Transportation Research Part B-Methodological最新文献

A risk-averse two-stage stochastic programming approach for backup rolling stock allocation and metro train rescheduling under uncertain disturbances

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-26 DOI: 10.1016/j.trb.2025.103233

Boyi Su , Andrea D’Ariano , Shuai Su , Zhikai Wang , Marta Leonina Tessitore , Tao Tang

Disturbances occur inevitably during daily operations of the metro system, leading to train delays and low service quality. Different from common deterministic reactive train rescheduling frameworks, taking the inherent uncertain characteristic of disturbance into account, this paper formulates a two-stage stochastic programming model to address the integration of proactive backup rolling stock allocation and reactive train rescheduling. Specifically, the backup rolling stock allocation plan is optimized in the first stage, while the train timetable and rolling stock circulation are rescheduled under different disturbance realizations in the second stage. The objective is to achieve a balance between allocation costs and negative disturbance impacts, which is evaluated by the mean-conditional value-at-risk criterion on account of the risk-averse attitude of train dispatchers. For computational tractability, the proposed model is reformulated as an equivalent mixed-integer linear programming (MILP) model. To improve computational efficiency, an innovative solution framework is designed. The integer L-shaped method is used to decompose the MILP into a master problem and a series of subproblems, with three acceleration techniques introduced to expedite the subproblem-solving process. Finally, numerical experiments are carried out based on the Beijing Batong Metro Line to verify the performance of the proposed mathematical model and solution framework. The results indicate that the proposed method outperforms benchmarks. Furthermore, comprehensive analysis is conducted on the effects of different parameter settings to provide some managerial insights for dispatchers.

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引用次数: 0

Column-and-row generation based exact algorithm for relay-based on-demand delivery systems

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-25 DOI: 10.1016/j.trb.2025.103223

Xueting He, Lu Zhen

This paper studies an operation optimization problem in a relay-based on-demand delivery system that uses couriers and drones to transport customers’ parcels. For a batch of customer orders with their delivery due times, the system must decide which orders to accept and which courier to dispatch to pick up each accepted order and transport it to a suitable station, from where a drone will transport it to another station and then another courier will transport it to its final destination. Using mixed-integer linear programing, this paper formulates a novel arc-based set-packing model with two types of columns, i.e., drone plans and courier plans, to maximize the profit from transporting a batch of orders. By combining branch-and-price, column-and-row generation, and some tailored acceleration tactics, an exact algorithm is designed and implemented to efficiently solve the model. Experimental results validate the efficiency of the proposed exact algorithm. Moreover, we find that large numbers of couriers, drones, or stations do not always substantially improve the system’s performance; if order due times are urgent, the benefit of drones (couriers) is more (less) significant. The model’s robustness and the applicability of our methodology in large-scale applications are validated.

本文研究了一个基于中继的按需配送系统中的操作优化问题，该系统使用快递员和无人机来运送客户的包裹。对于一批有交货期的客户订单，系统必须决定接受哪些订单，以及派遣哪些快递员来接收每个接受的订单并将其运送到合适的站点，然后由无人机将其运送到另一个站点，再由另一个快递员将其运送到最终目的地。本文利用混合整数线性规划，制定了一种新颖的基于弧的集合包装模型，其中包含两种列，即无人机计划和快递员计划，以最大化运输一批订单的利润。通过结合分支与价格、列与行生成以及一些量身定制的加速策略，本文设计并实现了一种精确算法来高效求解该模型。实验结果验证了所提精确算法的效率。此外，我们还发现，大量的快递员、无人机或站点并不总是能大幅提高系统性能；如果订单到期时间紧迫，无人机（快递员）的优势会更明显（不那么明显）。模型的稳健性和我们的方法在大规模应用中的适用性得到了验证。

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引用次数: 0

On the calibration of stochastic car following models

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-24 DOI: 10.1016/j.trb.2025.103224

