Multimodal Transportation最新文献_第3页

A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation 政府监管下多式联运系统中共享自动驾驶汽车的双寡头竞争问题

Multimodal Transportation

Pub Date : 2025-04-30 DOI: 10.1016/j.multra.2025.100241

Qing Li , Zihao Yan , Ke Lu , Feixiong Liao

Shared autonomous vehicles (SAVs) are expected to revolutionize urban mobility. To explore the complex dynamics of competition and cooperation between operators and other traditional transportation modes, this study proposes a tri-level programming model with equilibrium constraints in a multimodal transportation system. At the upper level, the government regulates the fleet size constraints and hub locations for SAVs. The middle level captures the effect of duopoly competition of SAV operators on fleet size and pricing considering the regulation constraints, which is represented as a 2-player noncooperative game with each player maximizing its profit. At the lower level, travelers’ responses to operational strategies are captured by the dynamic activity-travel assignment model in a multimodal transportation system. A hybrid genetic algorithm, involving a hub-based SAV relocation assignment and a route-swapping algorithm for travelers’ path choice at the lower level, is designed to solve the multi-objective programming problem at the middle level with certain government decisions. A numerical example with two SAV operators shows that the operator with higher-quality vehicles charges more but deploys a smaller fleet compared to the competitor deploying lower-cost vehicles. Government regulations can boost fleet utilization but are less effective when not strict.

共享自动驾驶汽车（sav）有望彻底改变城市交通。为了探索运营商与其他传统运输方式之间竞争与合作的复杂动态，本研究提出了多式联运系统中具有平衡约束的三层规划模型。在上层，政府规定了sav的机队规模限制和枢纽位置。中间层描述了考虑监管约束的航空运输船运营商双寡头竞争对机队规模和价格的影响，表示为每个参与者都最大化其利润的2人非合作博弈。在较低的层次上，多式联运系统中的动态活动-出行分配模型捕捉了乘客对运营策略的反应。设计了一种混合遗传算法，其中包括基于枢纽的交通工具重新分配和下层行人路径选择的路径交换算法，以解决具有特定政府决策的中层多目标规划问题。一个有两个SAV运营商的数值例子表明，与使用低成本车辆的竞争对手相比，拥有高质量车辆的运营商收取更高的费用，但部署的车队规模更小。政府法规可以提高机队利用率，但如果不严格，效果就会降低。

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引用次数: 0

Uncovering individual-level determinants of shared e-scooting travel frequency 揭示共享电动滑板车出行频率的个人层面决定因素

Multimodal Transportation

Pub Date : 2025-04-26 DOI: 10.1016/j.multra.2025.100228

Sajad Askari , Mahsa Merikhipour , Ehsan Rahimi , Farideddin Peiravian , Abolfazl (Kouros) Mohammadian

Shared electric scooter services (SESS) can potentially contribute to sustainable urban transport. However, utilization rates remain low and cast doubt on their cost-effectiveness, energy and resource efficiency, and environmental benefits. While aggregate-level studies have examined shared e-scooter usage, individual-level factors remain underexplored. This study addresses that gap using a behavioral survey of 1,425 responses. We employed a random parameter ordered probit model to quantify the factors that influence the frequency of SESS usage. Study findings reveal a gender and generational gap, with women and older adults less likely to utilize e-scooter sharing compared to men, Millennials, and Gen Z. Additionally, low-income individuals and those without vehicles have a higher probability of being regular users. Multimodal transit users and individuals who receive reduced-fare transit are more likely to use SESS frequently. Individuals who shop online regularly, often a tech‑savvy group, are also more inclined to be frequent users. Furthermore, our findings indicate that built environment attributes are important. Specifically, the results show that living in areas with higher employment entropy, denser road networks, greater accessibility by transit, and highly walkable environments increases the likelihood of frequent SESS use.

共享电动滑板车服务（SESS）可能有助于可持续的城市交通。然而，利用率仍然很低，使人怀疑它们的成本效益、能源和资源效率以及环境效益。虽然总体水平的研究调查了共享电动滑板车的使用情况，但个人水平的因素仍未得到充分探索。这项研究通过对1425人的行为调查来解决这一差距。我们采用随机参数有序概率模型来量化影响SESS使用频率的因素。研究结果揭示了性别和代际差距，与男性、千禧一代和z世代相比，女性和老年人更不可能使用电动滑板车共享。此外，低收入人群和没有车的人更有可能成为定期用户。多式联运用户和获得低价运输的个人更有可能频繁使用SESS。经常在网上购物的人，通常是一个精通技术的群体，也更倾向于成为频繁的用户。此外，我们的研究结果表明，建筑环境属性是重要的。具体而言，研究结果表明，生活在就业熵更高、道路网络更密集、交通可达性更高、步行环境高度适宜的地区，会增加频繁使用SESS的可能性。

