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  Subjects -> TRANSPORTATION (Total: 161 journals)
    - AIR TRANSPORT (7 journals)
    - AUTOMOBILES (20 journals)
    - RAILROADS (4 journals)
    - ROADS AND TRAFFIC (4 journals)
    - SHIPS AND SHIPPING (27 journals)
    - TRANSPORTATION (99 journals)

TRANSPORTATION (99 journals)

Accident Analysis & Prevention     Partially Free   (Followers: 43)
AI & Society     Hybrid Journal   (Followers: 3)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 1)
Archives of Transport     Open Access   (Followers: 18)
Bitácora Urbano-Territorial     Open Access   (Followers: 2)
Botswana Journal of Technology     Full-text available via subscription  
Case Studies on Transport Policy     Hybrid Journal   (Followers: 3)
Cities in the 21st Century     Open Access   (Followers: 12)
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: 6)
European Transport Research Review     Open Access   (Followers: 25)
Geosystem Engineering     Hybrid Journal   (Followers: 3)
IATSS Research     Open Access  
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 6)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 5)
International Innovation – Transport     Open Access   (Followers: 7)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 5)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 5)
International Journal of Critical Infrastructure Protection     Hybrid Journal   (Followers: 6)
International Journal of e-Navigation and Maritime Economy     Open Access  
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 6)
International Journal of Electronic Transport     Hybrid Journal   (Followers: 5)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 8)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 5)
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: 8)
International Journal of Services Technology and Management     Hybrid Journal   (Followers: 1)
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 8)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 16)
International Journal of Transportation Science and Technology     Full-text available via subscription   (Followers: 6)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 4)
International Journal of Vehicular Technology     Open Access   (Followers: 3)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 11)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 1)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 2)
Journal of Navigation     Hybrid Journal   (Followers: 109)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 9)
Journal of Sustainable Mobility     Full-text available via subscription  
Journal of the Transportation Research Forum     Open Access   (Followers: 5)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access  
Journal of Transport & Health     Hybrid Journal   (Followers: 4)
Journal of Transport and Land Use     Open Access   (Followers: 20)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 7)
Journal of Transport Geography     Hybrid Journal   (Followers: 17)
Journal of Transport History     Full-text available via subscription   (Followers: 12)
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: 14)
Journal of Transportation Technologies     Open Access   (Followers: 12)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 7)
Les Dossiers du Grihl     Open Access  
Logistique & Management     Full-text available via subscription  
Mobility in History     Full-text available via subscription   (Followers: 1)
Modern Transportation     Open Access   (Followers: 6)
Nonlinear Dynamics     Hybrid Journal   (Followers: 5)
Open Journal of Safety Science and Technology     Open Access   (Followers: 5)
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: 9)
PS: Political Science & Politics     Full-text available via subscription   (Followers: 24)
Public Transport     Hybrid Journal   (Followers: 15)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 2)
Research in Transportation Business and Management     Partially Free   (Followers: 3)
Revista Transporte y Territorio     Open Access   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 1)
Sport, Education and Society     Hybrid Journal   (Followers: 13)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 3)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 2)
Tire Science and Technology     Full-text available via subscription   (Followers: 2)
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: 24)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 7)
Transportation Journal     Full-text available via subscription   (Followers: 11)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 1)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 30)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 28)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 18)
Transportation Research Procedia     Open Access   (Followers: 1)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 34)
Transportation Science     Full-text available via subscription   (Followers: 17)
TRANSPORTES     Open Access   (Followers: 4)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 2)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 3)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 1)
Urban, Planning and Transport Research     Open Access   (Followers: 14)
Vehicular Communications     Full-text available via subscription   (Followers: 1)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 3)
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  [2812 journals]
  • Path-differentiated pricing in congestion mitigation
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Mahmood Zangui, Hedayat Z. Aashtiani, Siriphong Lawphongpanich, Yafeng Yin
      Instead of charging tolls on individual links, this paper considers doing the same on paths. Path and link tolls are “valid” if they encourage motorists to use routes that collectively lead to a target distribution, e.g., one that minimizes travel delay. Because the numbers of valid link and path tolls are typically infinite, an objective in pricing tolls is to find a set of valid tolls that yields the least revenue to lessen the financial burden on motorists. Path tolls are generally more flexible than link tolls and this paper shows that this flexibility can substantially reduce the financial burden on motorists. Additionally, valid path tolls yielding the least revenue possess characteristics with interesting policy implications. To determine these path tolls, it is natural to formulate the problem as a mathematical program with complementarity constraints. However, this paper also investigates alternative formulations that highlight the problem’s complexity and suggest ways to solve the problem efficiently.


      PubDate: 2015-07-31T10:58:59Z
       
  • On multi-objective stochastic user equilibrium
    • Abstract: Publication date: Available online 29 July 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Matthias Ehrgott, Judith Y.T. Wang, David P. Watling
      There is extensive empirical evidence that travellers consider many qualities (travel time, tolls, reliability, etc.) when choosing between alternative routes. Two main approaches exist to deal with this in network assignment models: Combine all qualities into a single (linear) utility function, or solve a multi-objective problem. The former has the advantages of a unique solution and efficient algorithms; the latter, however, is more general, but leads to many solutions and is difficult to implement in larger systems. In the present paper we present three alternative approaches for combining the principles of multi-objective decision-making with a stochastic user equilibrium model based on random utility theory. The aim is to deduce a tractable, analytic method. The three methods are compared both in terms of their theoretical principles, and in terms of the implied trade-offs, illustrated through simple numerical examples.


      PubDate: 2015-07-31T10:58:59Z
       
  • Specification of the cross-nested logit model with sampling of
           alternatives for route choice models
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Xinjun Lai, Michel Bierlaire
      We present an operational estimation procedure for the estimation of route choice multivariate extreme value (MEV) models based on sampling of alternatives. The procedure builds on the state-of-the-art literature, and in particular on recent methodological developments proposed by Flötteröd and Bierlaire (2013) and Guevara and Ben-Akiva (2013b). Case studies on both synthetic data and a real network demonstrate that the new method is valid and practical.


      PubDate: 2015-07-31T10:58:59Z
       
  • Rail-based public transport and urban spatial structure: The interplay
           between network design, congestion and urban form
    • Abstract: Publication date: Available online 23 July 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Martijn I. Dröes, Piet Rietveld
      We examine the effect of spatial differences in access to a railway network on both urbanization and road congestion in a typical ‘transport corridor between cities’ setup. Using a spatial urban equilibrium model, we find that if the number of access nodes, i.e. stations, is limited, stations contribute to the degree of urbanization. The total effect on road congestion, however, is small. By contrast, if stations are omnipresent there is little effect on urban spatial structure, but a considerable decrease in congestion. This suggests there is a policy trade-off between congestion and urbanization which crucially depends on the type of railway network. We find similar results for a within-city metro network. The key methodological contribution is that, besides the dependence between mode choice and where to work/live, the model allows for differences in the degree of substitutability – local competition – between transport modes. We find that an increase in the substitutability between car travel and railway travel substantially decreases the congestion reduction benefits of a dense railway network.


      PubDate: 2015-07-27T13:31:47Z
       
  • A simple nonparametric car-following model driven by field data
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Zhengbing He, Liang Zheng, Wei Guan
      Car-following models are always of great interest of traffic engineers and researchers. In the age of mass data, this paper proposes a nonparametric car-following model driven by field data. Different from most of the existing car-following models, neither driver’s behaviour parameters nor fundamental diagrams are assumed in the data-driven model. The model is proposed based on the simple k-nearest neighbour, which outputs the average of the most similar cases, i.e., the most likely driving behaviour under the current circumstance. The inputs and outputs are selected, and the determination of the only parameter k is introduced. Three simulation scenarios are conducted to test the model. The first scenario is to simulate platoons following real leaders, where traffic waves with constant speed and the detailed trajectories are observed to be consistent with the empirical data. Driver’s rubbernecking behaviour and driving errors are simulated in the second and third scenarios, respectively. The time–space diagrams of the simulated trajectories are presented and explicitly analysed. It is demonstrated that the model is able to well replicate periodic traffic oscillations from the precursor stage to the decay stage. Without making any assumption, the fundamental diagrams for the simulated scenario coincide with the empirical fundamental diagrams. These all validate that the model can well reproduce the traffic characteristics contained by the field data. The nonparametric car-following model exhibits traffic dynamics in a simple and parsimonious manner.


