used to demonstrate the proposed model.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.011
      Issue No: Vol. 108 (2018)
       
  • Congestion tolling - dollars versus tokens: A comparative
           analysis
    • Authors: André de Palma; Stef Proost; Ravi Seshadri; Moshe Ben-Akiva
      Pages: 261 - 280
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): André de Palma, Stef Proost, Ravi Seshadri, Moshe Ben-Akiva
      The case for some form of congestion tolling has long been made given the extent of traffic congestion in most urban transportation networks. However, there is little consensus on whether this tolling should be in the form of dollars (traditional congestion pricing schemes or price regulation) or in the form of tokens (credit based mobility schemes or quantity regulation). Although the comparison of price and quantity regulation has received significant attention in the economics community, the literature is relatively sparse in the context of transportation systems. The two systems differ not only in terms of transaction costs but also in their efficiency in dealing with demand and capacity shocks, frequent in road transport systems. This difference has been explored by economists in market contexts but the possible parallel in transport systems has largely been overlooked. This paper develops a methodology to compare the performance of price and quantity instruments under uncertainty using a simple transportation network consisting of parallel highway routes and a public transport alternative. Tolls (in dollars or tokens) are differentiated across roads and the permits or tokens can be traded across roads at fixed rates. The demand for each route is determined by a logit mixture model and the supply consists of static congestion. The comparison is based on the optimum social welfare which is computed for each instrument by solving a non-convex optimization problem involving stochastic user equilibrium constraints. Equity considerations are also examined. Numerical experiments across a wide range of demand/supply inputs lead us to the following insights. First, when the tolls in dollars and tokens can be fully adapted to demand and supply shocks (i.e. are day-to-day adaptive), both instruments are equivalent and attain the same optimum social welfare. Second, when the tolling system is not day-to-day adaptive and the supply of tokens is fixed, the quantity instrument performs better than the price instrument typically when the marginal external congestion function has a steeper slope than the demand function. Third, when the tolling system is non-adaptive, but the supply of tokens is day-to-day adaptive, the quantity instrument always outperforms the price instrument in terms of social welfare. Fourth, when the toll revenues and permits are distributed uniformly, this has a positive equity effect but the quantity instrument is more equitable than the price instrument. In view of these results, we argue the case for quantity control in the presence of uncertainty and strongly convex congestion costs.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2017.12.005
      Issue No: Vol. 108 (2018)
       
  • Co-opetition in enhancing global port network resiliency: A multi-leader,
           common-follower game theoretic approach
    • Authors: Ali Asadabadi; Elise Miller-Hooks
      Pages: 281 - 298
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Ali Asadabadi, Elise Miller-Hooks
      Ports are key elements of global supply chains, providing connection between land- and maritime-based transportation modes. They operate in cooperative, but competitive, co-opetitive, environments wherein individual port throughput is linked through an underlying transshipment network. Short-term port performance and long-term market share can be significantly impacted by a disaster event; thus, ports plan to invest in capacity expansion and protective measures to increase their reliability or resiliency in times of disruption. To account for the co-opetition among ports, a bi-level multiplayer game theoretic approach is used, wherein each individual port takes protective investment decisions while anticipating the response of the common market-clearing shipping assignment problem in the impacted network. This lower-level assignment is modeled as a cost minimization problem, which allows for consideration of gains and losses from other ports decisions through changes in port and service capacities and port cargo handling times. Linear properties of the lower-level formulation permit reformulation of the individual port bi-level optimization problems as single-level problems by replacing the common lower-level by its equivalent Karush Kuhn Tucker (KKT) conditions. Simultaneous consideration of individual port optimization problems creates a multi-leader, common-follower problem, i.e. an unrestricted game, that is modeled as an Equilibrium Problem with Equilibrium Constraints (EPEC). Equilibria solutions are sought by use of a diagonalization technique. Solutions of unrestricted, semi-restricted and restricted games are analyzed and compared for a hypothetical application from the literature involving ports in East Asia and Europe. The proposed co-opetitive approach was found to lead to increased served total demand, significantly increased market share for many ports and improved services for shippers.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.004
      Issue No: Vol. 108 (2018)
       
  • A survey of dial-a-ride problems: Literature review and recent
           developments
    • Authors: Sin C. Ho; W.Y. Szeto; Yong-Hong Kuo; Janny M.Y. Leung; Matthew Petering; Terence W.H. Tou
      Abstract: Publication date: Available online 15 February 2018
      Source:Transportation Research Part B: Methodological
      Author(s): Sin C. Ho, W.Y. Szeto, Yong-Hong Kuo, Janny M.Y. Leung, Matthew Petering, Terence W.H. Tou
      There has been a resurgence of interest in demand-responsive shared-ride systems, motivated by concerns for the environment and also new developments in technologies which enable new modes of operations. This paper surveys the research developments on the Dial-A-Ride Problem (DARP) since 2007. We provide a classification of the problem variants and the solution methodologies, and references to benchmark instances. We also present some application areas for the DARP, discuss some future trends and challenges, and indicate some possible directions for future research.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.02.001
       