Shirui Zhou , Shiteng Zheng , Tu Xu , Martin Treiber , Junfang Tian , Rui Jiang

Recent empirical and theoretical findings highlight the critical role of stochasticity in car-following (CF) dynamics. Although several stochastic CF models have been proposed, their calibration remains relatively underexplored compared to deterministic models. This article addresses this gap by utilizing four stochastic CF models to conduct a comprehensive evaluation of two existing calibration methods—minimizing multiple runs mean error (MRMean) and maximum likelihood estimation (MLE) as well as a newly proposed method, minimizing multiple runs minimum (MRMin) error, based on synthetic trajectories. Results show that MRMean and MLE exhibit significant biases in estimating the ground truth values of stochastic model parameters, while MRMin achieves nearly zero estimation errors. Specifically, MRMean eliminates stochasticity, transforming models into deterministic ones, whereas MRMin successfully separates aleatoric errors caused by randomness and epistemic errors caused by parameters, as demonstrated through a theoretical error analysis. Furthermore, CF experiments conducted in an identical driving environment reveal that differences in spacing are more pronounced than differences in speed. Calibration against experimental trajectories verifies the conclusions drawn from synthetic trajectories and theoretical analysis. Additionally, the covariance matrix of parameters is estimated using bootstrap sampling, highlighting MRMin’s ability to capture the inherent stochasticity of CF behavior. These findings deepen our understanding of CF stochasticity and provide a robust framework for calibrating stochastic models.

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引用次数: 0

Optimal private housing supply under various schemes of public housing provision

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-24 DOI: 10.1016/j.trb.2025.103232

Yue Huai , Hong K. Lo , Anming Zhang

Allocating land for public housing is an essential step in providing affordable housing for low-income citizens, as practiced in Hong Kong and Singapore. Locating public housing projects in suburban areas causes a spatial mismatch between public housing tenants and job opportunities, while placing public units in urban areas exacerbates the shortage of urban land, which may result in a more compact urban development that worsens the living conditions of urban private flats. We extend the stochastic bid-rent framework to derive the optimal supply decisions of profit-seeking developers under various schemes of public housing provision. The residence and travel choices of heterogeneous households are simulated under the optimal supply decisions. We find that placing a certain number of public flats in urban areas will lead to a higher profit for developers. With more public housing in urban areas, developers condense the urban development and provide more urban micro flats to capture the privilege of accessibility, which lowers the quality of private urban flats. On the other hand, compact development accommodates more residents in urban areas, thereby alleviating congestion in suburban areas. This improvement in accessibility, however, results in rent increases for suburban private flat residents, who will suffer a loss of consumer surplus. Similarly, policy measures that aim to improve living standards or shorten the commuting time for residents (e.g., imposing restrictions on minimum flat size or upgrading suburban transport facilities) may affect the welfare of other stakeholders adversely. Thus, it is unlikely that a land allocation that improves the welfare of all stakeholders can be found, rendering the importance of considering this trade-off judiciously.

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引用次数: 0

Government persuasion strategies for transport infrastructure adaptation: Spillover effects and social welfare impacts

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-24 DOI: 10.1016/j.trb.2025.103221

Shiyuan Zheng , Changmin Jiang

This paper explores the government's strategies to persuade multiple transport facility operators to undertake adaptation projects, particularly within the Asian doctrine governance regime, where the government exerts significant influence over facility operations. We develop a Bayesian persuasion model to analyze these strategies, focusing on the spillover effects among operators' projects and their externalities (both positive and negative) on social welfare. Our findings suggest that a straightforward signaling strategy, which directly advises operators on whether to invest, can effectively convey disaster information. When there are no spillover effects and the adaptation projects positively impact social welfare, the government should fully disclose disaster information and persuade operators based on their willingness to invest. However, higher adaptation costs or larger spillover effects complicate the government's persuasion efforts. To demonstrate the practical value of our theoretical framework, we apply our Bayesian persuasion model to the case of port adaptation in the Greater Bay Area in China. The model calibration results indicate that when operators act independently, larger spillover effects can lead to either lower or higher social welfare, depending on whether the adaptation projects have positive or negative impacts, respectively. When adaptation projects positively affect social welfare, operators' alliance strategies of joint adaptation investment or resource sharing enhance social welfare. If spillover effects exist among operators, a benefit distribution scheme based on the Shapley value can maintain stability within the grand coalition of all operators. Finally, increasing adaptation costs have uneven impacts on different operators, with those facing the highest costs being more likely to be excluded from the government's persuasion efforts.