      PubDate: 2015-07-27T13:31:47Z
       
  • Stochastic optimization approach for the car placement problem in
           ridesharing systems
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Joe Naoum-Sawaya, Randy Cogill, Bissan Ghaddar, Shravan Sajja, Robert Shorten, Nicole Taheri, Pierpaolo Tommasi, Rudi Verago, Fabian Wirth
      With the increasing fuel prices and the pressure towards greener modes of transportation, ridesharing has emerged as an alternative to private car ownership and public transportation. In this paper, we focus on a common destination ridesharing system which is of interest in large organizations such as companies and government offices. Particularly, such organizations are looking at using company owned vehicles to offer a ridesharing service by which employees carpool to work thus leading to several benefits that include decreasing pressure on on-campus parking spaces, lowering localized on-campus congestion, in addition to offering a greener transportation mode while lowering transportation costs for employees. Based on discussions with our industry partners, optimizing the distribution of limited number of company vehicles while insuring robustness against unlikely vehicle unavailability is of critical importance. Thus in this paper, we present a stochastic mixed integer programming model to optimize the allocation of shared vehicles to employees while taking into account the unforeseen event of vehicle unavailability which would require some participants to take own vehicles or rerouting of existing vehicles. Since solving the proposed model to optimality is computationally challenging for problems of large sizes, we also propose a heuristic that is capable of finding good quality solutions in limited computational time. The proposed model and heuristic are tested on several instances of varying sizes showing the computational performance. Finally, a test case based on the city of Rome, Italy is presented and insights related to vehicle distribution and travel time savings are discussed.


      PubDate: 2015-07-27T13:31:47Z
       
  • Fine-grained OD estimation with automated zoning and sparsity
           regularisation
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Aditya Krishna Menon, Chen Cai, Weihong Wang, Tao Wen, Fang Chen
      Given a road network, a fundamental object of interest is the matrix of origin destination (OD) flows. Estimation of this matrix involves at least three sub-problems: (i) determining a suitable set of traffic analysis zones, (ii) the formulation of an optimisation problem to determine the OD matrix, and (iii) a means of evaluating a candidate estimate of the OD matrix. This paper describes a means of addressing each of these concerns. We propose to automatically uncover a suitable set of traffic analysis zones based on observed link flows. We then employ regularisation to encourage the estimation of a sparse OD matrix. We finally propose to evaluate a candidate OD matrix based on its predictive power on held out link flows. Analysis of our approach on a real-world transport network reveals that it discovers automated zones that accurately capture regions of interest in the network, and a corresponding OD matrix that accurately predicts observed link flows.


      PubDate: 2015-07-27T13:31:47Z
       
  • Implicit choice set generation in discrete choice models: Application to
           household auto ownership decisions
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Rajesh Paleti
      Latent choice set models that account for probabilistic consideration of choice alternatives during decision making have long existed. The Manski model that assumes a two-stage representation of decision making has served as the standard workhorse model for discrete choice modeling with latent choice sets. However, estimation of the Manski model is not always feasible because evaluation of the likelihood function in the Manski model requires enumeration of all possible choice sets leading to explosion for moderate and large choice sets. In this study, we propose a new group of implicit choice set generation models that can approximate the Manski model while retaining linear complexity with respect to the choice set size. We examined the performance of the models proposed in this study using synthetic data. The simulation results indicate that the approximations proposed in this study perform considerably well in terms of replicating the Manski model parameters. We subsequently used these implicit choice set models to understand latent choice set considerations in household auto ownership decisions of resident population in the Southern California region. The empirical results confirm our hypothesis that certain segments of households may only consider a subset of auto ownership levels while making decisions regarding the number of cars to own. The results not only underscore the importance of using latent choice models for modeling household auto ownership decisions but also demonstrate the applicability of the approximations proposed in this study to estimate these latent choice set models.


      PubDate: 2015-07-19T11:10:04Z
       
  • Decomposition of general facility disruption correlations via augmentation
           of virtual supporting stations
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Siyang Xie , Xiaopeng Li , Yanfeng Ouyang
      Infrastructure facilities may be subject to probabilistic disruptions that compromise individual facility functionality as well as overall system performance. Disruptions of distributed facilities often exhibit complex spatial correlations, and thus it is difficult to describe them with succinct mathematical models. This paper proposes a new methodological framework for analyzing and modeling facility disruptions with general correlations. This framework first proposes pairwise transformations that unify three probabilistic representations (i.e., based on conditional, marginal, and scenario probabilities) of generally correlated disruption profile among multiple distributed facilities. Then facilities with any of these disruption profile representations can be augmented into an equivalent network structure consisting of additional supporting stations that experience only independent failures. This decomposition scheme largely reduces the complexity associated with system evaluation and optimization. We prove analytical properties of the transformations and the decomposition scheme, and illustrate the proposed methodological framework using a set of numerical case studies and sensitivity analyses. Managerial insights are also drawn.


      PubDate: 2015-07-15T08:25:00Z
       
  • Exploring trade-offs in frequency allocation in a transit network using
           bus route patterns: Methodology and application to large-scale urban
           systems
    • Abstract: Publication date: Available online 10 July 2015
      Source:Transportation Research Part B: Methodological
      Author(s): İ. Ömer Verbas , Hani S. Mahmassani
      Transit agencies seek to allocate their limited operational budget and fleet optimally to service routes in order to maximize user benefits. The Transit Network Frequency Setting Problem formulation developed in this study effectively captures the coupling between the routes and their prevailing patterns, which may have different subsets of stops visited at different times of the day. The number of riders is elastic to the prevailing number of bus trips at a given stop, which is the combination of different pattern dispatch frequencies. As a result, the study bridges the gap between the operator’s perspective where the decision unit is the pattern schedule, and the user’s perspective, which perceives frequencies at the route level. Two main formulations are introduced. The first one maximizes the number of riders and the total waiting time savings under budget, fleet, policy headway and bus loading constraints; the second minimizes the net cost under fleet, policy headway, bus loading, minimum ridership and minimum waiting time savings constraints. In both formulations, pattern headways are the decision variables. Spatial and temporal heterogeneity of ridership elasticity with respect to headway is captured. The formulations are applied to a large-scale test network for the Chicago area. The results show that a win–win solution is possible where both ridership and waiting time savings are increased, while the net cost is decreased.


      PubDate: 2015-07-15T08:25:00Z
       
  • An extended coordinate descent method for distributed anticipatory network
           traffic control
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Marco Rinaldi , Chris M.J. Tampère
      Anticipatory optimal network control can be defined as the practice of determining the set of control actions that minimizes a network-wide objective function, so that the consequences of this action are taken in consideration not only locally, on the propagation of flows, but globally, taking into account the user’s routing behavior. Such an objective function is, in general, defined and optimized in a centralized setting, as knowledge regarding the whole network is needed in order to correctly compute it. This is a strong theoretical framework but, in practice, reaching a level of centralization sufficient to achieve said optimality is very challenging. Furthermore, even if centralization was possible, it would exhibit several shortcomings, with concerns such as computational speed (centralized optimization of a huge control set with a highly nonlinear objective function), reliability and communication overhead arising. The main aim of this work is to develop a decomposed heuristic descent algorithm that, demanding the different control entities to share the same information set, attains network-wide optimality through separate control actions.


