Transportation Research Part C-Emerging Technologies最新文献

{"title":"Integrated demand-oriented and energy-efficiency train timetabling and rolling stock circulation planning for an urban rail transit line","authors":"Yu Huang,&nbsp;Wenliang Zhou,&nbsp;Guangming Xu,&nbsp;Lianbo Deng","doi":"10.1016/j.trc.2024.104993","DOIUrl":"10.1016/j.trc.2024.104993","url":null,"abstract":"<div><div>Saving energy has both significant environmental benefits and economic advantages. As the urban rail transit network and its consumed energy continue to expand, it is crucial to optimize the energy-saving operation scheme of trains. Energy-saving train operation often requires longer section running times, which is obviously not conducive to the quality of passenger service. In order to ensure passenger service quality when pursuing the decrease of the train’s energy consumption and rolling stocks’ operation cost, this paper proposes an integrated optimization model of the demand-oriented and energy-efficiency train timetable and rolling stock circulation plan for urban rail transit. Its objective is to minimize train net energy consumption, rolling stock utilization cost, as well as passenger waiting time and travel time. Specifically, the net energy consumption is defined as the difference between train required traction energy consumption and regenerative braking energy utilization. To efficiently solve this large-scale mixed integer nonlinear model, we design a solution algorithm combining Variable Neighborhood Search (VNS) and CPLEX, in which seven different neighborhood structures are constructed. Based on the data of Guangzhou Metro Line 13, we have verified the effectiveness and performance of the model and algorithm through numerical experiments of various scales, as well as through comparisons with other algorithms and models. The results demonstrate that the timetable and rolling stock circulation plan obtained by VNS can reduce net energy consumption by 9.55 %, rolling stock utilization cost by 9 %, and passenger waiting time by 4.77 %, and their travel time by 0.87 % compared to the current timetable.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104993"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating MFD model parameters from sparse license plate recognition data: The role of path reconstruction and regionalization","authors":"Cheng Hu ,&nbsp;Jinjun Tang ,&nbsp;Zhitao Li ,&nbsp;Yaopeng Wang ,&nbsp;Chuyun Zhao ,&nbsp;Jiguang Chen ,&nbsp;Hao Zhou","doi":"10.1016/j.trc.2024.104982","DOIUrl":"10.1016/j.trc.2024.104982","url":null,"abstract":"<div><div>The Macroscopic Fundamental Diagram (MFD) provides a convenient and computationally efficient tool for urban traffic monitoring and control. However, the accurate estimation of the model parameters is a prerequisite for the MFD models to be practically applicable. The significant deficiencies in commonly used data sources underscore the importance of utilizing new data sources to estimate the MFD model parameters. This study proposes a comprehensive framework to estimate critical parameters for multi-region MFD models based solely on License Plate Recognition (LPR) data. An efficient link-based path reconstruction algorithm is introduced to transform observed vehicle trajectories into continuous paths. Considering the inherent incompleteness of observed trajectories, this study presents a novel regionalization framework to match initial or final observation points to specific subregional networks. An adaptive large neighborhood search (ALNS) algorithm is proposed to improve the flow correlation within these subregions. Subsequently, an OD inference model using importance sampling is introduced to estimate the true OD of trips within the identified subregions. The resulting complete vehicle trips can be used to estimate trip length distributions and path flow coefficients. In addition, a method for estimating the MFD shape, tailored for application to sparse LPR data and based on reconstructed vehicle trajectories, is proposed. The effectiveness of these methods is validated through both simulation experiments and empirical studies. This framework is expected to facilitate the practical application of MFD models to realistic road networks.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104982"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal operation strategy in the collaborative urban freight transport system with concept of capacity allocation","authors":"Xin Guo ,&nbsp;David Z.W. Wang ,&nbsp;Huijin Sun ,&nbsp;Jianjun Wu ,&nbsp;Jin Zhou","doi":"10.1016/j.trc.2024.104973","DOIUrl":"10.1016/j.trc.2024.104973","url":null,"abstract":"<div><div>Worldwide, urban freight transport demand has rapidly expanded. Collaborative freight transport service, which integrates existing public transport system into the freight transport service, would be a promising solution to solve such post-pandemic urban freight transport problem. While most of the previous research works on this topic