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引用次数: 0

A Markov decision process framework for order dispatching in on-demand delivery services 按需配送服务中订单调度的马尔可夫决策过程框架

Multimodal Transportation

Pub Date : 2025-04-26 DOI: 10.1016/j.multra.2025.100240

Jian Liang, Jintao Ke

This article investigates the order dispatching problem in on-demand delivery services, and provides an in-depth analysis of the problem, its associated challenges, and progress in literature and practice. We discuss both the static and dynamic problem settings. In the static context, all information is available from the start, allowing for the formulation of optimization problems that yield theoretical optimal solutions. However, these models fall short in addressing the inherent uncertainties and evolving nature of real-world operations. Dynamic models, in contrast, consider uncertainty over time and is promising for optimizing dispatch policies by considering long-term impacts. Then, a MDP model incorporating four source of uncertainties is illustrated with an example presented. Future research should focus on developing comprehensive frameworks that jointly optimize multiple decisions, such as dispatching, routing, pricing, and workforce planning, to achieve system-wide efficiency and resilience. Moreover, there is a need to better incorporate human behaviors, such as driver acceptance and customer cancellations, into dispatch algorithms to reduce deviations from optimal outcomes.

本文研究了按需配送服务中的订单调度问题，并对该问题、相关挑战以及文献和实践方面的进展进行了深入分析。我们讨论了静态和动态的问题设置。在静态环境中，所有信息从一开始就可用，从而允许制定优化问题，从而产生理论上的最优解。然而，这些模型在解决现实世界操作的固有不确定性和不断变化的性质方面存在不足。相比之下，动态模型考虑了一段时间内的不确定性，并有望通过考虑长期影响来优化调度策略。然后，通过实例说明了包含四个不确定源的MDP模型。未来的研究应侧重于开发综合框架，共同优化多个决策，如调度、路线、定价和劳动力规划，以实现全系统的效率和弹性。此外，还需要更好地将驾驶员接受和客户取消等人类行为纳入调度算法，以减少与最佳结果的偏差。

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引用次数: 0

Solving synchromodal container transportation problem using a genetic algorithm 用遗传算法求解集装箱同运问题

Multimodal Transportation

Pub Date : 2025-04-25 DOI: 10.1016/j.multra.2025.100229

Ananthakrishnan Vaikkathe, Abdelhamid Benaini, Jaouad Boukachour

This paper proposes a Genetic Algorithm(GA) to solve the synchromodal transportation problem. The objective is to find a feasible transportation path for container transportation while minimizing travel duration and

C O_{2}

emissions. The transportation network is modeled in a multigraph and a novel chromosome encoding method, that takes into account the parallel edges is proposed, along with the GA operators. The parameters of the GA are set using Taguchi analysis. The model is validated on instances based on the Seine Axis in France while considering three modes of transport: Barge, Train, and Truck as well as a benchmark instance. The GA finds optimal solutions for small instances and provides good enough solutions with a low deviation from the best-known solution in larger instances.

本文提出了一种求解同步运输问题的遗传算法。目标是为集装箱运输找到一条可行的运输路径，同时最大限度地减少旅行时间和二氧化碳排放。将运输网络建模为多图模型，提出了一种考虑平行边的染色体编码方法和遗传算子。采用田口分析法对遗传算法的参数进行了设置。该模型以法国塞纳河为例进行了验证，同时考虑了驳船、火车和卡车三种运输方式以及一个基准实例。遗传算法为小实例找到最优解，并在较大实例中提供足够好的解决方案，与最知名的解决方案偏差很小。

引用次数: 0

Youth and shared mobility: Unveiling intentions in Kathmandu's gig economy 青年与共享出行：揭示加德满都零工经济的意图

Multimodal Transportation

Pub Date : 2025-04-25 DOI: 10.1016/j.multra.2025.100237

Merina Maharjan , Niranjan Devkota , Ghanashyam Khanal , Prashiddha Basnet , Devid Kumar Basyal , Udaya Raj Paudel , Ramhari Poudyal , Mijala Kayestha , Ranjana Kumari Dnuwar

Youths in the Kathmandu Valley of Nepal have abundant opportunities to experience private motorization through shared transportation without owning vehicles. Ride-sharing is a new mode of transportation in Nepal where young people are an important market segment for vehicle-sharing organisations. In this context, this study investigated youths’ behavioral intentions toward adopting ride-sharing practices. Following the explanatory research methodology, 396 responses were collected from youths in Kathmandu Valley, Nepal. The findings reveal that environmental concerns significantly impact attitudes, subjective norms, and perceived behavioral control. Similarly, subjective norms have a substantial impact on behavioural intentions towards the adoption of ride-sharing that align with the theory of planned behaviour.