      PubDate: 2015-07-15T08:25:00Z
       
  • Trajectory data reconstruction and simulation-based validation against
           macroscopic traffic patterns
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Marcello Montanino , Vincenzo Punzo
      This paper shows that the behavior of driver models, either individually or entangled in stochastic traffic simulation, is affected by the accuracy of empirical vehicle trajectories. To this aim, a “traffic-informed” methodology is proposed to restore physical and platoon integrity of trajectories in a finite time–space domain, and it is applied to one NGSIM I80 dataset. However, as the actual trajectories are unknown, it is not possible to verify directly whether the reconstructed trajectories are really “nearer” to the actual unknowns than the original measurements. Therefore, a simulation-based validation framework is proposed, that is also able to verify indirectly the efficacy of the reconstruction methodology. The framework exploits the main feature of NGSIM-like data that is the concurrent view of individual driving behaviors and emerging macroscopic traffic patterns. It allows showing that, at the scale of individual models, the accuracy of trajectories affects the distribution and the correlation structure of lane-changing model parameters (i.e. drivers heterogeneity), while it has very little impact on car-following calibration. At the scale of traffic simulation, when models interact in trace-driven simulation of the I80 scenario (multi-lane heterogeneous traffic), their ability to reproduce the observed macroscopic congested patterns is sensibly higher when model parameters from reconstructed trajectories are applied. These results are mainly due to lane changing, and are also the sought indirect validation of the proposed data reconstruction methodology.


      PubDate: 2015-07-15T08:25:00Z
       
  • Compound Gamma representation for modeling travel time variability in a
           traffic network
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Jiwon Kim , Hani S. Mahmassani
      This paper proposes a compound probability distribution approach for capturing both vehicle-to-vehicle and day-to-day variability in modeling travel time reliability in a network. Starting from the observation that standard deviation and mean of distance-normalized travel time in a network are highly positively correlated and their relationship is well characterized by a linear function, this study assumes multiplicative error structures to describe data with such characteristics and derives a compound distribution to model travel delay per unit distance as a surrogate for travel time. The proposed Gamma–Gamma model arises when (within-day) vehicle-to-vehicle travel delay per unit distance is distributed according to a Gamma distribution, with mean that itself fluctuates from day to day following another Gamma distribution. The study calibrates the model parameters and validates the underlying assumptions using both simulated and actual vehicle trajectory data. The Gamma–Gamma distribution shows good fits to travel delay observations when compared to the (simple) Gamma and Lognormal distributions. The main advantage of the Gamma–Gamma model is its ability to recognize different variability dimensions reflected in travel time data and clear physical meanings of its parameters in connection with vehicle-to-vehicle and day-to-day variability. Based on the linearity assumption for the relationship between mean and standard deviation, two shape parameters of the Gamma–Gamma model are linked to the coefficient of variation of travel delay in vehicle-to-vehicle and day-to-day distributions, respectively, and can be directly estimated from the slope of the associated mean-standard deviation plots. An extension of the basic model form was also introduced to address potential deviations from this linearity assumption. The extended Gamma–Gamma model can account for time-of-day variations in mean-standard deviation relationships—such as hysteresis patterns observed in mean and day-to-day variation in travel time—and incorporate such dynamics in travel time distribution modeling. In summary, the model provides a systematic way of quantifying, comparing, and assessing different types of variability, which is important in understanding travel time characteristics and evaluating various transportation measures that affect reliability.


      PubDate: 2015-07-09T20:49:54Z
       
  • Stochastic capacity expansion models for airport facilities
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Yanshuo Sun , Paul Schonfeld
      It is important and also challenging to plan airport facilities to meet future traffic needs in a rapidly changing environment, which is characterized by various uncertainties. One key issue in airport facility development is that facility performance functions (delay levels as functions of capacity utilization rates) are nonlinear, which complicates the solution method design. Potential demand fluctuations in a deregulated aviation market add another dimension to the decision making process. To solve this problem, a deterministic total cost minimization model is proposed and then extended into stochastic programs, by including uncertainties in traffic forecasts. After the exploration of properties of the delay cost function, an Outer-Approximation (OA) technique which is superior to the existing discrete approximation is designed. After model enhancements, an efficient solution framework based on the OA technique is used to solve the model to its global optimality by interactively generating upper and lower bounds to the objective. Computational tests demonstrate the validity of developed models and efficiency of proposed algorithms. The total cost is reduced by 18.8% with the stochastic program in the numerical example.


      PubDate: 2015-07-05T12:59:12Z
       
  • A scalable non-myopic dynamic dial-a-ride and pricing problem
    • Abstract: Publication date: Available online 2 July 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Hamid R. Sayarshad , Joseph Y.J. Chow
      Non-myopic dial-a-ride problem and other related dynamic vehicle routing problems often ignore the need for non-myopic pricing under the assumption of elastic demand, which leads to an overestimation of the benefits in level of service and resulting inefficiencies. To correct this problem, a new dynamic dial-a-ride policy is introduced, one that features non-myopic pricing based on optimal tolling of queues to fit with the multi-server queueing approximation method proposed by Hyttiä et al. (2012) for large-scale systems. By including social optimal pricing, the social welfare of the resulting system outperforms the marginal pricing assumed for previous approaches over a range of test instances. In the examples tested, improvements in social welfare of the non-myopic pricing over the myopic pricing were in the 20–31% range. For a given demand function, we can derive the optimal fleet size to maximize social welfare. Sensitivity tests to the optimal price confirm that it leads to an optimal social welfare while the marginal pricing policy does not. A comparison of single passenger taxis to shared-taxis shows that system cost may reduce at the expense of decreased social welfare, which agrees with the results of Jung et al. (2013).


      PubDate: 2015-07-05T12:59:12Z
       
  • Trip pricing of one-way station-based carsharing networks with zone and
           time of day price variations
    • Abstract: Publication date: Available online 2 July 2015
      Source:Transportation Research Part B: Methodological
      Author(s): Diana Jorge , Goran Molnar , Gonçalo Homem de Almeida Correia
      One-way station-based carsharing systems provide short term car rentals in which users can take a car from the initial station and return it to any other station. They are more flexible than round-trip carsharing, where the vehicle can only be returned to the station where it was picked up, and can be used for daily commuting trips as well. This flexibility, however, comes at a cost of vehicle stock imbalance within the network. Several solutions and strategies have been suggested to counter this problem, one of which is variable trip pricing. By charging high prices for the trips that increase imbalance and lowering prices for trips that help improve the balance, it has been hypothesized, but never demonstrated, that the clients’ behavior could be used to balance the vehicle stocks and thus make carsharing systems more manageable and profitable. In this paper, we develop a mixed integer non-linear programming (MINLP) model, defined as the Trip Pricing Problem for One-Way Carsharing Systems (TPPOCS), which sets these prices in order to maximize profit. An iterated local search (ILS) metaheuristic is proposed for solving it. The method is applied to the theoretical case-study of a network of 75 stations distributed across the city of Lisbon (Portugal). Although the implemented metaheuristic is tuned for the Lisbon example, the generic nature of its operators makes the model applicable elsewhere. The results demonstrate that the trip pricing strategy can be used to increase profit through a more balanced system. If no price-based balancing strategies are applied, operating this service results in a daily deficit of €1161. When the trip pricing policy is applied, profits of 2068 €/day are possible. The optimal prices are on average 23% higher than the base price, and 18% less demand is served, but the enhanced performance leads to lower expenses with the fleet of vehicles and number of parking spaces.


      PubDate: 2015-07-05T12:59:12Z
       
  • A mixed integer programming model for optimizing multi-level operations
           process in railroad yards
    • Abstract: Publication date: October 2015
      Source:Transportation Research Part B: Methodological, Volume 80
      Author(s): Tie Shi , Xuesong Zhou
      A typical railroad hump yard contains multiple layers of complex operations. The railcars coming with inbound trains through the yard need to be humped into different classification tracks according to the destination, and then assembled to generate the desired outbound trains. During this complex procedure, the processing time of railcars and various resource constraints at different railroad yard facilities could significantly affect the overall performance of yard operations, individually and in combination. It is theoretically challenging to represent a large number of practical operation rules through tractable mathematical programming models. This paper first presents a time-expanded multi-layer network flow model to describe the connection between different layers of yard operations. A mixed integer programming model is developed to optimize the overall performance by jointly considering tightly interconnected facilities. We adopt a cumulative flow count representation to model the spatial capacity constraints in terms of the number of railcars in classification yards. A novel lot-sizing modeling framework and related valid inequality formulations are introduced to model the assembling jobs for outbound trains. We also develop an aggregated flow assignment model and earliest due date-based heuristic rules to determine the humping jobs sequence for reducing the search space. Numerical experiments are conducted to examine the solution quality and computational efficiency under different types of formulation strategies.


