Transportation Letters-The International Journal of Transportation Research最新文献

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Service area design and allocation problem for electric bike sharing system under demand uncertainty 需求不确定性下电动自行车共享系统服务区设计与分配问题

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-02-01 DOI: 10.1080/19427867.2025.2454075

Wenshan Liu , Zihao Tian , Rui Zhao , Yixiao Liu , Lixin Tian , David Z. W. Wang

Currently, the electric bike sharing system (EBSS) has gained popularity due to its efficiency and eco-friendliness. However, limited battery capacity of electric bikes (EBs) complicates the system design. To address this, we propose a service area design and allocation model incorporating hybrid stations, aiming to maximize daily net profit. Two cases are explored to address demand uncertainty. First, an expected value model is established, where demand is described probabilistically. Second, demand uncertainty is addressed by modeling random variables as uncertain parameters within an uncertainty set. A two-stage robust optimization model is developed, which maximizes the net profit in the worst-case scenario. We design a row generation approach to solve adjustable two-stage robust programs. Numerical experiments with data from the Daha EBSS in Yangzhou, China, demonstrate the model applicability. Moreover, the proposed algorithm outperforms the existing scenario-based approach in terms of both solution quality and computational efficiency.

目前，电动自行车共享系统（EBSS）因其效率和生态友好性而受到欢迎。然而，电动自行车的电池容量有限，使系统设计变得复杂。为了解决这个问题，我们提出了一个包含混合站的服务区设计和分配模型，旨在最大化日净利润。探讨了两个案例来解决需求不确定性。首先，建立期望值模型，对需求进行概率描述。其次，通过将随机变量建模为不确定集合中的不确定参数来解决需求不确定性。建立了在最坏情况下净利润最大化的两阶段鲁棒优化模型。我们设计了一种行生成方法来求解可调的两阶段鲁棒规划。利用扬州大哈EBSS数据进行的数值试验验证了模型的适用性。此外，该算法在求解质量和计算效率方面都优于现有的基于场景的方法。

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引用次数: 0

Matrix-based long-term traffic flow prediction 基于矩阵的长期交通流量预测

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2024-12-15 DOI: 10.1080/19427867.2024.2440211

Qi Guo , Benyun Shi , Youjie Wan

Accurate long-term traffic prediction is crucial for enhancing traffic efficiency, ensuring urban safety, and fostering sustainable urban development. However, forecasting over extended periods is challenging due to intricate trends, cyclical variations, and interference from outlier data. To address these issues, this study proposes a matrix-based traffic flow prediction model. The model constructs a matrix with periods as rows and similarities as columns, leveraging periodicity and similarity in traffic data. A row-column prediction module links these patterns efficiently, while a fluctuation transformation mitigates the impact of outliers, significantly improving forecast accuracy. Extending the forecast time span to 14 days with hourly intervals, the model was validated using the PeMS dataset provided by the California Department of Transportation. Results demonstrate the model’s effectiveness in capturing complex temporal dynamics, providing a robust tool for long-term traffic prediction.

准确的长期交通预测对于提高交通效率、保障城市安全、促进城市可持续发展至关重要。然而，由于复杂的趋势、周期性变化和异常数据的干扰，长期预测是具有挑战性的。为了解决这些问题，本研究提出了一种基于矩阵的交通流预测模型。该模型利用交通数据的周期性和相似性，构建了以周期为行、相似度为列的矩阵。行-列预测模块有效地将这些模式联系起来，而波动变换减轻了异常值的影响，显著提高了预测精度。该模型利用加州交通部提供的PeMS数据集进行了验证，将预测时间延长至14天，每小时进行一次。结果表明，该模型在捕捉复杂的时间动态方面的有效性，为长期交通预测提供了一个强大的工具。

引用次数: 0

Revisit bus network robustness from the perspective of service-physical dependency 从服务-物理依赖的角度重新审视总线网络的健壮性

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-03-01 DOI: 10.1080/19427867.2025.2470543