considered the operation of the public transport service and freight delivery service separately, this paper would focus on how to determine coordinated operational strategies of the participating public transport and freight transport services in a cooperative regime. Specifically, the definition of the capacity allocation event is proposed to encourage more seamless freight movements at transfer hubs within the given limited temporal restrictions while considering both the travel delay for public transport passengers and all incurred operational costs for offering the collaborative freight transport service. To this end, we propose a multi-objective mathematical model to describe the operation design of the collaborative freight transport service, aiming to maximize the synchronized freight movement at transfer hub and minimize the incurred passenger travel delay and operational costs. A Multi-objective Bernstein Basis Differential Evolution (MOBDE) solution method, requiring no pre-determined control parameters, is employed to find the optimal solution efficiently. Finally, an illustrative example is presented to demonstrate the validity of the model formulation and efficiency of the solution method for the operation design of collaborative freight transport services.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104973"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Event-based models for the electric autonomous dial-a-ride problem","authors":"Verena Stallhofer,&nbsp;Sophie N. Parragh","doi":"10.1016/j.trc.2024.104896","DOIUrl":"10.1016/j.trc.2024.104896","url":null,"abstract":"<div><div>On-demand transportation systems can serve to complement standard scheduled public transport in areas with low population density or to address the mobility needs of handicapped and elderly people. In this paper, we address the electric autonomous dial-a-ride problem (e-ADARP). In the e-ADARP, vehicle routes for serving user requests consisting of pickup and drop-off locations are determined. The objective is to minimize a weighted combination of travel distances and excess user ride time. Since it is assumed that an electric and autonomous vehicle fleet is used for the ride-sharing service, in addition to vehicle capacity, time windows, and maximum user ride times, also battery capacity constraints have to respected. We develop a mixed-integer linear programming (MILP) model for the e-ADARP that relies on an event-based graph. By using an event-based graph, capacity, pairing, and precedence constraints are implicitly applied. Several valid inequalities from the literature as well as newly developed ones are used to strengthen the model. In comparison to existing exact methods for the e-ADARP, we obtain competitive results on a set of available benchmark instances: we provide several improved upper and lower bounds and provide optimal solutions to previously unsolved instances. Furthermore, we analyze the impact of the capacity setting as well as different weight combinations on solution time and demonstrate the effect of battery start and end levels over several periods.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104896"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical model for large-scale design of sidewalk delivery robot systems with bounded makespans","authors":"Hai Yang ,&nbsp;Yuchen Du ,&nbsp;Tho Le ,&nbsp;Joseph Y.J. Chow","doi":"10.1016/j.trc.2024.104978","DOIUrl":"10.1016/j.trc.2024.104978","url":null,"abstract":"<div><div>With the rise in demand for local deliveries and e-commerce, robotic deliveries are being considered as efficient and sustainable solutions. However, the deployment of such systems can be highly complex due to numerous factors involving stochastic demand, stochastic charging and maintenance needs, complex routing, etc. We propose a model that uses continuous approximation methods with bounded makespans for evaluating service trade-offs that consider the unique characteristics of large-scale sidewalk delivery robot systems used to serve online food deliveries. The model accurately approximates the average routing performance and the fleet size required to establish an online food delivery service without the operation details. Using the results, the model captures both the initial cost and the operation cost of the delivery system and evaluates the impact of constraints and operation strategies on the deployment. By minimizing the system cost, variables related to the system design can be determined. First, the minimization problem is formulated based on a homogeneous area, and the optimal system cost can be derived as a closed-form expression. We apply the model to neighborhoods in New York City to evaluate the cost of deploying the sidewalk delivery robot system in a real-world scenario. The results shed light on the potential of deploying such a system in the future.