      PubDate: 2015-07-05T12:59:12Z
       
  • Reformulating the Hoogendoorn–Bovy predictive dynamic user-optimal
           model in continuum space with anisotropic condition
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Jie Du , S.C. Wong , Chi-Wang Shu , Mengping Zhang
      Hoogendoorn and Bovy (2004) developed an approach for a pedestrian user-optimal dynamic assignment in continuous time and space. Although their model was proposed for pedestrian traffic, it can also be applied to urban cities. The model is very general, and consists of a conservation law (CL) and a Hamilton–Jacobi–Bellman (HJB) equation that contains a minimum value problem. However, only an isotropic application example was given in their paper. We claim that the HJB equation is difficult to compute numerically in an anisotropic case. To overcome this, we reformulate their model for a dense urban city that is arbitrary in shape and has multiple central business districts (CBDs). In our model, the minimum value problem is only used in the CL portion, and the HJB equation reduces to a Hamilton–Jacobi (HJ) equation for easier computation. The dynamic path equilibrium of our model is proven in a different way from theirs, and a numerical algorithm is also provided to solve the model. Finally, we show two numerical examples under the anisotropic case and compare the results with those of the isotropic case.


      PubDate: 2015-07-01T02:41:17Z
       
  • A comprehensive dwelling unit choice model accommodating psychological
           constructs within a search strategy for consideration set formation
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Chandra R. Bhat
      This study adopts a dwelling unit level of analysis and considers a probabilistic choice set generation approach for residential choice modeling. In doing so, we accommodate the fact that housing choices involve both characteristics of the dwelling unit and its location, while also mimicking the search process that underlies housing decisions. In particular, we model a complete range of dwelling unit choices that include tenure type (rent or own), housing type (single family detached, single family attached, or apartment complex), number of bedrooms, number of bathrooms, number of storeys (one or multiple), square footage of the house, lot size, housing costs, density of residential neighborhood, and commute distance. Bhat’s (2015) generalized heterogeneous data model (GHDM) system is used to accommodate the different types of dependent outcomes associated with housing choices, while capturing jointness caused by unobserved factors. The proposed analytic framework is applied to study housing choices using data derived from the 2009 American Housing Survey (AHS), sponsored by the Department of Housing and Urban Development (HUD) and conducted by the U.S. Census Bureau. The results confirm the jointness in housing choices, and indicate the superiority of a choice set formation model relative to a model that assumes the availability of all dwelling unit alternatives in the choice set.


      PubDate: 2015-07-01T02:41:17Z
       
  • Traffic user equilibrium and proportionality
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Marlies Borchers , Paul Breeuwsma , Walter Kern , Jaap Slootbeek , Georg Still , Wouter Tibben
      We discuss the problem of proportionality and uniqueness for route flows in the classical traffic user equilibrium model. It is well-known that under appropriate assumptions the user equilibrium ( f , x ) is unique in the link flow x but typically not in the route flow f. We consider the concept of proportionality in detail and re-discuss the well-known relation between the so-called bypass proportionality and entropy maximization. We exhibit special proportionality conditions which uniquely determine the route flow f. The results are illustrated with some simple example networks.


      PubDate: 2015-07-01T02:41:17Z
       
  • A set-covering model for a bidirectional multi-shift full truckload
           vehicle routing problem
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Ruibin Bai , Ning Xue , Jianjun Chen , Gethin Wyn Roberts
      This paper introduces a bidirectional multi-shift full truckload transportation problem with operation dependent service times. The problem is different from the previous container transport problems and the existing approaches for container transport problems and vehicle routing pickup and delivery are either not suitable or inefficient. In this paper, a set covering model is developed for the problem based on a novel route representation and a container-flow mapping. It was demonstrated that the model can be applied to solve real-life, medium sized instances of the container transport problem at a large international port. A lower bound of the problem is also obtained by relaxing the time window constraints to the nearest shifts and transforming the problem into a service network design problem. Implications and managerial insights of the results by the lower bound results are also provided.


      PubDate: 2015-07-01T02:41:17Z
       
  • Coordinated online in-vehicle routing balancing user optimality and system
           optimality through information perturbation
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Lili Du , Lanshan Han , Shuwei Chen
      The inconsistence between system optimality and user optimality represents one of the key difficulties on network traffic congestion control. The advanced connected vehicle systems, enabling smart vehicles to possess/exchange real-time information and conduct portable computation, provide new opportunities to address this challenge. Motivated by this view, this study proposes a coordinated online in-vehicle routing mechanism with intentional information provision perturbation (CRM-IP), which seeks to shape individual vehicles online routing decisions so that user optimality and system optimality are balanced, by exploiting bounded rationality of the users. The proposed CRM-IP is modeled as a pure strategy atomic routing game, and implemented by a sequentially updating distributed algorithm. The mathematical analysis is conducted to quantify the absolute gain of system optimality corresponding to the loss of user optimality resulting from a given level of the information perturbation in the worst case so that the efficiency of the information perturbation can be evaluated. Furthermore, numerical experiments conducted based on City of Sioux Falls network investigate the average effects of the CRM-IP on system optimality and user optimality under various network traffic conditions, comparing to the CRM developed by Du et al. (in press). The results indicate that the improvement of system optimality and the reduction of individual vehicles’ travel time from the CRM is more significant when the network traffic is under an mild congestion state, such as under the levels of service (LOS’s) C, D, and E, rather than under extremely sparse or congested states, such as under LOS’s A and B, or F. Moreover, higher level of information perturbation benefits system optimality more, but the marginal effect decreases after the perturbation reaching certain level, such as λ = 0.1 in this case study. In addition, a portion of vehicles may sacrifice user optimality due to the information perturbation, but the extent of the sacrifice is not significant, even though it increases with the information perturbation level. Hence, a small information perturbation is recommended to achieve an efficient network traffic control through the CRM-IP. Overall, this study proposes the CRM-IP as an efficient routing mechanism, which has a great potential to guide the routing decisions of individual vehicles so that their collective behavior improve network performance in both system optimality and user optimality.


      PubDate: 2015-07-01T02:41:17Z
       
  • Estimating bike-share trips using station level data
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Cyrille Médard de Chardon , Geoffrey Caruso
      Bicycle sharing systems (BSS) have increased in number rapidly since 2007. The potential benefits of BSS, mainly sustainability, health and equity, have encouraged their adoption through support and promotion by mayors in Europe and North America alike. In most cases municipal governments desire their BSS to be successful and, with few exceptions, state them as being so. New technological improvements have dramatically simplified the use and enforcement of bicycle return, resulting in the widespread adoption of BSS. Unfortunately little evaluation of the effectiveness of differently distributed and managed BSS has taken place. Comparing BSS systems quantitatively is challenging due to the limited data made available. The metrics of success presented by municipalities are often too general or incomparable to others making relative evaluations of BSS success arduous. This paper presents multiple methodologies allowing the estimation of the number of daily trips, the most significant measure of BSS usage, based on data that is commonly available, the number of bicycles available at a station over time. Results provide model coefficients as well as trip count estimates for select cities. Of four spatial and temporal aggregate models the day level aggregation is found to be most effective for estimation. In addition to trip estimation this work provides a rigorous formalization of station level data and the ability to distinguish spatio-temporal rebalancing quantities as well as new characteristics of BSS station use.
      Graphical abstract image

      PubDate: 2015-06-25T02:29:12Z
       
  • Robust weekly aircraft maintenance routing problem and the extension to
           the tail assignment problem
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Zhe Liang , Yuan Feng , Xiaoning Zhang , Tao Wu , Wanpracha Art Chaovalitwongse
      In this paper, we study two closely related airline planning problems: the robust weekly aircraft maintenance routing problem (RWAMRP) and the tail assignment problem (TAP). In real life operations, the RWAMRP solution is used in tactical planning whereas the TAP solution is implemented in operational planning. The main objective of these two problems is to minimize the total expected propagated delay (EPD) of the aircraft routes. To formulate the RWAMRP, we propose a novel weekly line-of-flights (LOF) network model that can handle complex and nonlinear cost functions of EPD. Because the number of LOFs grows exponentially with the number of flights to be scheduled, we propose a two-stage column generation approach to efficiently solve large-scale real-life RWAMRPs. Because the EPD of an LOF is highly nonlinear and can be very time-consuming to accurately compute, we propose three lower bounds on the EPD to solve the pricing subproblem of the column generation. Our approach is tested on eight real-life test instances. The computational results show that the proposed approach provides very tight LP relaxation (within 0.6% of optimal solutions) and solves the test case with more than 6000 flights per week in less than three hours. We also investigate the solutions obtained by our approach over 500 simulated realizations. The simulation results demonstrate that, in all eight test instances, our solutions result in less EPDs than those obtained from traditional methods. We then extend our model and solution approach to solve realistically simulated TAP instances.