Jin-Yang Li , Hui Wang , Jing Teng

This study revisits bus network robustness by addressing the dependency of bus service networks on the underlying physical road network. A novel methodology integrates resistance distance theory with a multilayer physical-service network framework, accounting for disruptions at the road layer and detour mechanisms. Two robustness indices are introduced: the absolute resistance robustness index, which quantifies the overall impact of disruptions, and the relative resistance robustness index, which reflects network redundancy. Using data from 29 cities, the empirical analysis reveals that geographical and socioeconomic factors significantly influence bus network robustness, with higher GDP, flatter terrains, and concentrated urban areas associated with greater relative robustness. Sensitivity analysis identifies terrain compactness as the most influential factor. This methodology advances the theoretical understanding of transportation network resilience and provides practical tools for urban transportation planning. Future research could extend the approach to directional networks and incorporate travel demand data for more refined analyses.

本研究通过解决公共汽车服务网络对底层物理道路网络的依赖性，重新审视了公共汽车网络的鲁棒性。一种新的方法将阻力距离理论与多层物理服务网络框架相结合，考虑了道路层和绕行机制的中断。引入了两个鲁棒性指标：量化中断总体影响的绝对阻力鲁棒性指标和反映网络冗余的相对阻力鲁棒性指标。利用来自29个城市的数据进行实证分析，发现地理和社会经济因素显著影响公交网络的稳健性，GDP越高、地形越平坦、城市集中地区相对稳健性越强。敏感性分析认为地形密实度是最重要的影响因素。该方法促进了对交通网络弹性的理论认识，并为城市交通规划提供了实用工具。未来的研究可以将方法扩展到定向网络，并将旅行需求数据纳入更精确的分析。

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引用次数: 0

Traffic flow forecasting based on augmented multi-component recurrent graph attention network 基于增强多分量循环图注意网络的交通流预测

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-01-13 DOI: 10.1080/19427867.2025.2450577

Yuan Yao , Linlong Chen , Xianchen Wang , Xiaojun Wu

Accurate real-time traffic flow forecasting has been a challenge due to the complex spatial–temporal dependencies and uncertainties associated with the dynamic changes in traffic flow. To overcome this problem, a traffic flow forecasting model based on an Augmented Multi-Component Recurrent Graph Attention Network (AMR-GAT) is proposed in this paper to model the spatial–temporal correlations and periodic offset of traffic flows. This paper introduces an augmented multi-component module to address periodic temporal offset in traffic flow forecasting. It proposes an encoder-decoder architecture combining 1D convolution and LSTM via a Temporal Correlation Learner (TCL) to capture temporal characteristics, while a Graph Attention Network (GAT) handles spatial features. TCL and GAT are integrated to manage spatial-temporal correlations, and the decoder uses TCL and convolutional neural networks to generate high-dimensional representations based on spatial-temporal sequences. Experiments on two datasets demonstrate superior prediction performance of the proposed AMR-GAT model.

由于交通流的动态变化具有复杂的时空依赖性和不确定性，对交通流进行准确的实时预测一直是一个挑战。为了克服这一问题，本文提出了一种基于增强多分量循环图注意网络（AMR-GAT）的交通流预测模型，以模拟交通流的时空相关性和周期偏移。针对交通流预测中的周期性时间偏移问题，提出了一种增强型多分量模型。它提出了一种结合1D卷积和LSTM的编码器-解码器架构，通过时间相关学习器（TCL）捕获时间特征，而图注意网络（GAT）处理空间特征。该解码器集成TCL和GAT来管理时空相关性，并使用TCL和卷积神经网络生成基于时空序列的高维表示。在两个数据集上的实验表明，所提出的AMR-GAT模型具有较好的预测性能。

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引用次数: 0

A system dynamics approach for assessing the impacts of autonomous vehicles on collision frequency 自动驾驶汽车碰撞频率影响评估的系统动力学方法

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-01-19 DOI: 10.1080/19427867.2025.2452725

