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  Subjects -> TRANSPORTATION (Total: 165 journals)
    - AIR TRANSPORT (7 journals)
    - AUTOMOBILES (20 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (5 journals)
    - SHIPS AND SHIPPING (29 journals)
    - TRANSPORTATION (99 journals)

TRANSPORTATION (99 journals)

Accident Analysis & Prevention     Partially Free   (Followers: 58)
AI & Society     Hybrid Journal   (Followers: 4)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 1)
Archives of Transport     Open Access   (Followers: 17)
Bitácora Urbano-Territorial     Open Access   (Followers: 1)
Botswana Journal of Technology     Full-text available via subscription  
Case Studies on Transport Policy     Hybrid Journal   (Followers: 5)
Cities in the 21st Century     Open Access   (Followers: 14)
Economics of Transportation     Partially Free   (Followers: 12)
Emission Control Science and Technology     Hybrid Journal   (Followers: 1)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 7)
European Transport Research Review     Open Access   (Followers: 23)
Geosystem Engineering     Hybrid Journal   (Followers: 2)
IATSS Research     Open Access  
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 9)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 8)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 7)
International Innovation - Transport     Open Access   (Followers: 9)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 6)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 7)
International Journal of Critical Infrastructure Protection     Hybrid Journal   (Followers: 5)
International Journal of e-Navigation and Maritime Economy     Open Access  
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 7)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 8)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 9)
International Journal of Micro-Nano Scale Transport     Full-text available via subscription   (Followers: 1)
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: 9)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 10)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 20)
International Journal of Transportation Science and Technology     Full-text available via subscription   (Followers: 11)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 5)
International Journal of Vehicular Technology     Open Access   (Followers: 5)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 12)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 5)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 116)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 8)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 1)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 3)
Journal of Transport & Health     Hybrid Journal   (Followers: 4)
Journal of Transport and Land Use     Open Access   (Followers: 21)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 9)
Journal of Transport Geography     Hybrid Journal   (Followers: 18)
Journal of Transport History     Full-text available via subscription   (Followers: 13)
Journal of Transport Literature     Open Access   (Followers: 6)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 8)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 12)
Journal of Transportation Technologies     Open Access   (Followers: 15)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 8)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics & Sustainable Transport     Open Access  
Logistique & Management     Full-text available via subscription  
Mobility in History     Full-text available via subscription   (Followers: 2)
Modern Transportation     Open Access   (Followers: 8)
Nonlinear Dynamics     Hybrid Journal   (Followers: 5)
Open Journal of Safety Science and Technology     Open Access   (Followers: 7)
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 9)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 10)
PS: Political Science & Politics     Full-text available via subscription   (Followers: 23)
Public Transport     Hybrid Journal   (Followers: 17)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 3)
Revista Transporte y Territorio     Open Access   (Followers: 1)
Romanian Journal of Transport Infrastructure     Open Access  
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 12)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 1)
Streetnotes     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 2)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 5)
Transport     Hybrid Journal   (Followers: 13)
Transport and Telecommunication Journal     Open Access   (Followers: 4)
Transport in Porous Media     Hybrid Journal   (Followers: 1)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 9)
Transportation     Hybrid Journal   (Followers: 26)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 7)
Transportation Journal     Full-text available via subscription   (Followers: 12)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 2)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 29)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 28)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 19)
Transportation Research Procedia     Open Access   (Followers: 2)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 34)
Transportation Science     Full-text available via subscription   (Followers: 19)
TRANSPORTES     Open Access   (Followers: 4)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 3)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 2)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 4)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 1)
Urban, Planning and Transport Research     Open Access   (Followers: 25)
Vehicular Communications     Full-text available via subscription   (Followers: 2)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 5)
Транспортні системи та технології перевезень     Open Access  
Journal Cover Transportation Research Part B: Methodological
  [SJR: 3.306]   [H-I: 70]   [28 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0191-2615
   Published by Elsevier Homepage  [2801 journals]
  • Disruption risk management in railroad networks: An optimization-based
           methodology and a case study
    • Abstract: Publication date: March 2016
      Source:Transportation Research Part B: Methodological, Volume 85
      Author(s): Nader Azad, Elkafi Hassini, Manish Verma
      We propose an optimization-based methodology for recovery from random disruptions in service legs and train services in a railroad network. A network optimization model is solved for each service leg to evaluate a number of what-if scenarios. The solutions of these optimization problems are then used in a predictive model to identify the critical disruption factors and accordingly design a suitable mitigation strategy. A mitigation strategy, such as adding flexible or redundant capacity in the network, is an action that is deliberately taken by management in order to hedge against the cost and impact of disruption if it occurs. It is important that managers consider the trade-offs between the cost of mitigation strategy and the expected cost of disruption. The proposed methodology is applied to a case study built using the realistic infrastructure of a railroad network in the mid-west United States. The resulting analysis underscores the importance of accepting a slight increase in pre-disruption transportation costs, which in turn will enhance network resiliency by building dis-similar paths for train services, and by installing alternative links around critical service legs.


      PubDate: 2016-01-24T08:41:50Z
       
  • Multi-period yard template planning in container terminals
    • Abstract: Publication date: Available online 23 January 2016
      Source:Transportation Research Part B: Methodological
      Author(s): Lu Zhen, Zhou Xu, Kai Wang, Yi Ding
      This paper is about yard management in container ports. As a tactical level decision-making tool in a port, a yard template determines the assignment of spaces (subblocks) in a yard for arriving vessels, which visit the port periodically. The objective of yard template planning is to minimize the transportation cost of moving containers around the yard. To handle yard template planning, a mixed integer programming model is proposed that also takes into account traffic congestion in the yard. A further complication is that the cycle time of the vessels' periodicities is not uniform and varies among them, perhaps being one week, ten days, or two weeks, etc. However, this multiple cycle time of the periodicities of vessel arrival patterns, which complicates the yard template decision, is also considered in the model. Moreover, a local branching based solution method and a Particle Swarm Optimization based solution method are developed for solving the model. Numerical experiments are also conducted to validate the effectiveness of the proposed model, which can save around 24% of the transportation costs of yard trucks when compared with the commonly used First-Come-First-Served decision rule. Moreover, the proposed solution methods can not only solve the proposed model within a reasonable time, but also obtain near-optimal results with about 0.1–2% relative gap.


      PubDate: 2016-01-24T08:41:50Z
       
  • Optimal choice of capacity, toll and government guarantee for
           build-operate-transfer roads under asymmetric cost information
    • Abstract: Publication date: March 2016
      Source:Transportation Research Part B: Methodological, Volume 85
      Author(s): Shasha Shi, Yafeng Yin, Xiaolei Guo
      The private provision of public roads via the build-operate-transfer (BOT) mode has been increasingly used around the world. By viewing a BOT contract as a combination of road capacity, toll and government guarantee, this paper investigates optimal concession contract design under both symmetric and asymmetric information about the marginal maintenance cost of private investors. Under asymmetric information, the government guarantee serves as an instrument to induce a private investor to reveal his true cost information. Compared with the situation under symmetric information, the government will suffer a loss of social welfare; the private investor will charge a higher toll that increases in his reported marginal maintenance cost, and specify a lower capacity that decreases with the reported cost. The results also show that the private investor obtains extra information rent beyond the reservation level of return and the rent decreases with his reported cost. However, the resulting volume-capacity ratios of the BOT road under both information structures are the same.


      PubDate: 2016-01-24T08:41:50Z
       
  • Pricing and competition in a shipping market with waste shipments and
           empty container repositioning
    • Abstract: Publication date: March 2016
      Source:Transportation Research Part B: Methodological, Volume 85
      Author(s): Rongying Chen, Jing-Xin Dong, Chung-Yee Lee
      In this paper, we study a shipping market with carriers providing services between two locations. Shipments are classified into two categories: goods and waste. Trade imbalance allows low-valued waste to be shipped at bargain rates. If imbalance persists, empty containers must be repositioned from a surplus location to a shortage location. Carriers decide prices, which will affect the demand. We build a monopoly and a duopoly model to find the optimal pricing strategy for carriers. We also analyze how the profit of a carrier is affected by price sensitivity, cost structure and competition intensity.