      PubDate: 2015-06-25T02:29:12Z
       
  • Accounting for stochastic variables in discrete choice models
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Federico Díaz , Víctor Cantillo , Julian Arellana , Juan de Dios Ortúzar
      The estimation of discrete choice models requires measuring the attributes describing the alternatives within each individual’s choice set. Even though some attributes are intrinsically stochastic (e.g. travel times) or are subject to non-negligible measurement errors (e.g. waiting times), they are usually assumed fixed and deterministic. Indeed, even an accurate measurement can be biased as it might differ from the original (experienced) value perceived by the individual. Experimental evidence suggests that discrepancies between the values measured by the modeller and experienced by the individuals can lead to incorrect parameter estimates. On the other hand, there is an important trade-off between data quality and collection costs. This paper explores the inclusion of stochastic variables in discrete choice models through an econometric analysis that allows identifying the most suitable specifications. Various model specifications were experimentally tested using synthetic data; comparisons included tests for unbiased parameter estimation and computation of marginal rates of substitution. Model specifications were also tested using a real case databank featuring two travel time measurements, associated with different levels of accuracy. Results show that in most cases an error components model can effectively deal with stochastic variables. A random coefficients model can only effectively deal with stochastic variables when their randomness is directly proportional to the value of the attribute. Another interesting result is the presence of confounding effects that are very difficult, if not impossible, to isolate when more flexible models are used to capture stochastic variations. Due the presence of confounding effects when estimating flexible models, the estimated parameters should be carefully analysed to avoid misinterpretations. Also, as in previous misspecification tests reported in the literature, the Multinomial Logit model proves to be quite robust for estimating marginal rates of substitution, especially when models are estimated with large samples.


      PubDate: 2015-06-25T02:29:12Z
       
  • Port investments on coastal and marine disasters prevention: Economic
           modeling and implications
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Yi-bin Xiao , Xiaowen Fu , Adolf K.Y. Ng , Anming Zhang
      Located along shorelines, seaports are highly vulnerable to coastal and marine natural disasters largely due to climate change. Damage caused by disasters can be prevented or alleviated if sufficient investments are made in a timely manner. However, despite a wide range of investment options and well-developed engineering expertise, port investment on disaster prevention remains a challenging task involving great complexities. This paper develops an integrated economic model for the analysis of disaster-prevention investments at a “landlord” port. It simultaneously considers the uncertainty of disaster occurrence and associated return of prevention investments, the information accumulation and related investment timing, and the benefit spillovers of investment among stakeholders. Our analysis shows that the timing of port investments depends on the probability of disasters. Immediate investment is optimal for disasters with very high probability, while investment should be postponed if such a probability is very low. Optimal timing for cases of intermediate probability cannot be determined analytically, as it is influenced by other factors such as discount rate, information accumulation and efficiency of investments. Positive spillovers between a port and its tenants lead to under-investment, which can be corrected by coordination between stakeholders. However, since there are risks of “overinvestment” (the marginal benefits of investments are zero ex post if there is no disaster), regulatory intervention is not always optimal when the regulator does not have a good understanding of disaster probability distribution. Therefore, scientific research would bring significant economic and strategic value to policy, planning and investment decisions.


      PubDate: 2015-06-25T02:29:12Z
       
  • Applying variational theory to travel time estimation on urban arterials
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Etienne Hans , Nicolas Chiabaut , Ludovic Leclercq
      The Variational Theory (VT) expresses the LWR model as a least cost path problem. Recent researches have shown that this problem can be simply applied on a graph with a minimal number of nodes and edges when the fundamental diagram is triangular (sufficient variational graph – SVG). Such a graph accounts for traffic signal settings on an urban arterial and leads to mean traffic states for the total arterial in free-flow or congested stationary conditions. The Macroscopic Fundamental Diagram (MFD) can then be directly estimated. In this paper, we extend this method to provide the complete distribution of deterministic travel times observed on an arterial. First, we will show how to obtain a tight estimation of the arterial capacity by properly identifying the most constraining part of the SVG. Then, we will show that a modified version of the SVG allows the exact calculation of the cumulative count curves at the entry and exit of an arterial. It is finally possible to derive the full travel time distributions for any dynamic conditions.
      Graphical abstract image

      PubDate: 2015-06-25T02:29:12Z
       
  • Real-time high-speed train rescheduling in case of a complete blockage
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Shuguang Zhan , Leo G. Kroon , Lucas P. Veelenturf , Joris C. Wagenaar
      This paper focuses on real-time rescheduling of railway traffic on a high speed railway line in case of a complete blockage of the railway infrastructure. Due to the disruption, all tracks in a railway segment are out of order for a certain period of time. In the situation that we consider, trains that are blocked by the disruption do not return to their origin by taking over train services in the opposite direction, but wait inside the stations until the disruption is over. Thus the main decisions to be taken are the following: in which stations do trains have to wait, in which order do they have to leave when the disruption is over, and which trains have to be canceled? A Mixed Integer Programming model is formulated to minimize the total weighted train delay and the number of canceled trains, while adhering to headway and station capacity constraints. Most instances can be solved in a single optimization run, but for the most complex instances we propose a two-stage optimization approach to improve the computational efficiency. The model is tested on real-world instances of the Beijing–Shanghai high speed railway line. The results show that the model is promising for reducing the effect of a disruption on passenger service, especially in comparison with a heuristic method used in practice.


      PubDate: 2015-06-25T02:29:12Z
       
  • A time-dependent freight tour synthesis model
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Iván Sánchez-Díaz , José Holguín-Veras , Xuegang (Jeff) Ban
      This paper introduces a model of urban freight demand that seeks to estimate tour flows from secondary data sources e.g., traffic counts, to bypass the need for expensive surveys. The model discussed in this paper, referred as Freight Tour Synthesis (FTS), enhances current techniques by incorporating the time-dependent tour-based behavior of freight vehicles, and the decision maker’s (e.g., metropolitan planning agency planner) preferences for different sources of information. The model, based on entropy maximization theory, estimates the most likely set of tour flows, given a set of freight trip generation estimates, a set of traffic counts per time interval, and total freight transportation cost in the network. The type of inputs used allows the assessment of changes in infrastructure, policy and land use. The ability of the model to replicate actual values is assessed using the Denver Region (CO) as a case study.


      PubDate: 2015-06-25T02:29:12Z
       
  • A piecewise-constant congestion taxing policy for repeated routing games
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Farhad Farokhi , Karl H. Johansson
      In this paper, we consider repeated routing games with piecewise-constant congestion taxing in which a central planner sets and announces the congestion taxes for fixed windows of time in advance. Specifically, congestion taxes are calculated using marginal congestion pricing based on the flow of the vehicles on each road prior to the beginning of the taxing window (and, hence, there is a time-varying delay in setting the congestion taxes). We motivate the piecewise-constant taxing policy by that users or drivers may dislike fast-changing prices and that they also prefer prior knowledge of the prices. We prove for this model that the multiplicative update rule and the discretized replicator dynamics converge to a socially optimal flow when using vanishing step sizes. Considering that the algorithm cannot adapt itself to a changing environment when using vanishing step sizes, we propose adopting constant step sizes in this case. Then, however, we can only prove the convergence of the dynamics to a neighborhood of the socially optimal flow (with the size of the neighbourhood being of the order of the selected step size). The results are illustrated on a nonlinear version of Pigou’s famous routing game.