Ali Farhan , Lina Kattan , Nigel Waters , Richard Tay

This study employs a System Dynamics (SD) approach to assess the long-term impact of Autonomous Vehicles (AVs) on traffic collisions. By modeling key variables affecting collision frequency, the SD framework represents existing transportation systems and incorporates AV adoption to evaluate changes in collision rates. The models predict the frequency of Property Damage Only (PDO) and Fatal-Injury (FI) collisions at different levels of AV market penetration. Two policy scenarios are examined: incentives for shared AVs and higher occupancy rates for shared AV services. Results indicate significant improvements in traffic safety as AV penetration increases, particularly when coupled with shared AV usage and advanced sensing and communication technologies. The models provide valuable insights into the complex interactions between AVs and collision-related factors. These findings support the development of effective policies to guide the adoption of AV technology, reduce accidents, and enhance overall road safety in the long term.

本研究采用系统动力学（SD）方法评估自动驾驶汽车（AVs）对交通碰撞的长期影响。通过对影响碰撞频率的关键变量进行建模，SD框架代表了现有的交通系统，并结合自动驾驶汽车的采用来评估碰撞率的变化。这些模型预测了在不同的自动驾驶汽车市场渗透率水平下，仅财产损害（PDO）和致命伤害（FI）碰撞的频率。研究了两种政策情景：共享自动驾驶汽车的激励措施和共享自动驾驶汽车服务的更高入住率。研究结果表明，随着自动驾驶汽车普及率的提高，尤其是与共享自动驾驶汽车和先进的传感和通信技术相结合，交通安全得到了显著改善。这些模型为自动驾驶汽车与碰撞相关因素之间的复杂相互作用提供了有价值的见解。这些研究结果支持制定有效的政策，以指导自动驾驶技术的采用，减少事故，并从长远来看提高整体道路安全。

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引用次数: 0

Optimizing the train timetable considering cross-line operation in the urban rail transit network 考虑城市轨道交通网络跨线运行的列车时刻表优化

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-03-17 DOI: 10.1080/19427867.2025.2470456

Junsheng Huang , Qin Luo , Kang Huang

Cross-line operation stands out as one of the emerging new metro operations. This paper investigates the cooperative optimization of cross-line train stopping/overtaking schemes, and train timetables on the metro network under cross-line operation. To describe passengers’ traveling process, a travel path alternative set generation method based on rational passengers is proposed, which proactively distinguishes the travel paths of passengers. For a given passenger travel path, the paper adopts a passenger pre-classification method, dividing passengers into four groups, to separately calculate their travel time. The model’s optimization objective is to minimize the travel time of passengers across the entire network. To enhance the efficiency of the model solution, a two-stage algorithm with a search strategy is introduced. To demonstrate the correctness of the model and the effectiveness of the algorithm, the model is applied to a network comprising 4 lines and 39 stations. Comparing with split-line operation, the results demonstrate that cross-line operations can achieve an approximate 11.32% reduction in network-wide passenger travel time and a substantial 67.09% reduction in network-wide transfer flow. Finally, this paper conducts a set of sensitivity analyses to summarize the characteristics of cross-line train operation and provides recommended combinations for passengers choosing the train service.

跨线运营是新兴的地铁运营方式之一。本文研究了跨线运营下地铁网络列车停/超车方案和列车时刻表的协同优化问题。为了描述乘客的出行过程，提出了一种基于理性乘客的出行路径备选集生成方法，该方法能够主动区分乘客的出行路径。对于给定的乘客出行路径，本文采用乘客预分类方法，将乘客分为四组，分别计算其出行时间。该模型的优化目标是使整个网络中乘客的出行时间最小。为了提高模型求解的效率，引入了一种带搜索策略的两阶段算法。为了验证该模型的正确性和算法的有效性，将该模型应用于一个包含4条线路和39个站点的网络。结果表明，与分线运营相比，跨线运营可使全网旅客出行时间减少约11.32%，全网换乘流量减少67.09%。最后，通过一组敏感性分析，总结出跨线列车运营的特点，为旅客选择列车服务提供推荐组合。