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引用次数: 0

Robust control for connected automated vehicle platoon with multiple-predecessor following topology considering communication loss

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-22 DOI: 10.1016/j.trb.2025.103212

Lei Yang , Zhanbo Sun , Yafei Liu , Linbin Chen

The paper presents a robust control method for effectively managing uncertainties and communication loss in a connected automated vehicle (CAV) platoon under the multiple-predecessor following (MPF) topology. The proposed approach incorporates uncertainties in vehicle dynamics, such as vehicle parameters and environmental resistances, into the closed-loop platoon system to enhance the robustness of the platoon controller. The impacts of communication loss are analyzed specifically for the MPF topology, considering potential disruptions in information flow among different numbers and locations of predecessors in a CAV platoon. A novel formulation of desired spacing, suitable for CAV platoon with the MPF topology under communication loss, is then developed based on the constant time headway (CTH) policy. Furthermore, the paper derives and proves the sufficient and necessary conditions for the local stability of the proposed robust platoon controller using Kharitonov's theorem. The sufficient conditions for string stability are also discussed through frequency-domain analysis and combined with the Lyapunov function to determine the relationship between average dwell time and maximum allowable delay, ensuring platoon string stability under switching communication topology. These conditions establish the stability region for the robust controller of a CAV platoon with varying locations and numbers of unconnected predecessors. Simulation experiments are conducted to demonstrate that the stability region of the controller diminishes as the number of unconnected predecessors increases, with the greatest impact observed when the communication with the nearest connected predecessor is lost. Additionally, the control performance is affected by uncertain dynamics and the range of time headway, resulting in a significant reduction in the stability region. The findings highlight the importance of fine-tuning control parameters within the stability region guided by the derived stability conditions to ensure both local and string stability of CAV platoons.

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引用次数: 0

A bi-level optimization model for project scheduling and traffic flow routing in railway networks

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-20 DOI: 10.1016/j.trb.2025.103213

Tomas Lidén , Filip Kristofersson , Martin Aronsson

Long-term tactical infrastructure planning for a transportation network consists of deciding on renewals and major maintenance works. Such projects constitute large budget volumes and will impair the available traffic capacity during their execution, especially for railway systems. Quantitative methods that schedule and coordinate infrastructure projects together with traffic flow adaptations is however largely lacking today.

This paper addresses the joint planning of temporary capacity restrictions and traffic flow adaptions during track work closures, by proposing a bi-level optimization model which separates the problem into project scheduling (upper level) and traffic assignment (lower level). The latter model uses a novel traffic flow formulation for routing volumes of trains through the transportation network under the capacity restrictions given by the project scheduling. An aggregated network is used together with time discretized into uniform periods, which makes it possible to treat large national planning problems with a planning horizon of up to a year and a period length of a couple hours. The computational properties are evaluated, both for the individual models, and for their joint usage. Furthermore, results from applying the models on two case studies, concerning Northern and South-Western Sweden, are presented.

The main conclusion is that the model formulations are capable of solving realistic planning cases and to provide support for capacity planners at an infrastructure manager, even for a large national railway. The results show that a good overview over the collective traffic impact is obtained, but also that details of particular traffic relations or capacity usage over individual network links and their variation over time can be studied. One major deficiency has been identified in the flow-based traffic assignment model, which can lead to incoherent train flows over long traveling distances and many time periods.