      PubDate: 2015-06-25T02:29:12Z
       
  • Analysis of real-time control strategies in a corridor with multiple bus
           services
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Daniel Hernández , Juan Carlos Muñoz , Ricardo Giesen , Felipe Delgado
      Control strategies have been widely used in the literature to counteract the effects of bus bunching in passenger‘s waiting times and its variability. These strategies have only been studied for the case of a single bus line in a corridor. However, in many real cases this assumption does not hold. Indeed, there are many transit corridors with multiple bus lines interacting, and this interaction affects the efficiency of the implemented control mechanism. This work develops an optimization model capable of executing a control scheme based on holding strategy for a corridor with multiple bus lines. We analyzed the benefits in the level of service of the public transport system when considering a central operator who wants to maximize the level of service for users of all the bus lines, versus scenarios where each bus line operates independently. A simulation was carried out considering two medium frequency bus lines that serve a set of stops and where these two bus lines coexist in a given subset of stops. In the simulation we compared the existence of a central operator, using the optimization model we developed, against the independent operation of each line. In the simulations the central operator showed a greater reduction in the overall waiting time of the passengers of 55% compared to a no control scenario. It also provided a balanced load of the buses along the corridor, and a lower variability of the bus headways in the subset of stops where the lines coexist, thus obtaining better reliability for all types of passengers present in the public transport system.


      PubDate: 2015-06-25T02:29:12Z
       
  • A joint bottom-up solution methodology for system-level pavement
           rehabilitation and reconstruction
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Jinwoo Lee , Samer Madanat
      We present a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. The proposed bottom-up approach adopts an augmented condition state to account for the history-dependent properties of pavement deterioration, and solves for steady-state policies for an infinite horizon. Genetic algorithms (GAs) are implemented in the system-level optimization based on segment-specific optimization results. The complexity of the proposed algorithm is polynomial in the size of the system and the policy-related parameters. We provide graphical presentations of the optimal solutions for various budget situations. As a case study, a subset of California’s highway system is analyzed. The case study results demonstrate the economic benefit of a combined rehabilitation and reconstruction budget compared to separate budgets.


      PubDate: 2015-06-25T02:29:12Z
       
  • Empirical flow-density and speed-spacing relationships: Evidence of
           vehicle length dependency
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Benjamin Coifman
      Traffic flow theory has come to a point where conventional, fixed time averaged data are limiting our insight into critical behavior both at the macroscopic and microscopic scales. This paper develops a methodology to measure relationships of density and vehicle spacing on freeways. These relationships are central to most traffic flow theories but have historically been difficult to measure empirically. The work leads to macroscopic flow-density and microscopic speed-spacing relationships in the congested regime derived entirely from dual loop detector data and then verified against the NGSIM data set. The methodology eliminates the need to seek out stationary conditions and yields clean relationships that do not depend on prior assumptions of the curve shape before fitting the data. Upon review of the clean empirical relationships a key finding of this work is the fact that many of the critical parameters of the macroscopic flow-density and microscopic speed-spacing relationships depend on vehicle length, e.g., upstream moving waves should travel through long vehicles faster than through short vehicles. Thus, the commonly used assumption of a homogeneous vehicle fleet likely obscures these important phenomena. More broadly, if waves travel faster or slower depending on the length of the vehicles through which the waves pass, then the way traffic is modeled should be updated to explicitly account for inhomogeneous vehicle lengths.


      PubDate: 2015-06-25T02:29:12Z
       
  • A two-stage robustness approach to evacuation planning with buses
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Marc Goerigk , Kaouthar Deghdak , Vincent T’Kindt
      We consider the problem of scheduling a bus fleet to evacuate persons from an endangered region. As most of the planning data is subject to uncertainty, we develop a two-stage bicriteria robust formulation, which considers both the evacuation time, and the vulnerability of the schedule to changing evacuation circumstances. As the resulting integer program is too large to be solved directly using an off-the-shelf solver, we develop a scenario-generation algorithm which iteratively adds new scenarios to the incumbent subproblem being solved. Computational experiments show that this approach is fast enough to solve a realistic instance corresponding to an evacuation case within the city of Kaiserslautern (Germany).


      PubDate: 2015-06-25T02:29:12Z
       
  • A tractable two-stage robust winner determination model for truckload
           service procurement via combinatorial auctions
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Bo Zhang , Tao Yao , Terry L. Friesz , Yuqi Sun
      A combinatorial auction is one of the adopted mechanisms for truckload (TL) service procurement. In such an auction, the shipper faces a well-known winner determination problem (WDP): the shipper, as the auctioneer, is given bids submitted by a group of carriers. In most literature, WDP is modeled as a deterministic mixed-integer program (MIP) and is solved by standard MIP algorithms. However, in practice, the exact shipping demand is unavailable until after the auction. This shipment volume uncertainty has a significant impact on the solution to WDP. Therefore, a deterministic winner determination model with an estimate of shipment volume may not provide solutions that attain low procurement costs. This paper proposes a new tractable two-stage robust optimization (RO) approach to solve WDP for TL service procurement under shipment volume uncertainty. Assuming that only historical data is available, we propose a data-driven approach based on the central limit theorem (CLT) to construct polyhedral uncertainty sets. In particular, we consider two random cases: independent shipment volume and correlated shipment volume. A two-stage RO model with integer first-stage decision variables and continuous recourse variables is then formulated. We develop a reformulation solution method and use numerical tests to demonstrate that it is much more computationally efficient than the widely adopted Benders’ type constraint generation algorithm. We demonstrate by numerical tests that real-world sized instances of TL service procurement problems can be solved by our proposed robust method. Moreover, we compare our robust approach with benchmark and show that it is more tractable and robust to uncertainty.


      PubDate: 2015-06-25T02:29:12Z
       
  • From behavioral psychology to acceleration modeling: Calibration,
           validation, and exploration of drivers’ cognitive and safety
           parameters in a risk-taking environment
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Samer H. Hamdar , Hani S. Mahmassani , Martin Treiber
      We investigate a utility-based approach for driver car-following behavioral modeling while analyzing different aspects of the model characteristics especially in terms of capturing different fundamental diagram regions and safety proxy indices. The adopted model came from an elementary thought where drivers associate subjective utilities for accelerations (i.e. gain in travel times) and subjective dis-utilities for decelerations (i.e. loss in travel time) with a perceived probability of being involved in rear-end collision crashes. Following the testing of the model general structure, the authors translate the corresponding behavioral psychology theory – prospect theory – into an efficient microscopic traffic modeling with more elaborate stochastic characteristics considered in a risk-taking environment. After model formulation, we explore different model disaggregate and aggregate characteristics making sure that fidelity is kept in terms of equilibrium properties. Significant effort is then dedicated to calibrating and validating the model using microscopic trajectory data. A modified genetic algorithm is adopted for this purpose while focusing on capturing inter-driver heterogeneity for each of the parameters. Using the calibration exercise as a starting point, simulation sensitivity analysis is performed to reproduce different fundamental diagram regions and to explore rear-end collisions related properties. In terms of fundamental diagram regions, the model in hand is able to capture traffic breakdowns and different instabilities in the congested region represented by flow-density data points scattering. In terms of incident related measures, the effect of heterogeneity in both psychological factors and execution/perception errors on the accidents number and their distribution is studied. Through sensitivity analysis, correlations between the crash-penalty, the negative coefficient associated with losses in speed, the positive coefficient associated with gains in speed, the driver’s uncertainty, the anticipation time and the reaction time are retrieved. The formulated model offers a better understanding of driving behavior, particularly under extreme/incident conditions.