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引用次数: 0

A comparative study of public transport commuters’ travel choice for autonomous vehicles from a travel experience perspective 基于出行体验视角的公共交通通勤者对自动驾驶汽车出行选择的比较研究

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-02-12 DOI: 10.1080/19427867.2025.2463027

Huanmei Qin , Binhai Yu , Yonghuan Zhang , Meina Cheng , Zhaolin Lu

The application of autonomous vehicles (AVs) will offer a novel travel option for public transport users in the future. To analyze their choice preferences regarding AVs, this study conducted an experience-based stated choice survey in two hypothetical commuting scenarios. The survey was administered in Beijing and a total of 213 samples were collected. Travel choice models incorporating experienced perceptions and attitudes were formulated to identify public transport commuters’ preferences regarding AVs. It is concluded that hands-on travel experience has enhanced commuters’ overall perception of traveling with AVs. Travel cost is their primary concern, followed by travel time and comfort. Holding more positive attitudes and improved perceptions of AVs would increase their choice of SAVs. Additionally, this shift may lead to decreased passenger flow for public transport and increased traffic flow in the road network. The research findings can provide insight into transport policies for future transportation systems.

自动驾驶汽车（AVs）的应用将为未来的公共交通用户提供一种新的出行选择。为了分析他们对自动驾驶汽车的选择偏好，本研究在两种假设的通勤情景中进行了基于经验的陈述选择调查。调查在北京进行，共收集了213份样本。结合经验感知和态度，制定了出行选择模型，以确定公共交通通勤者对自动驾驶汽车的偏好。综上所述，亲身体验增强了通勤者对自动驾驶汽车出行的整体认知。他们最关心的是旅行费用，其次是旅行时间和旅行舒适度。对av持有更积极的态度和更好的认知会增加他们对av的选择。此外，这种转变可能导致公共交通的客流减少，道路网络的交通流量增加。研究结果可以为未来交通系统的交通政策提供见解。

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引用次数: 0

Mobile charging service optimization for electric vehicles 电动汽车移动充电服务优化

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-01-10 DOI: 10.1080/19427867.2024.2448783

Dong Qiao , Guangmin Wang , Meng Xu

Mobile charging stations (MCSs) offer flexible, portable, and scalable alternatives to fixed charging stations (FCSs) for electric vehicles. To develop a cost-effective and efficient mobile charging fleet, this study proposes a bi-objective programming model to address the joint scheduling and routing problem of MCSs considering the layout of FCSs. The objectives are to minimize the total travel distance of MCSs and maximize the system coverage level. The weighted sum method and linear relaxation technique are employed to transform the proposed model into a single-objective integer linear programming model solved by the Gurobi solver. A case study in the Futian District of Shenzhen, China shows that the integration of MCSs results in a 6.7% improvement in the system coverage level. The experimental results provide quantitative insights into the impact of various MCS configurations on objectives. Additionally, the operational data of MCSs offer valuable references for the strategic planning of FCSs.

移动充电站（mcs）为电动汽车提供了灵活、便携和可扩展的替代固定充电站（FCSs）。为了构建一个经济高效的移动充电车队，本研究提出了一种双目标规划模型，以解决考虑fcs布局的mcs联合调度和路由问题。目标是最小化mcs的总行程距离并最大化系统覆盖水平。利用加权和法和线性松弛技术将该模型转化为单目标整数线性规划模型，并用Gurobi求解器求解。以深圳福田区为例研究表明，mcs的整合使系统覆盖水平提高了6.7%。实验结果为不同MCS配置对物镜的影响提供了定量的见解。此外，mcs的运行数据为fcs的战略规划提供了有价值的参考。

引用次数: 0

Understanding work-arrangement choices: factors and implications 理解工作安排选择：因素和影响

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-02-01 DOI: 10.1080/19427867.2025.2456364