      PubDate: 2016-01-24T08:41:50Z
       
  • A probabilistic model for vehicle scheduling based on stochastic trip
           times
    • Abstract: Publication date: March 2016
      Source:Transportation Research Part B: Methodological, Volume 85
      Author(s): Yindong Shen, Jia Xu, Jingpeng Li
      Vehicle scheduling plays a profound role in public transit planning. Traditional approaches for the Vehicle Scheduling Problem (VSP) are based on a set of predetermined trips in a given timetable. Each trip contains a departure point/time and an arrival point/time whilst the trip time (i.e. the time duration of a trip) is fixed. Based on fixed durations, the resulting schedule is hard to comply with in practice due to the variability of traffic and driving conditions. To enhance the robustness of the schedule to be compiled, the VSP based on stochastic trip times instead of fixed ones is studied. The trip times follow the probability distributions obtained from the data captured by Automatic Vehicle Locating (AVL) systems. A network flow model featuring the stochastic trips is devised to better represent this problem, meanwhile the compatibility of any pair of trips is redefined based on trip time distributions instead of fixed values as traditionally done. A novel probabilistic model of the VSP is proposed with the objectives of minimizing the total cost and maximizing the on-time performance. Experiments show that the probabilistic model may lead to more robust schedules without increasing fleet size.


      PubDate: 2016-01-20T08:40:27Z
       
  • Two-phase stochastic program for transit network design under demand
           uncertainty
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): Kun An, Hong K. Lo
      This paper develops a reliability-based formulation for rapid transit network design under demand uncertainty. We use the notion of service reliability to confine the stochastic demand into a bounded uncertainty set that the rapid transit network is designed to cover. To evaluate the outcome of the service reliability chosen, flexible services are introduced to carry the demand overflow that exceeds the capacity of the rapid transit network such designed. A two-phase stochastic program is formulated, in which the transit line alignments and frequencies are determined in phase 1 for a specified level of service reliability; whereas in phase 2, flexible services are determined depending on the demand realization to capture the cost of demand overflow. Then the service reliability is optimized to minimize the combined rapid transit network cost obtained in phase 1, and the flexible services cost and passenger cost obtained in phase 2. The transit line alignments and passenger flows are studied under the principles of system optimal (SO) and user equilibrium (UE). We then develop a two-phase solution algorithm that combines the gradient method and neighborhood search and apply it to a series of networks. The results demonstrate the advantages of utilizing the two-phase formulation to determine the service reliability as compared with the traditional robust formulation that pre-specifies a robustness level.


      PubDate: 2016-01-15T06:42:07Z
       
  • Forecasting light-duty vehicle demand using alternative-specific constants
           for endogeneity correction versus calibration
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): C. Grace Haaf, W. Ross Morrow, Inês M.L. Azevedo, Elea McDonnell Feit, Jeremy J. Michalek
      We investigate parameter recovery and forecast accuracy implications of incorporating alternative-specific constants (ASCs) in the utility functions of vehicle choice models. We compare two methods of incorporating ASCs: (1) a maximum likelihood estimator that computes ASCs post-hoc as calibration constants (MLE-C) and (2) a generalized method of moments estimator that uses instrumental variables (GMM-IV) to correct for price endogeneity. In a synthetic study we observe significant coefficient bias with MLE-C when the price-ASC correlation (endogeneity) is large. GMM-IV successfully mitigates this bias given valid instruments but exacerbates the bias given invalid instruments. Despite greater coefficient bias, MLE-C yields better forecasts than GMM-IV with valid instruments in most of the cases examined, including most cases where the price-ASC correlation present in the estimation data is absent in the prediction data. In a market study of U.S. midsize sedan sales from 2002 – 2006 the GMM-IV model predicts the 1-year-forward market better, but the MLE-C model predicts the 5-year-forward market better. Including an ASC in predictions by any of the methods proposed improves share forecasts, and assuming that the ASC of each new vehicle matches that of its closest competitor vehicle yields the best long term forecasts. We find evidence that the instruments most frequently used in the automotive demand literature may be invalid.


      PubDate: 2016-01-15T06:42:07Z
       
  • Optimization of incentive polices for plug-in electric vehicles
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): Yu (Marco) Nie, Mehrnaz Ghamami, Ali Zockaie, Feng Xiao
      High purchase prices and the lack of supporting infrastructure are major hurdles to the adoption of plug-in electric vehicles (PEVs). It is widely recognized that the government could help break these barriers through incentive policies, such as offering rebates to PEV buyers or funding charging stations. The objective of this paper is to propose a modeling framework that can optimize the design of such incentive policies. The proposed model characterizes the impact of the incentives on the dynamic evolution of PEV market penetration over a discrete set of time intervals, by integrating a simplified consumer vehicle choice model and a macroscopic travel and charging model. The optimization problem is formulated as a nonlinear and non-convex mathematical program and solved by a specialized steepest descent direction algorithm. We show that, under mild regularity conditions, the KKT conditions of the proposed model are necessary for local optimum. Results of numerical experiments indicate that the proposed algorithm is able to obtain satisfactory local optimal policies quickly. These optimal policies consistently outperform the alternative policies that mimic the state-of-the-practice by a large margin, in terms of both the total savings in social costs and the market share of PEVs. Importantly, the optimal policy always sets the investment priority on building charging stations. In contrast, providing purchase rebates, which is widely used in current practice, is found to be less effective.


      PubDate: 2016-01-15T06:42:07Z
       
  • Continuum modelling of spatial and dynamic equilibrium in a travel
           corridor with heterogeneous commuters—A partial differential
           complementarity system approach
    • Abstract: Publication date: March 2016
      Source:Transportation Research Part B: Methodological, Volume 85
      Author(s): David Z.W. Wang, Bo Du
      This paper studies on modelling and solving spatial and dynamic equilibrium travel pattern in a travel corridor. Consider a travel corridor connecting continuously distributed commuters to the city centre. The traffic is subject to flow congestion and the commuter heterogeneity is captured. The traffic flow dynamics is described by flow continuity equation and the equilibrium travel pattern is assumed to follow trip-timing condition. The continuous spatial and dynamic equilibrium travel pattern is formulated into a partial differential complementarity system, which is then solved through Godunov scheme. The proof of solution existence is provided, and a set of numerical experiments are demonstrated.


      PubDate: 2016-01-15T06:42:07Z
       
  • The impact of depot location, fleet composition and routing on emissions
           in city logistics
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): Çağrı Koç, Tolga Bektaş, Ola Jabali, Gilbert Laporte
      This paper investigates the combined impact of depot location, fleet composition and routing decisions on vehicle emissions in city logistics. We consider a city in which goods need to be delivered from a depot to customers located in nested zones characterized by different speed limits. The objective is to minimize the total depot, vehicle and routing cost, where the latter can be defined with respect to the cost of fuel consumption and CO2 emissions. A new powerful adaptive large neighborhood search metaheuristic is developed and successfully applied to a large pool of new benchmark instances. Extensive analyses are performed to empirically assess the effect of various problem parameters, such as depot cost and location, customer distribution and heterogeneous vehicles on key performance indicators, including fuel consumption, emissions and operational costs. Several managerial insights are presented.