      PubDate: 2015-06-25T02:29:12Z
       
  • Editorial Board
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78




      PubDate: 2015-06-25T02:29:12Z
       
  • Infrastructure deployment under uncertainties and competition: The biofuel
           industry case
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Xin Wang , Michael K. Lim , Yanfeng Ouyang
      Technological paradigm shifts often come with a newly emerging industry that seeks a viable infrastructure deployment plan to compete against established competitors. Such phenomenon has been repeatedly seen in the field of transportation systems, such as those related to the booming bioenergy production, among others. We develop a game-theoretic modeling framework using a continuum approximation scheme to address the impacts of competition on the optimal infrastructure deployment. Furthermore, we extend the model to incorporate uncertainties in supply/demand and the risk of facility disruptions. Analytical properties of the optimal infrastructure system are obtained, based on which fast numerical solution algorithms are developed. Several hypothetical problem instances are used to illustrate the effectiveness of the proposed algorithms and to quantify the impacts of various system parameters. A large-scale biofuel industry case study for the U.S. Midwest is conducted to obtain additional managerial insights.


      PubDate: 2015-06-25T02:29:12Z
       
  • The recoverable robust facility location problem
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Eduardo Álvarez-Miranda , Elena Fernández , Ivana Ljubić
      This work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second stage. In contrast to some related modeling approaches from the literature, this new recoverable robust model is more general in terms of the considered data uncertainty; it can address situations in which uncertainty may be present in any of the following four categories: provider-side uncertainty, receiver-side uncertainty, uncertainty in-between, and uncertainty with respect to the cost parameters. For this novel problem, a sophisticated branch-and-cut framework based on Benders decomposition is designed and complemented by several non-trivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zero-half cuts. Two large sets of instances that incorporate spatial and demographic information of countries such as Germany and US (transportation) and Bangladesh and the Philippines (disaster management) are introduced. They are used to analyze in detail the characteristics of the proposed model and the obtained solutions as well as the effectiveness, behavior and limitations of the designed algorithm.


      PubDate: 2015-06-25T02:29:12Z
       
  • A generalized queuing model and its solution properties
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Jia Li , H.M. Zhang
      Modeling queuing behavior is central to the analysis of transportation and other service systems. To date, several queuing models been developed, but analytical insights on their global properties are hard to obtain. This is because in most cases, queuing dynamics are formulated as differential or difference equations, with possible discontinuities in their solutions, making most conventional analytical tools inadequate. As a result, simulations are often used to study these models, and if not properly treated, negative flows could arise from the simulation near certain discontinuities. In this paper, we propose a continuous-time queuing model that captures generalized queuing dynamics, where bottleneck discharging capacity and demand can vary simultaneously. We provide insights on the global properties of this model, upon deriving its closed-form variational solutions. Rather than resorting to the usual Hamilton–Jacobi theory, our derivations are built on an intrinsic periodicity property of the general queuing dynamics combined with measure-theoretic analysis. This treatment allows us to obtain results with more complex boundary conditions and make further extensions. We demonstrate its applications and show its solution properties in queuing simulation and performance bounding. In particular, we provide graphical, iterative and linearized solution schemes, which are all devoid of the well-known negative flow issue associated with numerical solutions to the point queue model.


      PubDate: 2015-06-25T02:29:12Z
       
  • A new generalized heterogeneous data model (GHDM) to jointly model mixed
           types of dependent variables
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Chandra R. Bhat
      This paper formulates a generalized heterogeneous data model (GHDM) that jointly handles mixed types of dependent variables—including multiple nominal outcomes, multiple ordinal variables, and multiple count variables, as well as multiple continuous variables—by representing the covariance relationships among them through a reduced number of latent factors. Sufficiency conditions for identification of the GHDM parameters are presented. The maximum approximate composite marginal likelihood (MACML) method is proposed to estimate this jointly mixed model system. This estimation method provides computational time advantages since the dimensionality of integration in the likelihood function is independent of the number of latent factors. The study undertakes a simulation experiment within the virtual context of integrating residential location choice and travel behavior to evaluate the ability of the MACML approach to recover parameters. The simulation results show that the MACML approach effectively recovers underlying parameters, and also that ignoring the multi-dimensional nature of the relationship among mixed types of dependent variables can lead not only to inconsistent parameter estimation, but also have important implications for policy analysis.


      PubDate: 2015-06-25T02:29:12Z
       
  • Formulation, existence, and computation of boundedly rational dynamic user
           equilibrium with fixed or endogenous user tolerance
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Ke Han , W.Y. Szeto , Terry L. Friesz
      This paper analyzes dynamic user equilibrium (DUE) that incorporates the notion of boundedly rational (BR) user behavior in the selection of departure times and routes. Intrinsically, the boundedly rational dynamic user equilibrium (BR-DUE) model we present assumes that travelers do not always seek the least costly route-and-departure-time choice. Rather, their perception of travel cost is affected by an indifference band describing travelers’ tolerance of the difference between their experienced travel costs and the minimum travel cost. An extension of the BR-DUE problem is the so-called variable tolerance dynamic user equilibrium (VT-BR-DUE) wherein endogenously determined tolerances may depend not only on paths, but also on the established path departure rates. This paper presents a unified approach for modeling both BR-DUE and VT-BR-DUE, which makes significant contributions to the model formulation, analysis of existence, solution characterization, and numerical computation of such problems. The VT-BR-DUE problem, together with the BR-DUE problem as a special case, is formulated as a variational inequality. We provide a very general existence result for VT-BR-DUE and BR-DUE that relies on assumptions weaker than those required for normal DUE models. Moreover, a characterization of the solution set is provided based on rigorous topological analysis. Finally, three computational algorithms with convergence results are proposed based on the VI and DVI formulations. Numerical studies are conducted to assess the proposed algorithms in terms of solution quality, convergence, and computational efficiency.


      PubDate: 2015-06-25T02:29:12Z
       
  • Some insights into a sequential resource allocation mechanism for en route
           air traffic management
    • Abstract: Publication date: September 2015
      Source:Transportation Research Part B: Methodological, Volume 79
      Author(s): Amy Kim , Mark Hansen
      This paper presents a game theoretic model of a sequential capacity allocation process in a congestible transportation system. In this particular application, we investigate the governing principles at work in how airlines will time their requests for en route resources under capacity shortfalls and uncertain conditions, when flights are not able to take their preferred route at their preferred departure time slot due to the shortfalls. We examine a sequential “First Submitted First Assigned” (FSFA) capacity allocation process within an en route air traffic flow management (ATFM) program such as the Collaborative Trajectory Options Program (CTOP), which is a Federal Aviation Administration initiative that aims to manage en route capacity constraints brought on by inclement weather and capacity/demand imbalances. In the FSFA process, flights are assigned the best available routes and slots available at the time flight operators submit their preference requests during the planning period, in a sequential manner. Because flight operators compete with one another for resources, in such an allocation process they would be expected to make their requests as early as possible. However, because weather and traffic conditions – and therefore, the values of resources – can change significantly, flight operators may prefer to request resources later in the process rather than earlier. We use a game theoretic setup to understand how flight operators might tradeoff these conflicts and choose an optimal time to submit their preferences for their flights, as submission times are competitive responses by flight operators looking to maximize their benefits. We first develop a loss function that captures the expected utility of submitting preferences under uncertainty about operating conditions. Then, a conceptual model of the FSFA process is constructed using a simultaneous incomplete information game, where flight operators compete for the “prizes” of having submitted their inputs before others. A numerical study is performed in which it is demonstrated that preference submission times are heavily influenced by the general uncertainty surrounding weather and operational conditions of the ATFM program, and each flight operator’s internal ability to handle this uncertainty. A key finding is that, in many of the scenarios presented, an optimal strategy for a flight operator is to submit their preferences at the very beginning of the planning period. If air traffic managers could expect to receive more submissions at the beginning of the planning period, they could more easily coordinate the ATFM program with other ATFM programs taking place or scheduled to take place, and they would have more opportunity to call another FSFA allocation route before the ATFM program begins, should conditions change enough to warrant this. Outputs of the model may provide some general insights to flight operators in planning submission strategies within competitive allocation processes such as FSFA. Also, this work may have a broader application to other sequential resource allocation strategies within congestible and controlled transportation systems.