Md Asif Hasan Anik , Muhammad Ahsanul Habib

Information and communication technologies (ICTs) have spurred new work arrangements, yet factors influencing these choices remain unclear. This study employs mixed-logit modeling to investigate the determinants of work arrangements—’fully work-from-home (WFH),’ ‘hybrid,’ and ‘no WFH’ – and their impact on activity-travel behavior. Conducted in Halifax Regional Municipality, Nova Scotia, Canada, the study combines travel survey data with Census and built-environment data for analysis. Significant differences are found in activity count, work duration, vehicle kilometers traveled, and commute time among the work-arrangement groups. ‘Hybrid’ and ‘no WFH’ individuals tend to reside closer to downtown, while ‘full WFH’ individuals prefer suburban and rural areas. Results identify individual, household, and accessibility attributes as key determinants, confirming random heterogeneity among respondents. Results suggest shorter auto commute times correlate with higher likelihood of ‘no WFH’ and lower likelihood of ‘full WFH.’ This research aids policymakers and transportation professionals in developing effective travel demand management strategies.

信息和通信技术催生了新的工作安排，但影响这些选择的因素尚不清楚。本研究采用混合logit模型来调查工作安排的决定因素——“完全在家工作”、“混合”和“不在家工作”——以及它们对活动-旅行行为的影响。该研究在加拿大新斯科舍省的哈利法克斯地区进行，将旅行调查数据与人口普查和建筑环境数据相结合进行分析。在活动量、工作时长、车辆行驶公里数和通勤时间上，各工作安排组存在显著差异。“混合型”和“非WFH型”的人往往住在离市中心较近的地方，而“完全WFH型”的人更喜欢住在郊区和农村地区。结果确定了个人、家庭和可及性属性是关键决定因素，证实了受访者之间的随机异质性。研究结果表明，较短的开车通勤时间与较高的“无工作时间”和较低的“完全工作时间”相关。“这项研究有助于决策者和交通专业人士制定有效的出行需求管理策略。”

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引用次数: 0

Integrating virtual obstacle into variable speed limit control for highways in connected traffic environments 基于虚拟障碍的互联交通环境下高速公路可变限速控制

IF 3.3 3区工程技术 Q2 TRANSPORTATION

Transportation Letters-The International Journal of Transportation Research

Pub Date : 2025-09-14 Epub Date: 2025-02-17 DOI: 10.1080/19427867.2025.2464784

Lu Hu , Zikang Chen , Weiyao Xu , Boyu Hou , Haowei Deng , Zhihong Yao

Variable speed limits (VSL), as a global control mechanism, present challenges in accurately regulating traffic flow on highway local road segments. This paper incorporates a novel virtual obstacle (VO) control into VSL with time-varying control sections in a connected environment to balance global and local traffic management. VO control dynamically creates, adjusts, and removes virtual obstacles to form controllable artificial bottlenecks. A highway traffic flow network model is first developed based on a link queue model, considering the effects of VSL and VO. Variable link length describes the time-varying VSL control section and VO position. Then, a multi-objective function is introduced within the model predictive control framework. An improved genetic algorithm is employed to optimize speed limits and control sections of the VSL, as well as the position and width of the VO. Experimental results indicate that the proposed coordinated control method effectively alleviates congestion compared to the VSL control.

可变速度限制作为一种全局控制机制，在高速公路局部路段的交通流量精确调控方面存在挑战。本文将一种新颖的虚拟障碍控制方法引入到具有时变控制段的互联环境中，以平衡全局和局部交通管理。VO控制动态创建、调整和消除虚拟障碍，形成可控的人工瓶颈。首先基于链路队列模型建立了考虑VSL和VO影响的公路交通流网络模型。可变链路长度描述了随时间变化的VSL控制段和VO位置。然后，在模型预测控制框架中引入多目标函数。采用改进的遗传算法优化了VSL的限速和控制路段，以及VO的位置和宽度。实验结果表明，与VSL控制相比，所提出的协调控制方法有效地缓解了拥塞。

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引用次数: 0

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