  • Continuous-time general link transmission model with simplified fanning,
           Part II: Event-based algorithm for networks
    • Authors: Mark P.H. Raadsen; Michiel C.J. Bliemer
      Abstract: Publication date: Available online 6 February 2018
      Source:Transportation Research Part B: Methodological
      Author(s): Mark P.H. Raadsen, Michiel C.J. Bliemer
      In this paper a novel solution algorithm is proposed for solving general first order dynamic network loading (DNL) problems in general transport networks. This solution algorithm supports any smooth non-linear two regime concave fundamental diagram and adopts a simplified fanning scheme. It is termed eGLTM (event-based General Link Transmission Model) and is based on a continuous-time formulation of the kinematic wave model that adapts shockwave theory to simplify expansion fans. As the name suggests eGLTM is a generalisation of eLTM, which is a special case that solves the simplified first order model assuming a triangular fundamental diagram. We analyse the impact of modelling delay in the hypocritical branch of the fundamental diagram to assess the differences between the two models. In addition, we propose an additional stream of mixture events to propagate multi-commodity flow in event based macroscopic models, which makes both eLTM and eGLTM suitable for dynamic traffic assignment (DTA) applications. The proposed solution scheme can yield exact solutions as well as approximate solutions at a significantly lesser cost. The efficiency of the model is demonstrated in a number of case studies. Furthermore, different settings for our simplified fanning scheme are investigated as well as an extensive analysis on the effect of including route choice on the algorithms computational cost. Finally, a large scale case study is conducted to investigate the suitability of our newly proposed model in a practical context and assess its efficiency. In this study comparisons between eLTM and eGLTM are included to demonstrate the impact of aforementioned generalisation as well as the multi-commodity extension that is proposed.

      PubDate: 2018-02-26T18:51:31Z
      DOI: 10.1016/j.trb.2018.01.003
       
  • Continuous-time general link transmission model with simplified fanning,
           part I: Theory and link model formulation
    • Authors: Michiel C.J. Bliemer; Mark P.H. Raadsen
      Abstract: Publication date: Available online 10 January 2018
      Source:Transportation Research Part B: Methodological
      Author(s): Michiel C.J. Bliemer, Mark P.H. Raadsen
      The kinematic wave theory is widely used to simulate traffic flows on road segments. Link transmission models are methods to find a solution to the kinematic wave model, however, their computational efficiency heavily relies on the shape of the fundamental diagram that is used as input. Despite the limitations and drawbacks of triangular and piecewise linear fundamental diagrams, they remain popular because they result in highly efficient algorithms. Using smooth nonlinear branches is often preferred in terms of realism and other desirable properties, but this comes at a significantly higher computational cost and requires time discretization to find an approximate solution. In this paper we consider a nonlinear fundamental diagram as input and propose on-the-fly multi-step linearization techniques to simplify expansion fans. This leads to two simplified link transmission models that can be solved exactly in continuous time under the assumption of piecewise stationary travel demand. One of the models simplifies to shockwave theory in case of a single step. We show that embedding shockwave theory in the link transmission model allows for finding an exact solution in continuous time and we discuss the potential for the design of efficient event-based algorithms for general networks.

      PubDate: 2018-02-05T06:22:00Z
      DOI: 10.1016/j.trb.2018.01.001
       
  • Capacity-drop at extended bottlenecks: Merge, diverge, and weave
    • Authors: Danjue Chen; Soyoung Ahn
      Pages: 1 - 20
      Abstract: Publication date: February 2018
      Source:Transportation Research Part B: Methodological, Volume 108
      Author(s): Danjue Chen, Soyoung Ahn
      This paper investigates the mechanisms of how spatially distributed lane changes (LCs) interact and contribute to “capacity-drop” at three types of extended bottlenecks: merge, diverge, and weave. A hybrid approach is used to study the problem: analytical approach to capture the behavior of merging and diverging LCs and numerical simulations to quantify capacity-drop considering various geometric configurations of extended bottlenecks. This study focuses on the impact of LC vehicles’ bounded acceleration on “void” (wasted space) creation in traffic streams when they insert/desert at a lower speed, and interactions among multiple voids. We found that (1) LCs closer to the downstream end of bottlenecks are more likely to create persisting voids and contribute to capacity-drop. (2) For weave bottlenecks, capacity-drop is governed by two counteracting effects of LCs: persisting voids and utilization of vacancies created by diverging vehicles; (3) the more balanced the merging and diverging flows, the lower the capacity-drop; and (4) capacity-drop is minimum if merging LCs occur downstream of diverging LCs, and maximum in the opposite alignment.

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

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

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

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

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

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

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

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

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

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

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

      PubDate: 2017-12-27T07:47:07Z
      DOI: 10.1016/j.trb.2017.10.007
      Issue No: Vol. 107 (2017)
       
 
 
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