      PubDate: 2015-06-25T02:29:12Z
       
  • Statistical approach for activity-based model calibration based on plate
           scanning and traffic counts data
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Treerapot Siripirote , Agachai Sumalee , H.W. Ho , William H.K. Lam
      Traditionally, activity-based models (ABM) are estimated from travel diary survey data. The estimated results can be biased due to low-sampling size and inaccurate travel diary data. For an accurate calibration of ABM parameters, a maximum-likelihood method that uses multiple sources of roadside observations (link counts and/or plate scanning data) is proposed. Plate scanning information (sensor path information) consists of sequences of times and partial paths that the scanned vehicles are observed over the preinstalled plate scanning locations. Statistical performances of the proposed method are evaluated on a test network using Monte Carlo technique for simulating the link flows and sensor path information. Multiday observations are simulated and derived from the true ABM parameters adopted in the choice models of activity pattern, time of the day, destination and mode. By assuming different number of plate scanning locations and identification rates, impacts of data quantity and data quality on ABM calibration are studied. The results illustrate the efficiency of the proposed model in using plate scanning information for ABM calibration and its potential for large and complex network applications.


      PubDate: 2015-06-25T02:29:12Z
       
  • Airline competition and market frequency: A comparison of the s-curve and
           schedule delay models
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Mark Hansen , Yi Liu
      We compare two common ways of incorporating service frequency into models of airline competition. One is based on the so called s-curve, in which, all else equal, market shares are determined by frequency shares. The other is based on schedule delay—the time difference between when travelers wish to travel and when flights are available. We develop competition models that differ only with regard to which of the above approaches is used to capture the effect of frequency. The demand side of both models is an approximation of a nested logit model which yields endogenous travel demand by including not traveling in the choice set. We find symmetric competitive equilibrium for both models analytically, and compare their predictions concerning market frequency with empirical evidence. In contrast to the s-curve model, the schedule delay model depicts a more plausible relationship between market share and frequency share and accurately predicts observed patterns of supply side behavior. Moreover, the predictions from both models are largely the same if we employ numerical versions of the model that capture real-world aspects of competition. We also find that, for either model, the relationship between airline frequency and market traffic is the same whether frequency is determined by competitive equilibrium, social optimality, or social optimality with a break-even constraint.


      PubDate: 2015-06-25T02:29:12Z
       
  • Transit technology investment and selection under urban population
           volatility: A real option perspective
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Zhi-Chun Li , Qian-Wen Guo , William H.K. Lam , S.C. Wong
      This paper addresses transit technology investment issues under urban population volatility using a real option approach. Two important problems are investigated: which transit technology should be selected and when should it be introduced. A real option model is proposed to incorporate explicitly the effects of transit technology investment on urban spatial structure in terms of households’ residential location choices and housing market. The trigger population thresholds for investing in a transit technology project and for shifting from a transit technology to another are explored analytically. Comparative static analyses of the urban system and transit technology investment are also carried out. It was found that (i) transit technology investment can induce urban sprawl; (ii) ignoring the effects of transit technology investment on urban spatial equilibrium can lead to a late investment; and (iii) there is a significant difference in the trigger population thresholds for transit technology shift estimated by the net present value approach and the real option approach.


      PubDate: 2015-06-25T02:29:12Z
       
  • Introducing non-normality of latent psychological constructs in choice
           modeling with an application to bicyclist route choice
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Chandra R. Bhat , Subodh K. Dubey , Kai Nagel
      In the current paper, we propose the use of a multivariate skew-normal (MSN) distribution function for the latent psychological constructs within the context of an integrated choice and latent variable (ICLV) model system. The multivariate skew-normal (MSN) distribution that we use is tractable, parsimonious in parameters that regulate the distribution and its skewness, and includes the normal distribution as a special interior point case (this allows for testing with the traditional ICLV model). Our procedure to accommodate non-normality in the psychological constructs exploits the latent factor structure of the ICLV model, and is a flexible, yet very efficient approach (through dimension-reduction) to accommodate a multivariate non-normal structure across all indicator and outcome variables in a multivariate system through the specification of a much lower-dimensional multivariate skew-normal distribution for the structural errors. Taste variations (i.e., heterogeneity in sensitivity to response variables) can also be introduced efficiently and in a non-normal fashion through interactions of explanatory variables with the latent variables. The resulting model we develop is suitable for estimation using Bhat’s (2011) maximum approximate composite marginal likelihood (MACML) inference approach. The proposed model is applied to model bicyclists’ route choice behavior using a web-based survey of Texas bicyclists. The results reveal evidence for non-normality in the latent constructs. From a substantive point of view, the results suggest that the most unattractive features of a bicycle route are long travel times (for commuters), heavy motorized traffic volume, absence of a continuous bicycle facility, and high parking occupancy rates and long lengths of parking zones along the route.


      PubDate: 2015-06-25T02:29:12Z
       
  • Scheduling heterogeneous train traffic on double tracks with efficient
           dispatching rules
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Xiaoming Xu , Keping Li , Lixing Yang
      To further improve the utilization rate of railway tracks and reduce train delays, this paper focuses on developing a high-efficiency train routing and timetabling approach for double-track railway corridors in condition that trains are allowable to travel on reverse direction tracks. We first design an improved switchable policy which is rooted in the approaches by Mu and Dessouky (2013), with the analysis of possible delays caused by different path choices. Then, three novel integrated train routing and timetabling approaches are proposed on the basis of a discrete event model and different dispatching rules, including no switchable policy (No-SP), Mu and Dessouky (2013)’s switchable policy (Original-SP) and improved switchable policy (Improved-SP). To demonstrate the performance of the proposed approaches, the heterogeneous trains on Beijing–Shanghai high speed railway are scheduled by aforementioned approaches. The case studies indicate that in comparison to No-SP and Original-SP approaches, respectively, the Improved-SP approach can reduce the total delay of trains up to 44.44% and 73.53% within a short computational time. Moreover, all of the performance criteria of the Improved-SP approach are usually better than those of other two approaches.


      PubDate: 2015-06-25T02:29:12Z
       
  • Data dependent input control for origin–destination demand
           estimation using observability analysis
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Yudi Yang , Yueyue Fan
      In this paper, we address the observability issue of static O–D estimation based on link counts. Unlike most classic observability analyses that relied only on network topological relationships, our analysis incorporates the actual values of input parameters, thus including network operational relations as well. We first analyze possible mathematical properties of an O–D estimation problem with different data input. We then propose a modeling approach based on mixed-integer program for selecting model input that ensures observability and estimation quality. Through establishing a stronger connection between observability analysis and the corresponding estimation problem, the proposed method aims to improve estimation quality while reducing reliance on erroneous data.


      PubDate: 2015-06-25T02:29:12Z
       
  • Joint service capacity planning and dynamic container routing in shipping
           network with uncertain demands
    • Abstract: Publication date: August 2015
      Source:Transportation Research Part B: Methodological, Volume 78
      Author(s): Jing-Xin Dong , Chung-Yee Lee , Dong-Ping Song
      Service capacity planning is a key tactic decision in container shipping, which has a significant impact on daily operations of shipping company. On the other hand, operational decisions such as demand fulfilment and shipment routing will impact on service capacity requirements and utilisation, particularly in the presence of demand uncertainty. This article proposes a two stage stochastic programming model with recourse to deal with the problem of joint service capacity planning and dynamic container routing in liner shipping. The first stage of the model concerns how to determine the optimal service capacity, and the second focuses on the optimal routing of shipments in stochastic and dynamic environments under a given service capacity plan. Initially, SAA (Sample Average Approximation) is employed to solve the model. Noting the computational complexity of the problem, Progressive Hedging Algorithm (PHA) is employed to decompose the SAA model into a number of scenario-based models so that reasonably large scale problems can be solved. To handle larger scale problems, we develop a new solution procedure termed as APHA (Adapted Progressive Hedging Algorithm) that further decomposes the scenario-based model into job (customer order) based models with measurable error bounds. Numerical experiments are conducted to illustrate the effectiveness of the proposed APHA in solving the problems under consideration.


      PubDate: 2015-06-25T02:29:12Z
       
 
 
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