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引用次数: 0

Nonparametric mixed logit model with market-level parameters estimated from market share data

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-18 DOI: 10.1016/j.trb.2025.103220

Xiyuan Ren , Joseph Y.J. Chow , Prateek Bansal

We propose a nonparametric mixed logit model that is estimated using market-level choice share data. The model treats each market as an agent and represents taste heterogeneity through market-specific parameters by solving a multiagent inverse utility maximization problem, addressing the limitations of existing market-level choice models with parametric estimation. A simulation study is conducted to evaluate the performance of our model in terms of estimation time, estimation accuracy, and out-of-sample predictive accuracy. In a real data application, we estimate the travel mode choice of 53.55 million trips made by 19.53 million residents in New York State. These trips are aggregated based on population segments and census block group-level origin-destination (OD) pairs, resulting in 120,740 markets. We benchmark our model against multinomial logit (MNL), nested logit (NL), inverse product differentiation logit (IPDL), and the BLP models. The results show that the proposed model improves the out-of-sample accuracy from 65.30 % to 81.78 %, with a computation time less than one-tenth of that taken to estimate the BLP model. The price elasticities and diversion ratios retrieved from our model and benchmark models exhibit similar substitution patterns. Moreover, the market-level parameters estimated by our model provide additional insights and facilitate their seamless integration into supply-side optimization models for transportation design. By measuring the compensating variation for the driving mode, we found that a $9 congestion toll would impact roughly 60 % of the total travelers. As an application of supply-demand integration, we showed that a 50 % discount of transit fare could bring a maximum ridership increase of 9402 trips per day under a budget of $50,000 per day.

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引用次数: 0

Robust train carriage planning for mixed transportation of passengers and uncertain freights in a high-speed railway network

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-18 DOI: 10.1016/j.trb.2025.103216

Chuntian Zhang , Zhou Xu , Lixing Yang , Ziyou Gao , Yuan Gao

Mixed transportation of passengers and freights is an effective strategy for reducing environmental pollution and improving the service level of railway systems. This study addresses the problem of robust train composition and carriage arrangement for the mixed transportation of passengers and freights in a high-speed railway (HSR) network. Specifically, a network-based robust optimization (RO) model is introduced to address the uncertainty in freight demand while considering deterministic passenger demand. The model utilizes space–time network representations to characterize the movements of passengers and freights. To account for various potential scenarios, a polyhedral uncertainty set is integrated into the model. Moreover, we develop a novel exact algorithm called B-C&CG, which utilizes the strengths of Benders decomposition for solving the deterministic passenger sub-problem and the strengths of column-and-constraint generation (C&CG) for solving the robust freight sub-problem. This provides an efficient solution to the RO model formulated for our problem. The objective is to optimize the train operating cost, passenger generalized travel cost, and the worst-case freight travel cost simultaneously. Additionally, a series of numerical experiments based on the real-world instance in a HSR network are conducted to verify the effectiveness of the developed B-C&CG algorithm and the advantages of the proposed RO model. The results demonstrate that (i) the newly developed algorithm outperforms both the Benders decomposition algorithm and the hybrid algorithm (B-BC&CG) in terms of computing time, where the latter differs from B-C&CG by using both Benders decomposition and C&CG to handle the robust freight sub-problem; (ii) the degree of conservatism can be controlled by altering parameters related to uncertain freight demand; (iii) the proposed RO model can improve the worst-case solutions under polyhedral uncertainty set, compared to nominal and stochastic programming models.

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引用次数: 0

Managing uncertain traffic and societal externalities in a road and rail network: Pricing versus Permits

IF 5.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part B-Methodological

Pub Date : 2025-04-17 DOI: 10.1016/j.trb.2025.103214

Kexin Geng , Zhiyuan Liang , Erik T. Verhoef , Yacan Wang

This paper studies the relative performance of congestion pricing versus tradable permits for a congested bi-modal transport system with traffic externalities, that affect passengers only, and societal externalities that go beyond the passengers. The point in this case is infection risks, as in the pandemic. We study this relative performance for the case where there are uncertainties on both traffic externalities and societal externalities. Earlier literature considered the relative performance of prices and permits for the case with only stochastic traffic externalities. The numerical results indicate that, given how infection risks are likely to affect social cost functions, pricing regulation can be expected to perform better than a tradable permit scheme when there are uncertainties on private infection cost, especially when the uncertainties on the marginal private infection cost increase. However, the government can enhance the performance of tradable permits by allowing the bankability of permits, or by actively engaging in buying or selling permits to optimize the price in response to the realization of stochastic parameters. The results provide theoretical support for policymakers to choose the optimal instruments to internalize the multiple external costs when uncertainties exist.

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引用次数: 0