      PubDate: 2016-01-11T12:53:53Z
       
  • Advanced traveller information systems under recurrent traffic conditions:
           Network equilibrium and stability
    • Abstract: Publication date: Available online 7 January 2016
      Source:Transportation Research Part B: Methodological
      Author(s): Gennaro N. Bifulco, Giulio E. Cantarella, Fulvio Simonelli, Pietro Velonà
      In this paper the stability of traffic equilibrium is analysed by using a framework where advanced traveller information systems (ATIS) are explicitly modelled. The role played by information in traffic networks is discussed, with particular reference to the day-to-day dynamics of the traffic network and to system stability at equilibrium. The perspective adopted is that of transportation planning under recurrent network conditions. The network is considered to be in equilibrium, viewed as a fixed-point state of a day-to-day deterministic process, here modelled as a time-discrete non-linear Markovian dynamic system. In discussing the effects generated by the introduction of ATIS, the paper examines: changes in the fixed point(s) with respect to the absence of ATIS, how the theoretical conditions for fixed-point existence and uniqueness are affected, and the impact on the stability properties and the stability region at equilibrium. Most of the analyses are carried out with explicit theoretical considerations. Moreover, a toy network is also employed to explore numerically the effects of removing some assumptions concerning the accuracy of ATIS.


      PubDate: 2016-01-11T12:53:53Z
       
  • Reducing the passenger travel time in practice by the automated
           construction of a robust railway timetable
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): P. Sels, T. Dewilde, D. Cattrysse, P. Vansteenwegen
      Automatically generating timetables has been an active research area for some time, but the application of this research in practice has been limited. We believe this is due to two reasons. Firstly, some of the models in the literature impose artificial upper bounds on time supplements. This causes a high risk of generating infeasibilities. Secondly, some models that leave out these upper bounds often generate solutions that contain some very large time supplements because these supplements are not penalised in the objective function. The reason is that these objective functions often do not completely correspond to the true goal of a timetable. We solve both problems by minimising our objective function: total passenger travel time, expected in practice. Since this function evaluates and indirectly steers all time related decision variables in the system, we do not need to further restrict the ranges of any of these variables. As a result, our model does not suffer from infeasibilities generated by such artificial upper bounds for supplements. Furthermore, some measures are taken to significantly speed up the solver times of our model. These combined features result in our model being solved more quickly than previous models. As a result, our method can be used for timetabling in practice. We demonstrate our claims by optimising, in about two hours only, the timetable of all 196 hourly passenger trains in Belgium. Assuming primary delay-distributions with an average of 2% on the minima of each activity, the optimised timetable reduces expected passenger time in practice, as evaluated on the macroscopic level, by 3.8% during peak hours. This paper demonstrates that we added two important missing steps to make cyclic timetabling for passengers really useable in practice: (i) the addition of the objective function of expected passenger time in practice and (ii) the reduction of computation time by addition of well chosen additional constraints.


      PubDate: 2016-01-11T12:53:53Z
       
  • Optimal queue placement in dynamic system optimum solutions for single
           origin-destination traffic networks
    • Abstract: Publication date: Available online 7 January 2016
      Source:Transportation Research Part B: Methodological
      Author(s): D. Ngoduy, N.H. Hoang, H.L. Vu, D. Watling
      The Dynamic System Optimum (DSO) traffic assignment problem aims to determine a time-dependent routing pattern of travellers in a network such that the given time-dependent origin-destination demands are satisfied and the total travel time is at a minimum, assuming some model for dynamic network loading. The network kinematic wave model is now widely accepted as such a model, given its realism in reproducing phenomena such as transient queues and spillback to upstream links. An attractive solution strategy for DSO based on such a model is to reformulate as a set of side constraints apply a standard solver, and to this end two methods have been previously proposed, one based on the discretisation scheme known as the Cell Transmission Model (CTM), and the other based on the Link Transmission Model (LTM) derived from variational theory. In the present paper we aim to combine the advantages of CTM (in tracking time-dependent congestion formation within a link) with those of LTM (avoiding cell discretisation, providing a more computationally attractive with much fewer constraints). The motivation for our work is the previously-reported possibility for DSO to have multiple solutions, which differ in where queues are formed and dissipated in the network. Our aim is to find DSO solutions that optimally distribute the congestion over links inside the network which essentially eliminate avoidable queue spillbacks. In order to do so, we require more information than the LTM can offer, but wish to avoid the computational burden of CTM for DSO. We thus adopt an extension of the LTM called the Two-regime Transmission Model (TTM), which is consistent with LTM at link entries and exits but which is additionally able to accurately track the spatial and temporal formation of the congestion boundary within a link (which we later show to be a critical element, relative to LTM). We set out the theoretical background necessary for the formulation of the network-level TTM as a set of linear side constraints. Numerical experiments are used to illustrate the application of the method to determine DSO solutions avoiding spillbacks, reduce/eliminate the congestion and to show the distinctive elements of adopting TTM over LTM. Furthermore, in comparison to a fine-level CTM-based DSO method, our formulation is seen to significantly reduce the number of linear constraints while maintaining a reasonable accuracy.


      PubDate: 2016-01-11T12:53:53Z
       
  • A math-heuristic algorithm for the integrated air service recovery
    • Abstract: Publication date: Available online 4 January 2016
      Source:Transportation Research Part B: Methodological
      Author(s): Dong Zhang, Chuhang Yu, Jitamitra Desai, H.Y.K. Henry Lau
      A sophisticated flight schedule might be easily disrupted due to adverse weather, aircraft mechanical failures, crew absences, etc. Airlines incur huge costs stemming from such flight schedule disruptions in addition to the serious inconveniences experienced by passengers. Therefore, an efficient recovery solution that simultaneously decreases an airline's recovery cost while simultaneously mitigating passenger dissatisfaction is of great importance to the airline industry. In this paper, we study the integrated airline service recovery problem in which the aircraft and passenger schedule recovery problems are simultaneously addressed, with the objective of minimizing aircraft recovery and operating costs, passenger itinerary delay cost, and passenger itinerary cancellation cost. Recognizing the inherent difficulty in modeling the integrated airline service recovery problem within a single formulation (due to its huge solution space and quick response requirement), we propose a three-stage sequential math-heuristic framework to efficiently solve this problem, wherein the flight schedules and aircraft rotations are recovered in the first stage, Then, a flight rescheduling problem and passenger schedule recovery problems are iteratively solved in the next two stages. Time-space network flow representations, along with mixed-integer programming formulations, and algorithms that take advantages of the underlying problem structures, are proposed for each of three stages. This algorithm was tested on realistic data provided by the ROADEF 2009 challenge and the computational results reveal that our algorithm generated the best solution in nearly 72% of the test instances, and a near-optimal solution was achieved in the remaining instances within an acceptable timeframe. Furthermore, we also ran additional computational runs to explore the underlying characteristics of the proposed algorithm, and the recorded insights can serve as a useful guide during practical implementations of this algorithm.


      PubDate: 2016-01-07T12:51:18Z
       
  • Mechanisms that govern how the Price of Anarchy varies with travel demand
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): Steven J O'Hare, Richard D Connors, David P Watling
      Selfish routing, represented by the User-Equilibrium (UE) model, is known to be inefficient when compared to the System Optimum (SO) model. However, there is currently little understanding of how the magnitude of this inefficiency, which can be measured by the Price of Anarchy (PoA), varies across different structures of demand and supply. Such understanding would be useful for both transport policy and network design, as it could help to identify circumstances in which policy interventions that are designed to induce more efficient use of a traffic network, are worth their costs of implementation. This paper identifies four mechanisms that govern how the PoA varies with travel demand in traffic networks with separable and strictly increasing cost functions. For each OD movement, these are expansions and contractions in the sets of routes that are of minimum cost under UE and minimum marginal total cost under SO. The effects of these mechanisms on the PoA are established via a combination of theoretical proofs and conjectures supported by numerical evidence. In addition, for the special case of traffic networks with BPR-like cost functions having common power, it is proven that there is a systematic relationship between link flows under UE and SO, and hence between the levels of demand at which expansions and contractions occur. For this case, numerical evidence also suggests that the PoA has power law decay for large demand.