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104978"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-echelon prize-collecting vehicle routing with time windows and vehicle synchronization: A branch-and-price approach","authors":"I. Edhem Sakarya ,&nbsp;Milad Elyasi ,&nbsp;S.U.K. Rohmer ,&nbsp;O. Örsan Özener ,&nbsp;Tom Van Woensel ,&nbsp;Ali Ekici","doi":"10.1016/j.trc.2024.104987","DOIUrl":"10.1016/j.trc.2024.104987","url":null,"abstract":"<div><div>The steady growth in e-commerce and grocery deliveries within cities strains the available infrastructure in urban areas by increasing freight movements, aggravating traffic congestion, and air and noise pollution. This research introduces the <em>Two-Echelon Prize-Collecting Vehicle Routing Problem with Time Windows and Vehicle Synchronization</em>, where deliveries are carried out by smaller low- or zero-emission vehicles and larger trucks. Given their capacity restrictions, the smaller vehicles can only deliver small-sized orders and must be replenished via depot locations or larger-sized trucks. Besides replenishing smaller vehicles at satellite locations, larger trucks can deliver small orders and larger items. Managing these two types of fleets in an urban setting under consideration of capacity limitations, tight delivery time windows, vehicle synchronization, and selective order fulfillment is challenging. We model this problem on a time-expanded network and apply network reduction by considering the time window constraints. In addition, we propose a branch-and-price algorithm capable of solving instances with up to 200 customers, which continuously outperforms a state-of-the-art general-purpose optimization solver. Moreover, we present several managerial insights concerning synchronization, vehicles, and the placement of depot/satellite locations.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104987"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of graph attention networks for traffic assignment in a large number of network scenarios","authors":"Xiuyu Hu,&nbsp;Chi Xie","doi":"10.1016/j.trc.2025.104997","DOIUrl":"10.1016/j.trc.2025.104997","url":null,"abstract":"<div><div>The traffic assignment problem (TAP) has been a well-known research problem in transportation science for over five decades. Various solution algorithms, including link-based, path-based, and bush-based methods, have been developed to address this problem, with different structural complexities, memory requirements, and solution efficiency. In transportation planning practice, it is required to execute a traffic assignment algorithm hundreds or thousands of times to find the most efficient planning scenarios for a large metropolitan network, which may be very time-consuming, often taking several days and even a few weeks. In this study, we suggest a data-driven method to perform evaluating a large number of transportation planning scenarios in a quicker manner. Instead of relying on iterative network optimization-oriented or equilibrium-oriented algorithms, we introduce a graph attention network (GAT) within an encoder–decoder framework to learn and derive traffic assignment solutions. The model consists of an encoder module and a decoder module, where the encoder module utilizes a special attention mechanism to abstract complex spatial supply–demand features, and the decoder module transforms these features into network flow patterns. We also present two model variants based on different output objectives: one directly predicts link flows, while the other first predicts path flows and then converts them to link flows. To validate the proposed models with different structural configurations and parameter values, we conducted two rounds of experiments on a set of widely used benchmark networks with various topological structures and demand patterns. The results show that both models can predict link flow rates with a mean absolute percentage error ranging from 3.8% to 8.5% across different networks. Moreover, they require lower computing time compared to traditional convergence algorithms. As the network size increases, the computational efficiency advantage becomes more pronounced. This suggests that the proposed machine learning approach provides an efficient computing procedure for executing traffic assignment for a large number of transportation planning scenarios.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104997"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic adjustment strategy of electric bus operations: A spatial branch-and-bound method with acceleration techniques","authors":"Yin Yuan ,&nbsp;Shukai Li ,&nbsp;Andrea D’Ariano ,&nbsp;Tommaso Bosi ,&nbsp;Lixing Yang","doi":"10.1016/j.trc.2025.105003","DOIUrl":"10.1016/j.trc.2025.105003","url":null,"abstract":"<div><div>Electric bus systems frequently encounter operational instability, resulting in delays, bunching and disturbed charging schemes. Advanced technologies like sensoring and wireless connectivity strongly support dynamic adjustments to improve the stability of electric bus systems, fostering flexibility responsiveness to changing operating