      PubDate: 2016-01-02T18:08:59Z
       
  • Optimal location of advance warning for mandatory lane change near a
           two-lane highway off-ramp
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): Siyuan Gong, Lili Du
      Improper mandatory lane change (MLC) maneuvers in the vicinity of highway off-ramp will jeopardize traffic efficiency and safety. Providing an advance warning for lane change necessity is one of the efficient methods to perform systematic lane change management, which encourages smooth MLC maneuvers occurring at proper locations to mitigate the negative effects of MLC maneuvers on traffic flow nearby off-ramp. However, the state of the art indicates the lack of rigorous methods to optimally locate this advance warning so that the maximum benefit can be obtained. This research is motivated to address this gap. Specifically, the proposed approach considers that the area downstream of the advance warning includes two zones: (i) the green zone whose traffic ensures safe and smooth lane changes without speed deceleration (S-MLC); the start point of the green zone corresponding to the location of the advance warning; (ii) the yellow zone whose traffic leads to rush lane change maneuvers with speed deceleration (D-MLC). An optimization model is proposed to search for the optimal green and yellow zones. Traffic flow theory such as Greenshield model and shock wave analysis are used to analyze the impacts of the S-MLC and D-MLC maneuvers on the traffic delay. A grid search algorithm is applied to solve the optimization model. Numerical experiments conducted on the simulation model developed in Paramics 6.9.3 indicate that the proposed optimization model can identify the optimal location to set the advance MLC warning nearby an off-ramp so that the traffic delay resulting from lane change maneuvers is minimized, and the corresponding capacity drop and traffic oscillation can be efficiently mitigated. Moreover, the experiments validated the consistency of the green and yellow zones obtained in the simulation traffic flow and from the optimization model for a given optimally located MLC advance warning under various traffic regimes. The proposed approach can be implemented by roadside mobile warning facility or on-board GPS for human-driven vehicles, or embedded into lane change aid systems to serve connected and automated vehicles. Thus it will greatly contribute to both literature and engineering practice in lane change management.


      PubDate: 2016-01-02T18:08:59Z
       
  • Regulating inter-firm agreements: The case of airline codesharing in
           parallel networks
    • Abstract: Publication date: February 2016
      Source:Transportation Research Part B: Methodological, Volume 84
      Author(s): Nicole Adler, Eran Hanany
      We compare aviation markets under conditions of competition, codesharing contracts and anti-trust immune alliances, assuming that demand for flights depends on both fares and the level of frequency offered. Using a hybrid competitive/cooperative game theoretic framework, we show that the stronger the inter-airline agreement on overlapping routes, the higher the producer surplus. On the other hand, consumer surplus and overall social welfare are maximized under limited codesharing agreements. Partial mergers appear preferable to no agreement in ‘thin’ markets, in which both demand and profit margins are relatively low. Inter-governmental agreements are also analyzed and we show that bilaterals create the least favorable market outcomes for consumers and producers. Finally, a realistic case study demonstrates that under asymmetric and uncertain demand, codesharing on parallel links may be preferable to competitive outcomes for multiple consumer types.


      PubDate: 2016-01-02T18:08:59Z
       
  • Editorial Board
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83




      PubDate: 2015-12-29T18:45:13Z
       
  • A marginal utility day-to-day traffic evolution model based on one-step
           strategic thinking
    • Abstract: Publication date: Available online 23 December 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Xiaozheng He, Srinivas Peeta
      Most deterministic day-to-day traffic evolution models, either in continuous-time or discrete-time space, have been formulated based on a fundamental assumption on driver route choice rationality where a driver seeks to maximize her/his marginal benefit defined as the difference between the perceived route costs. The notion of rationality entails the exploration of the marginal decision rule from economic theory, which states that a rational individual evaluates his/her marginal utility, defined as the difference between the marginal benefit and the marginal cost, of each incremental decision. Seeking to analyze the marginal decision rule in the modeling of deterministic day-to-day traffic evolution, this paper proposes a modeling framework which introduces a term to capture the marginal cost to the driver induced by route switching. The proposed framework enables to capture both benefit and cost associated with route changes. The marginal cost is then formulated upon the assumption that drivers are able to predict other drivers’ responses to the current traffic conditions, which is adopted based on the notion of strategic thinking of rational players developed in behavior game theory. The marginal cost based on 1-step strategic thinking also describes the “shadow price” of shifting routes, which helps to explain the behavioral tendency of the driver perceiving the cost-sensitivity to link/route flows. After developing a formulation of the marginal utility day-to-day model, its theoretical properties are analyzed, including the invariance property, asymptotic stability, and relationship with the rational behavioral adjustment process.


      PubDate: 2015-12-25T18:34:57Z
       
  • Train commuters’ scheduling preferences: Evidence from a large-scale
           peak avoidance experiment
    • Abstract: Publication date: Available online 22 December 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Stefanie Peer, Jasper Knockaert, Erik T. Verhoef
      We study the trip scheduling preferences of train commuters in a real-life setting. The underlying data have been collected during large-scale peak avoidance experiment conducted in the Netherlands, in which participants could earn monetary rewards for traveling outside peak hours. The experiment included ca. 1000 participants and lasted for multiple months. Holders of an annual train pass were invited to join the experiment, and a customized smartphone app was used to measure the travel behavior of the participants. We find that compared to the pre-measurement, the relative share of peak trips decreased by 22% during the reward period, and by 10% during the post-measurement. By combining multiple complementary data sources, we are able to specify and estimate (MNL and panel latent class) departure time choice models. These yield plausible estimates for the monetary values that participants attach to reducing travel time, schedule delays, the number of transfers, crowdedness, and unreliability.


      PubDate: 2015-12-25T18:34:57Z
       
  • Improved bush-based methods for network contraction
    • Abstract: Publication date: Available online 23 December 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Ehsan Jafari, Stephen D. Boyles
      Calculating equilibrium sensitivity on a bush can be done very efficiently, and serve as the basis for a network contraction procedure. The contracted network (a simplified network with a few nodes and links) approximates the behavior of the full network but with less complexity. The network contraction method can be advantageous in network design applications where many equilibrium problems must be solved for different design scenarios. The network contraction procedure can also be used to increase the accuracy of subnetwork analysis. This method requires calculating travel time derivatives between two nodes, with respect to the demand between them, assuming that the flow distributes in a way that equilibrium is maintained. Previous research describes two methods for calculating these derivatives. This paper presents a third method, which is simpler, faster, and just as accurate. The method presented in this paper reformulates the linear system of equations defining these sensitivities as the solution to a convex programming problem, which can be solved by making minor modifications to static user equilibrium algorithms. In addition, the model is extended to capture the interactions between the path travel times and network flows, and a heuristic is proposed to compute these interactions. The accuracy and complexity of the proposed methodology are evaluated using the network of Barcelona, Spain. Further, numerical experiments on the Austin, Texas regional network validate its performance for subnetwork analysis applications.


      PubDate: 2015-12-25T18:34:57Z
       
  • Integrating a heterogeneous fixed fleet and a flexible assignment of
           destination depots in the waste collection VRP with intermediate
           facilities
    • Abstract: Publication date: Available online 24 December 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Iliya Markov, Sacha Varone, Michel Bierlaire
      We consider a complex recyclable waste collection problem that extends the class of vehicle routing problems with intermediate facilities by integrating a heterogeneous fixed fleet and a flexible assignment of destination depots. Several additional side constraints, such as a mandated break period contingent on tour start time, multiple vehicle capacities, and site dependencies are also included. This specific problem was inspired by a real-world application and does not appear in the literature. It is modeled as an MILP which is enhanced with several valid inequalities. Due to the rich nature of the problem, state-of-the-art solvers are only able to tackle instances of small to medium size. To solve realistic instances, we propose a multiple neighborhood search heuristic capable of systematically treating all problem features and general enough to respond to the varying characteristics of the case study regions for which it is intended. The results show that the heuristic achieves optimality on small instances, exhibits competitive performance in comparison to state-of-the-art solution methods for special cases of our problem, and leads to important savings in the state of practice. Moreover, it highlights and quantifies the savings from allowing a flexible depot assignment. The data from the state of practice comes from a company in the waste collection industry in Geneva, Switzerland.


      PubDate: 2015-12-25T18:34:57Z
       
  • A two-stage stochastic optimization model for the transfer activity choice
           in metro networks
    • Abstract: Publication date: Available online 17 December 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Lixing Yang, Yan Zhang, Shukai Li, Yuan Gao
      This research focuses on finding the best transfer schemes in metro networks. Using sample-based time-invariant link travel times to capture the uncertainty of a realistic network, a two-stage stochastic integer programming model with the minimized expected travel time and penalty value incurred by transfer activities is formulated. The first stage aims to find a sequence of potential transfer nodes (stations) that can compose a feasible path from origins to destinations in the transfer activity network, and the second stage provides the least time paths passing by the generated transfer stations in the first stage for evaluating the given transfer schemes and then outputs the best routing information. To solve our proposed model, an efficient hybrid algorithm, in which the label correcting algorithm is embedded into a branch and bound searching framework, is presented to find the optimal solutions of the considered problem. Finally, the numerical experiments are implemented in different scales of metro networks. The computational results demonstrate the effectiveness and performance of the proposed approaches even for the large-scale Beijing metro network.


      PubDate: 2015-12-17T15:04:34Z
       
  • Shipping log data based container ship fuel efficiency modeling
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Qiang Meng, Yuquan Du, Yadong Wang
      Container shipping lines have been initiating various ship fuel efficiency management programs because bunker fuel costs always dominate the daily operating costs of a container ship. As the basis of these kinds of programs, we develop a viable research methodology for modeling the relationship between the fuel consumption rate of a particular container ship and its determinants, including sailing speed, displacement, sea conditions and weather conditions, by using the shipping log data available in practice. The developed methodology consists of an outlier-score-based data preprocessing procedure to tackle the fuzziness, inaccuracy and limited information of shipping logs, and two regression models for container ship fuel efficiency. Real shipping logs from four container ships (two with 13000 TEUs and two with 5000 TEUs) over a six-month sailing period are used to exhibit the applicability and effectiveness of the proposed methodology. The empirical studies demonstrate the performance of three models for fitting the fuel consumption rate of a ship and the industrial merits of ship fuel efficiency management. In addition, we highlight the potential impacts of the models developed in this study on liner shipping network analysis, as these models can serve as base models for additionally considering the influence of displacement and weather conditions on ship fuel efficiency and exhaust emissions.


      PubDate: 2015-12-17T15:04:34Z
       
  • A conflict-based path-generation heuristic for evacuation planning
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Victor Pillac, Pascal Van Hentenryck, Caroline Even
      Evacuation planning and scheduling is a critical aspect of disaster management and national security applications. This paper proposes a conflict-based path-generation approach for evacuation planning. Its key idea is to decompose the evacuation planning problem into a master and a subproblem. The subproblem generates new evacuation paths for each evacuated area, while the master problem optimizes the flow of evacuees and produce an evacuation plan. Each new path is generated to remedy conflicts in the evacuation flows and adds new columns and a new row in the master problem. The algorithm is applied to a set of large-scale evacuation scenarios ranging from the Hawkesbury-Nepean flood plain (West Sydney, Australia) which require evacuating in the order of 70,000 persons, to the New Orleans metropolitan area and its 1,000,000 residents. Experiments illustrate the scalability of the approach which is able to produce evacuation for scenarios with more than 1200 nodes, while a direct Mixed Integer Programming formulation becomes intractable for instances with more than 5 nodes. With this approach, realistic evacuations scenarios can be solved near-optimally in reasonable time, supporting both evacuation planning in strategic, tactical, and operational environments.


      PubDate: 2015-12-13T06:55:17Z
       
  • Demand responsive transit systems with time-dependent demand: User
           equilibrium, system optimum, and management strategy
    • Abstract: Publication date: Available online 11 December 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Mahyar Amirgholy, Eric J. Gonzales
      The operating cost of a demand responsive transit (DRT) system strictly depends on the quality of service that it offers to its users. An operating agency seeks to minimize operating costs while maintaining the quality of service while users experience costs associated with scheduling, waiting, and traveling within the system. In this paper, an analytical model is employed to approximate the agency's operating cost for running a DRT system with dynamic demand and the total generalized cost that users experience as a result of the operating decisions. The approach makes use of Vickrey's (1969) congestion theory to model the dynamics of the DRT system in the equilibrium condition and approximate the generalized cost for users when the operating capacity is inadequate to serve the time-dependent demand over the peak period without excess delay. The efficiency of the DRT system can be improved by optimizing one of three parameters that define the agency's operating decision: (1) the operating capacity of the system, (2) the number of passengers that have requested a pick-up and are awaiting service, and (3) the distribution of requested times for service from the DRT system. A schedule management strategy and dynamic pricing strategies are presented that can be implemented to manage demand and reduce the total cost of the DRT system by keeping the number of waiting requests optimized over the peak period. In the end, proposed optimization strategies are compared using a numerical example.


      PubDate: 2015-12-13T06:55:17Z
       
  • The nonlinear equation system approach to solving dynamic user optimal
           simultaneous route and departure time choice problems
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Jiancheng Long, W.Y. Szeto, Ziyou Gao, Hai-Jun Huang, Qin Shi
      Dynamic user optimal simultaneous route and departure time choice (DUO-SRDTC) problems are usually formulated as variational inequality (VI) problems whose solution algorithms generally require continuous and monotone route travel cost functions to guarantee convergence. However, the monotonicity of the route travel cost functions cannot be ensured even if the route travel time functions are monotone. In contrast to traditional formulations, this paper formulates a DUO-SRDTC problem (that can have fixed or elastic demand) as a system of nonlinear equations. The system of nonlinear equations is a function of generalized origin-destination (OD) travel costs rather than route flows and includes a dynamic user optimal (DUO) route choice subproblem with perfectly elastic demand and a quadratic programming (QP) subproblem under certain assumptions. This study also proposes a solution method based on the backtracking inexact Broyden–Fletcher–Goldfarb–Shanno (BFGS) method, the extragradient algorithm, and the Frank-Wolfe algorithm. The BFGS method, the extragradient algorithm, and the Frank-Wolfe algorithm are used to solve the system of nonlinear equations, the DUO route choice subproblem, and the QP subproblem, respectively. The proposed formulation and solution method can avoid the requirement of monotonicity of the route travel cost functions to obtain a convergent solution and provide a new approach with which to solve DUO-SRDTC problems. Finally, numeric examples are used to demonstrate the performance of the proposed solution method.


      PubDate: 2015-12-13T06:55:17Z
       
  • A heterogeneous reliable location model with risk pooling under supply
           disruptions
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Ying Zhang, Lawrence V. Snyder, Mingyao Qi, Lixin Miao
      This paper investigates a facility location model that considers the disruptions of facilities and the cost savings from the inventory risk-pooling effect and economies of scale. Facilities may have heterogeneous disruption probabilities. When a facility fails, its customers may be reassigned to other surviving ones to hedge against lost-sales costs. We first develop both an exact and an approximate expression for the nonlinear inventory cost, and then formulate the problem as a nonlinear integer programming model. The objective is to minimize the expected total cost across all possible facility failure scenarios. To solve this problem, we design two methods, an exact approach using special ordered sets of type two (SOS2) and a heuristic based on Lagrangian relaxation. We test the model and algorithms on data sets with up to 150 nodes. Computational results show that the proposed algorithms can solve the problem efficiently in reasonable time. Managerial insights on the optimal facility deployment, customer assignments and inventory control strategies are also drawn.


      PubDate: 2015-12-13T06:55:17Z
       
  • Real-time holding control for high-frequency transit with dynamics
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): G.E. Sánchez-Martínez, H.N. Koutsopoulos, N.H.M. Wilson
      Operations control is an important means of improving service quality for high-frequency transit. Past research on real-time control has focused on developing and evaluating the effectiveness of different control strategies, largely relying on running times and demand which are assumed to be static. We formulate a mathematical model for holding control optimization that reflects dynamic running times and demand. The model can be used to produce a plan of holding times that accounts not only for the current state of the system, but also for expected changes in running times and demand. We evaluate the effectiveness of the model within a simulation environment. The results show that control based on dynamic inputs outperforms its static equivalent in high demand cases where passengers can be left behind at stops, and to a lesser extent in low to moderate demand cases with time-varying running times.