conditions. This article explores the dynamic adjustment problem of electric bus operations to jointly generate bus charging schemes and timetable adjustments in a real-time decision-making process. We propose a mixed-integer nonlinear programming model for each decision stage, explicitly considering factors such as vehicle overtaking, passenger load, capacity limitations, and charging behaviors. To efficiently solve this problem, we design a spatial branch-and-bound method with multiple acceleration techniques of logical inference for bound contraction, bilinear-specific branching, and parallel computation. Indeed, the original mixed-integer nonlinear programming problem can be split into a series of mixed-integer quadratic programming problems with reduced domains. The acceleration techniques proposed could be easily customized to address other mixed-integer nonlinear programs in such branch-and-bound-based schemes. Computational experiments validate the effectiveness of the proposed adjustment strategy yielding feasible solutions that enhance headway regularity, energy savings and service quality. Additionally, our solution method efficiently tackles real-world scenarios of significant complexity, with up to 12 vehicles running 8 loops on a route comprising 54 stops, with an average of 5.11-seconds computational time, outperforming both the common commercial solver and standard spatial branch-and-bound approaches in computational speed.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 105003"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vehicle routing in one-way carsharing service with ridesharing options: A variable neighborhood search algorithm","authors":"Jiaqi Guo ,&nbsp;Jiancheng Long ,&nbsp;W.Y. Szeto ,&nbsp;Weimin Tan ,&nbsp;Sisi Jian","doi":"10.1016/j.trc.2024.104983","DOIUrl":"10.1016/j.trc.2024.104983","url":null,"abstract":"<div><div>The widespread adoption of one-way carsharing systems faces a significant hurdle in the form of vehicle imbalance. To address this challenge, this study proposes a novel hybrid operator-user-based relocation scheme that integrates one-way carsharing systems with ridesharing options, enabling users to complete their trips by sharing carsharing vehicles with others. This integration necessitates the concurrent optimization of vehicle relocation routing and ridesharing matching strategies by carsharing operators. The underlying problem, termed the vehicle relocation and ridesharing matching problem, is formulated as a mixed-integer linear program with the objective of maximizing total system profit. Given the NP-hard nature of the vehicle relocation and ridesharing matching problem, a variable neighborhood search algorithm is developed for its solution. The algorithm incorporates an efficient route evaluation scheme to improve the efficiency of the algorithm. Numerical experiments demonstrate that the proposed solution method is capable of producing high-quality solutions within short computing time. We also show that the mutual benefits of the proposed integrated scheme for both carsharing operators and users, including increased profitability, reduced travel costs, and improved service quality.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104983"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating lane-change prediction into energy-efficient speed control of connected autonomous vehicles at intersections","authors":"Maziar Zamanpour ,&nbsp;Suiyi He ,&nbsp;Michael W. Levin ,&nbsp;Zongxuan Sun","doi":"10.1016/j.trc.2024.104968","DOIUrl":"10.1016/j.trc.2024.104968","url":null,"abstract":"<div><div>Connected and autonomous vehicles (CAVs) possess the capability of perception and information broadcasting with other CAVs and connected intersections. Additionally, they exhibit computational abilities and can be controlled strategically, offering energy benefits. One potential control strategy is real-time speed control, which adjusts the vehicle speed by taking advantage of broadcasted traffic information, such as signal timings. However, the optimal control is likely to increase the gap in front of the controlled CAV, which induces lane changing by other drivers. This study proposes a modified traffic flow model that aims to predict lane-changing occurrences and assess the impact of lane changes on future traffic states. The primary objective is to improve energy efficiency. The prediction model is based on a cell division platform and is derived considering the additional flow during lane changing. An optimal control strategy is then developed, subject to the predicted trajectory generated for the preceding vehicle. Lane change prediction estimates future speed and gap of vehicles, based on predicted traffic states. The proposed framework outperforms the non-lane change traffic model, resulting in up to 13% energy savings when lane changing is predicted 4–6 s in advance.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104968"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}