      PubDate: 2015-12-13T06:55:17Z
       
  • Activity imputation for trip-chains elicited from smart-card data using a
           continuous hidden Markov model
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Gain Han, Keemin Sohn
      Although smart-card data were expected to substitute for conventional travel surveys, the reality is that only a few automatic fare collection (AFC) systems can recognize an individual passenger's origin, transfer, and destination stops (or stations). The Seoul metropolitan area is equipped with a system wherein a passenger's entire trajectory can be tracked. Despite this great advantage, the use of smart-card data has a critical limitation wherein the purpose behind a trip is unknown. The present study proposed a rigorous methodology to impute the sequence of activities for each trip chain using a continuous hidden Markov model (CHMM), which belongs to the category of unsupervised machine-learning technologies. Coupled with the spatial and temporal information on trip chains from smart-card data, land-use characteristics were used to train a CHMM. Unlike supervised models that have been mobilized to impute the trip purpose to GPS data, A CHMM does not require an extra survey, such as the prompted-recall survey, in order to obtain labeled data for training. The estimated result of the proposed model yielded plausible activity patterns that are intuitively accountable and consistent with observed activity patterns.


      PubDate: 2015-12-13T06:55:17Z
       
  • Generalized Extreme Value models for count data: Application to worker
           telecommuting frequency choices
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Rajesh Paleti
      Count models are used for analyzing outcomes that can only take non-negative integer values with or without any pre-specified large upper limit. However, count models are typically considered to be different from random utility models such as the multinomial logit (MNL) model. In this paper, Generalized Extreme Value (GEV) models that are consistent with the Random Utility Maximization (RUM) framework and that subsume standard count models including Poisson, Geometric, Negative Binomial, Binomial, and Logarithmic models as special cases were developed. The ability of the Maximum Likelihood (ML) inference approach to retrieve the parameters of the resulting GEV count models was examined using synthetic data. The simulation results indicate that the ML estimation technique performs quite well in terms of recovering the true parameters of the proposed GEV count models. Also, the models developed were used to analyze the monthly telecommuting frequency decisions of workers. Overall, the empirical results demonstrate superior data fit and better predictive performance of the GEV models compared to standard count models.


      PubDate: 2015-12-13T06:55:17Z
       
  • E-commerce and traffic congestion: An economic and policy analysis
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Jing Shao, Hangjun Yang, Xiaoqiang Xing, Liu Yang
      E-commerce, due to its ability to re-direct consumers from physical stores to online, can potentially alleviate traffic congestion. In this paper, we set up a theoretic model to analyze interactions between a firm’s distribution strategy and traffic congestion. In an unregulated economy, we first characterize the private firm’s optimal strategy concerning e-commerce under the influence of traffic congestion. We then examine a centralized economy where the firm is publicly owned and derive the distribution strategy that maximizes social welfare. Comparing the two cases, we show that the private firm’s incentives may deviate from the socially optimal decisions, which leads to inefficiency. We identify two effects, i.e., monopoly effect and congestion externality effect, which drive the private firm to deviate from the social optimum. Based on our analysis, we propose a differentiated tolls/rebates policy to achieve maximum social welfare. Under such a policy, the firm will not only adopt the socially optimal distribution strategy but offer the socially optimal quantities.


      PubDate: 2015-12-13T06:55:17Z
       
  • Second best toll pricing within the framework of bounded rationality
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Xuan Di, Henry X. Liu, Xuegang (Jeff) Ban
      The network design problem is usually formulated as a bi-level program, assuming the user equilibrium is attained in the lower level program. Given boundedly rational route choice behavior, the lower-level program is replaced with the boundedly rational user equilibria (BRUE). The network design problem with boundedly rational route choice behavior is understudied due to non-uniqueness of the BRUE. In this study, thus, we mainly focus on boundedly rational toll pricing (BR-TP) with affine link cost functions. The topological properties of the lower level BRUE set are first explored. As the BRUE solution is generally non-unique, urban planners cannot predict exactly which equilibrium flow pattern the transportation network will operate after a planning strategy is implemented. Due to the risk caused by uncertainty of people’s reaction, two extreme scenarios are considered: the traffic flow patterns with either the minimum system travel cost or the maximum, which is the “risk-prone” (BR-TP-RP) or the “risk-averse” (BR-TP-RA) scenario respectively. The upper level BR-TP is to find an optimal toll minimizing the total system travel cost, while the lower level is to find the best or the worst scenario. Accordingly BR-TP can be formulated as either a min –min  or a min –max  program. Solution existence is discussed based on the topological properties of the BRUE and algorithms are proposed. Two examples are accompanied to illustrate the proposed methodology.


      PubDate: 2015-12-13T06:55:17Z
       
  • Bottleneck congestion: Differentiating the coarse charge
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Jasper Knockaert, Erik T. Verhoef, Jan Rouwendal
      The traditional bottleneck model for road congestion promotes the implementation of a triangular, and time varying, charge as the optimal solution for the road congestion externality. However, cognitive and technological barriers put a practical limit to the degree of differentiation real world implementations can handle. The traditional approach to accommodate for this concern has been a step toll, with the single step coarse charge as its simplest case. In this paper we study how efficiency of the coarse charge can be improved by differentiating its level and timing across groups of travellers. We use the traditional bottleneck model to analyse how the coarse charge can be differentiated over two groups of travellers assuming inelastic peak-hour demand. The results of our analysis indicate that differentiating the coarse charge across two groups of travellers considerably improves its efficiency without increasing cognitive effort and decision making costs for the individual traveller. A numeric illustration reveals a welfare gain of 69% of the first-best charge, up from 53% for the generic coarse charge. This increase is similar to what is obtained by moving from the coarse charge to a generic two step toll. Once different groups have been defined, one could in fact achieve the same gains by temporal separation of drivers, for example by use of licence plate numbers. The presented charging regime has a considerable degree of flexibility with respect to the share of travellers to attribute to each scheme, which further adds to its merits in practical applicability.


      PubDate: 2015-12-13T06:55:17Z
       
  • Modeling and optimization of multimodal urban networks with limited
           parking and dynamic pricing
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Nan Zheng, Nikolas Geroliminis
      Cruising-for-parking constraints mobility in urban networks. Car-users may have to cruise for on-street parking before reaching their destinations. The accessibility and the cost of parking significantly influence people's travel behavior (such as mode choice, or parking facility choice between on-street and garage). The cruising flow causes delays eventually to everyone, even users with destinations outside limited parking areas. It is therefore important to understand the impact of parking limitation on mobility, and to identify efficient parking policies for travel cost reduction. Most existing studies on parking fall short in reproducing the dynamic spatiotemporal features of traffic congestion in general, lack the treatment of dynamics of the cruising-for-parking phenomenon, or require detailed input data that are typically costly and difficult to collect. In this paper, we propose an aggregated and dynamic approach for modeling multimodal traffic with the treatment on parking, and utilize the approach to design dynamic parking pricing strategies. The proposed approach is based on the Macroscopic Fundamental Diagram (MFD), which can capture congestion dynamics at network-level for single-mode and bi-modal (car and bus) systems. A parsimonious parking model is integrated into the MFD-based multimodal modeling framework, where the dynamics of vehicular and passenger flows are considered with a change in the aggregated behavior (e.g. mode choice and parking facility choice) caused by cruising and congestion. Pricing strategies are developed with the objective of reducing congestion, as well as lowering the total travel cost of all users. A case study is carried out for a bi-modal city network with a congested downtown region. An elegant feedback dynamic parking pricing strategy can effectively reduce travel delay of cruising and the generic congestion. Remarkably, such strategy, which is applicable in real-time management with limited available data, is fairly as efficient as a dynamic pricing scheme obtained from system optimum conditions and a global optimization with full information about the future states of the system. Stackelberg equilibrium is also investigated in a competitive behavior between different parking facility operators. Policy indications on on-street storage capacity management and pricing are provided.


      PubDate: 2015-12-13T06:55:17Z
       
  • Regulating hazardous materials transportation by dual toll pricing
    • Abstract: Publication date: January 2016
      Source:Transportation Research Part B: Methodological, Volume 83
      Author(s): Tolou Esfandeh, Changhyun Kwon, Rajan Batta
      We investigate dual-toll setting as a policy tool to mitigate the risk of hazardous material (hazmat) shipment in road networks. We formulate the dual-toll problem as a bi-level program wherein the upper level aims at minimizing the risk, and the lower level explores the user equilibrium decision of the regular vehicles and hazmat carriers given the toll. When the upper level objective is to minimize the risk and all links are tollable, we decompose the formulation into first-stage and second-stage, and suggest a computational method to solve each stage. Our two-stage solution methodology guarantees nonnegative valid dual tolls regardless of the solution accuracy of the first-stage problem. We also consider a general dual-toll setting problem where the regulator rather wishes to minimize a combination of risk and the paid tolls and/or some links are untollable. To solve this truly bilevel problem, we provide heuristic algorithms that decompose the problem into subproblems each being solved by a line search. Case studies based on the Sioux Falls network illustrate the insights on the dual-toll policies.


      PubDate: 2015-12-13T06:55:17Z
       
  • Editorial Board
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82




      PubDate: 2015-11-28T20:20:04Z
       
  • A driving force model for non-strict priority crossing behaviors of
           right-turn drivers
    • Abstract: Publication date: Available online 18 November 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Dianchao Lin, Wanjing Ma, Li Li, Yinhai Wang
      At urban intersections, conflicts between right-turn vehicles and through non-motorized vehicles are a critical cause of traffic congestion and safety challenges. Based on the fact that in different countries there is no strict priority in conflicts between motorized and non-motorized vehicles, this study focused on analysis of the inherent mechanism of this universal phenomenon. By the analogy of a force model for moving vehicles, this paper developed a micro driving force model, including the safety driving force and efficiency driving force, for right-turn drivers which constitute the dominant party during the non-strict priority crossing process. We further demonstrate that the strict priority crossing behavior is a special case of the proposed driving force model. All the parameters used in this model were calibrated through field data collected at twelve signalized intersection sites in Shanghai. Model validation results proved the accuracy and reliability of the proposed driving force model. The model was further proved that it can be used for right-turn vehicle's average crossing speed prediction. The sensitivity analysis identified the influence of vehicle type, non-motorized traffic flow rate, and non-motorized traffic speed on the average speed, and offered support for the rationality of the non-strict priority.


      PubDate: 2015-11-25T12:37:56Z
       
  • Improved models for technology choice in a transit corridor with fixed
           demand
    • Abstract: Publication date: Available online 21 November 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Luigi Moccia, Gilbert Laporte
      We present three extensions to a base optimization model for a transit line which can be used to strategically evaluate technology choices. We add to the base model optimal stop spacing and train length, a crowding penalty, and a multi-period generalization. These extensions are analytically solvable by simple approximations and lead to meaningful insights. Their significance is illustrated by means of an example in which two road modes and two rail modes are defined by a set of techno-economical parameters. These parameters loaded in the base model yield dominance of road modes for all but the largest demand levels. We consistently keep this set of parameters for all models, and show how the break-even points between road and rail modes progressively recede toward lower demand levels when model refinements – not parameter changes – are applied. Scenario analyses of plausible parameter sets highlight the model’s versatility, and caution on general conclusions regarding technology dominance.


      PubDate: 2015-11-25T12:37:56Z
       
  • Integrated modeling of high performance passenger and freight train
           planning on shared-use corridors in the US
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Ahmadreza Talebian, Bo Zou
      This paper studies strategic level train planning for high performance passenger and freight train operations on shared-use corridors in the US. We develop a hypergraph-based, two-level approach to sequentially minimize passenger and freight costs while scheduling train services. Passenger schedule delay and freight lost demand are explicitly modeled. We explore different solution strategies and conclude that a problem-tailored linearized reformulation yields superior computational performance. Using realistic parameter values, our numerical experiments show that passenger cost due to schedule delay is comparable to in-vehicle travel time cost and rail fare. In most cases, marginal freight cost increase from scheduling more passenger trains is higher than marginal reduction in passenger schedule delay cost. The heterogeneity of train speed reduces the number of freight trains that can run on a corridor. Greater tolerance for delays could reduce lost demand and overall cost on the freight side. The approach developed in the paper could be applied to other scenarios with different parameter values.


      PubDate: 2015-11-12T13:14:14Z
       
  • Airport congestion pricing and terminal investment: Effects of terminal
           congestion, passenger types, and concessions
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Yulai Wan, Changmin Jiang, Anming Zhang
      None of the airport-pricing studies have differentiated the congestion incurred in the terminals from the congestion incurred on the runways. This paper models and connects the two kinds of congestion in one joint model. This is done by adopting a deterministic bottleneck model for the terminal to describe passengers’ behavior, and a simpler static congestion model for the runway. We find that different from the results obtained in the literature, uniform airfare does not yield the first-best outcome when terminal congestion is explicitly taken into account. In particular, business passengers are at first-best charged a higher fare than leisure passengers if and only if their relative schedule-delay cost is higher. We further identify circumstances under which passengers are, given a uniform airport charge scheme, under- or over-charged with respect to the terminal charge. Furthermore, when concession surplus is added to the analysis, the airport may raise (rather than reduce) the airport charge in order to induce more business passengers who in turn will lengthen leisure passengers’ dwell time and hence increase their chance of purchasing concession goods. Finally, the impacts of terminal capacity expansion and time-varying terminal fine toll are discussed.


      PubDate: 2015-11-12T13:14:14Z
       
  • Real-time schedule recovery in liner shipping service with regular
           uncertainties and disruption events
    • Abstract: Publication date: Available online 10 November 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Chen Li, Xiangtong Qi, Dongping Song
      This paper studies real-time schedule recovery policies for liner shipping under various regular uncertainties and the emerging disruption event that may delay a vessel from its planned schedule. The aim is to recover the affected schedule in the most efficient way. One important contribution of this work is to explicitly distinguish two types of uncertainties in liner shipping, and propose different strategies to handle them. The problem can be formulated as a multi-stage stochastic control problem that minimizes the total expected fuel cost and delay penalty. For regular uncertainties that can be characterized by appropriate probabilistic models, we develop the properties of the optimal control policy; then we show how an emerging disruption may change the control policies. Numerical studies demonstrate the advantages of real-time schedule recovery policies against some typical alternatives.


      PubDate: 2015-11-12T13:14:14Z
       
  • Editorial Board
    • Abstract: Publication date: November 2015
      Source:Transportation Research Part B: Methodological, Volume 81, Part 1




      PubDate: 2015-11-12T13:14:14Z
       
  • Liner container seasonal shipping revenue management
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Yadong Wang, Qiang Meng, Yuquan Du
      This paper proposes a liner container seasonal shipping revenue management problem for a container shipping company. For a given weekly multi-type shipment demand pattern in a particular season, the proposed problem aims to maximize the total seasonal shipping profit by determining the number of multi-type containers to be transported and assigned on each container route, the number of containerships deployed on each ship route, and the sailing speed of containerships on each shipping leg subject to both the volume and capacity constraints of each containership. By adopting the realistic bunker consumption rate of a containership as a function of its sailing speed and payload (displacement), we develop a mixed-integer nonlinear programing with a nonconvex objective function for the proposed liner container seasonal shipping revenue management problem. A tailored branch and bound (B&B) method is designed to obtain the global ε-optimal solution of the model. Numerical experiments are finally conducted to assess the efficiency of the solution algorithm and to show the applicability of the developed model.


      PubDate: 2015-11-12T13:14:14Z
       
  • An evolutionary local search for the capacitated vehicle routing problem
           minimizing fuel consumption under three-dimensional loading constraints
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Zhenzhen Zhang, Lijun Wei, Andrew Lim
      This study introduces a new practical variant of the combined routing and loading problem called the capacitated vehicle routing problem minimizing fuel consumption under three-dimensional loading constraints (3L-FCVRP). It presents a meta-heuristic algorithm for solving the problem. The aim is to design routes for a fleet of homogeneous vehicles that will serve all customers, whose demands are formed by a set of three-dimensional, rectangular, weighted items. Unlike the well-studied capacitated vehicle routing problem with 3D loading constraints (3L-CVRP), the objective of the 3L-FCVRP is to minimize total fuel consumption rather than travel distance. The fuel consumption rate is assumed to be proportionate to the total weight of the vehicle. A route is feasible only if a feasible loading plan to load the demanded items into the vehicle exists and the loading plan must satisfy a set of practical constraints. To solve this problem, the evolutionary local search (ELS) framework incorporating the recombination method is used to explore the solution space, and a new heuristic based on open space is used to examine the feasibility of the solutions. In addition, two special data structures, Trie and Fibonacci heap, are adopted to speed up the procedure. To verify the effectiveness of our approach, we first test the ELS on the 3L-CVRP, which can be seen as a special case of the 3L-FCVRP. The results demonstrate that on average ELS outperforms all of the existing approaches and improves the best-known solutions for most instances. Then, we generate data for 3L-FCVRP and report the detailed results of the ELS for future comparisons.


      PubDate: 2015-11-12T13:14:14Z
       
  • Speed-spacing dependency on relative speed from the adjacent lane: New
           insights for car following models
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Balaji Ponnu, Benjamin Coifman
      This paper examines the traffic dynamics underlying a recently observed phenomenon, the so called “sympathy of speeds” whereby a high occupancy vehicle (HOV) lane seemingly exhibits lower vehicular capacity and lower flow at speeds throughout the congested regime compared to the adjacent general purpose (GP) lanes. Unlike previous studies this paper examines a time-of-day HOV lane. During the non-HOV periods the study lane reverts to a GP lane, thereby providing a control condition for the specific lane and location. This work uses the single vehicle passage (svp) method to group vehicle passages before measuring the traffic state and extends the svp to bin vehicles in the study lane based on the relative speed to the adjacent lane. The extended svp method allows the work to also study the impacts during the non-HOV periods when the study lane serves GP vehicles. This work finds that: (1) during the non-HOV periods the study lane exhibited behavior indistinguishable from the adjacent GP lane. (2) The sympathy of speeds persists throughout the day, even when the study lane serves GP vehicles. (3) The relative speed to the adjacent lane provided a better predictor of behavior than whether or not the HOV restriction is active. In short, the car following behavior that gives rise to the sympathy of speeds is unrelated to the HOV restriction per se, persisting under GP operations as well. This dependency on the relative speed in the adjacent lane is an important finding given the fact that most existing car following models assume that the longitudinal acceleration of a following vehicle is strictly a function of the relationship to the leading vehicle in the same lane. Because drivers in general adopt a larger spacing when faced with a high differential in speed between lanes means that car following behavior also depends on the relative speed to the adjacent lane. This fact has likely gone unnoticed to date because generally the conditions that give rise to a differential in speeds between lanes are usually short lived, and thus, do not become apparent in conventional macroscopic data except under exceptional circumstances that include confounding factors like HOV operations.


      PubDate: 2015-11-12T13:14:14Z
       
  • Long queue estimation for signalized intersections using mobile data
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Peng Hao, Xuegang Ban
      Queue length is one of the key measures in assessing arterial performances. Under heavy congestion, queues are difficult to estimate from either fixed-location sensors (such as loop detectors) or mobile sensors since they may exceed the region of detection, which is defined as long queue in the literature. While the long queue problem has been successfully addressed in the past using fixed-location sensors, whether this can be done using mobile traffic sensors remains unclear. In this paper, a queue length estimation method is proposed to solve this long queue problem using short vehicle trajectories obtained from mobile sensors. The method contains vehicle trajectory reconstruction models to estimate the missing deceleration or acceleration process of a vehicle. Long queue estimation models are then developed using the reconstructed vehicle trajectories. The proposed method can provide estimates of the queue profile and the maximum queue length of a cycle. The method is tested in a field experiment with reasonable results.


      PubDate: 2015-11-12T13:14:14Z
       
  • The benefits of meeting points in ride-sharing systems
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Mitja Stiglic, Niels Agatz, Martin Savelsbergh, Mirko Gradisar
      We investigate the potential benefits of introducing meeting points in a ride-sharing system. With meeting points, riders can be picked up and dropped off either at their origin and destination or at a meeting point that is within a certain distance from their origin or destination. The increased flexibility results in additional feasible matches between drivers and riders, and allows a driver to be matched with multiple riders without increasing the number of stops the driver needs to make. We design and implement an algorithm that optimally matches drivers and riders in large-scale ride-sharing systems with meeting points. We perform an extensive simulation study to assess the benefits of meeting points. The results demonstrate that meeting points can significantly increase the number of matched participants as well as the system-wide driving distance savings in a ride-sharing system.


      PubDate: 2015-11-12T13:14:14Z
       
  • A green intermodal service network design problem with travel time
           uncertainty
    • Abstract: Publication date: Available online 3 November 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Emrah Demir, Wolfgang Burgholzer, Martin Hrušovský, Emel Arıkan, Werner Jammernegg, Tom Van Woensel
      In a more and more competitive and global world, freight transports have to overcome increasingly long distances while at the same time becoming more reliable. In addition, a raising awareness of the need for environmentally friendly solutions increases the importance of transportation modes other than road. Intermodal transportation, in that regard, allows for the combination of different modes in order to exploit their individual advantages. Intermodal transportation networks offer flexible, robust and environmentally friendly alternatives to transport high volumes of goods over long distances. In order to reflect these advantages, it is the challenge to develop models which both represent multiple modes and their characteristics (e.g., fixed-time schedules and routes) as well as the transhipment between these transportation modes. In this paper, we introduce a Green Intermodal Service Network Design Problem with Travel Time Uncertainty (GISND-TTU) for combined offline intermodal routing decisions of multiple commodities. The proposed stochastic approach allows for the generation of robust transportation plans according to different objectives (i.e., cost, time and greenhouse gas (GHG) emissions) by considering uncertainties in travel times as well as demands with the help of the sample average approximation method. The proposed methodology is applied to a real-world network, which shows the advantages of stochasticity in achieving robust transportation plans.


      PubDate: 2015-11-04T15:36:43Z
       
  • Revisiting the Task–Capability Interface model for incorporating
           human factors into car-following models
    • Abstract: Publication date: December 2015
      Source:Transportation Research Part B: Methodological, Volume 82
      Author(s): Mohammad Saifuzzaman, Zuduo Zheng, Md. Mazharul Haque, Simon Washington
      Human factors such as distraction, fatigue, alcohol and drug use are generally ignored in car-following (CF) models. Such ignorance overestimates driver capability and leads to most CF models’ inability in realistically explaining human driving behaviors. This paper proposes a novel car-following modeling framework by introducing the difficulty of driving task measured as the dynamic interaction between driving task demand and driver capability. Task difficulty is formulated based on the famous Task–Capability Interface (TCI) model, which explains the motivations behind driver's decision making. The proposed method is applied to enhance two popular CF models: Gipps’ model and IDM, and named as TDGipps and TDIDM respectively. The behavioral soundness of TDGipps and TDIDM are discussed and their stabilities are analyzed. Moreover, the enhanced models are calibrated with the vehicle trajectory data, and validated to explain both regular and human factor influenced CF behavior (which is distraction caused by hand-held mobile phone conversation in this paper). Both the models show better performance than their predecessors, especially in presence of human factors.


      PubDate: 2015-10-26T12:51:33Z
       
 
 
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