尼泊尔加德满都山谷的年轻人有很多机会通过共享交通体验私人机动化，而无需拥有车辆。在尼泊尔，拼车是一种新的交通方式，年轻人是汽车共享组织的重要细分市场。在此背景下，本研究调查了年轻人采用拼车行为的行为意向。根据解释性研究方法，从尼泊尔加德满都谷地的年轻人中收集了396份回复。研究结果表明，环境问题显著影响态度、主观规范和感知行为控制。同样，主观规范对采用与计划行为理论相一致的拼车的行为意图有重大影响。

引用次数: 0

An optimization similarity fuzzy inference method for traffic signal control at an isolated intersection 孤立交叉口交通信号控制的优化相似度模糊推理方法

Multimodal Transportation

Pub Date : 2025-04-25 DOI: 10.1016/j.multra.2025.100234

Mahin Esmaeili , Ali Anjomshoae , Nasser Shahsavari-Pour , Punyaanek Srisurin , Ruth Banomyong

Managing urban traffic is challenging because traffic patterns change unpredictably. Although fuzzy logic-based traffic signal control (TSC) systems like Mamdani and Sugeno work well, they struggle to adjust effectively to real-time traffic changes. This study introduces the Optimization Similarity Fuzzy Inference (OSFI) method, which improves traffic signal control at isolated intersections by continuously adjusting fuzzy rules based on the similarity between actual and desired outcomes. Unlike traditional models, OSFI uses truth tables to dynamically adjust signal timing and phase sequencing based on real-time factors such as vehicle arrival rates and queue lengths. Simulation results show that OSFI reduces average vehicle delays by 1.11–5.73% compared to Mamdani controllers and 0.69–4.84% compared to Sugeno controllers, with traffic throughput improvements of up to 18.75% during heavy traffic. These findings demonstrate OSFI’s ability to consistently improve traffic flow. Future research will focus on expanding OSFI to control networks of intersections and testing its real-world performance to address current challenges related to scalability and efficiency.

管理城市交通具有挑战性，因为交通模式的变化不可预测。尽管Mamdani和Sugeno等基于模糊逻辑的交通信号控制（TSC）系统运行良好，但它们难以有效地适应实时交通变化。本研究引入了优化相似模糊推理（OSFI）方法，该方法基于实际结果与期望结果的相似度，通过不断调整模糊规则来改善孤立交叉口的交通信号控制。与传统模型不同，OSFI使用真值表根据车辆到达率和队列长度等实时因素动态调整信号时序和相位排序。仿真结果表明，OSFI比Mamdani控制器减少了1.11-5.73%的平均车辆延误，比Sugeno控制器减少了0.69-4.84%的平均车辆延误，在交通繁忙的情况下，交通吞吐量提高了18.75%。这些发现证明了OSFI持续改善交通流量的能力。未来的研究将集中于扩展OSFI以控制路口网络，并测试其实际性能，以解决当前与可扩展性和效率相关的挑战。

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引用次数: 0

Holiday ride-hailing at intercity transfer hubs: Where space squeezes and time stretches 假日在城际交通枢纽叫车：空间拥挤，时间延长

Multimodal Transportation

Pub Date : 2025-04-24 DOI: 10.1016/j.multra.2025.100239

Zhuonan Jiang , Tianqi Gu , Zhuo Chen , Hua Liang , Jiao Jiao , Han Li

This study explores the spatiotemporal characteristics of ride-hailing services at intercity transfer hubs in Suzhou, China, examining ride-hailing trip patterns across different land use types, focusing on holidays and regular days. An algorithm is proposed to identify the ride-hailing trips to or from the intercity transfer hubs. During holidays, ride-hailing trips cover longer distances and incur higher fares, with a significant increase in trips related to transportation, tourist areas, and land use for higher education. The spatiotemporal distribution of ride-hailing trips from intercity transfer hubs shows spatial concentration and temporal dispersion during holidays, in contrast to the spatial dispersion and temporal concentration observed on regular days. Specifically, holiday trips are more evenly distributed throughout the day, while regular days exhibit significant morning and evening peaks. It is also found that ride-hailing trips are predominantly concentrated in central business districts, residential areas, and commercial zones, with a noticeable increase in trips to tourist attractions and land use for education during holidays, peaking at the start and end of the holiday period. In contrast, regular days exhibit concentrated travel demand during peak hours, mainly driven by commuting needs. Furthermore, ride-hailing services play a crucial role in areas with limited metro coverage and inconvenient bus transfers, serving as a vital supplement to the urban public transportation system, especially during holidays when passengers often carry large luggage. It highlights a high demand for ride-hailing transfers between different intercity transfer hubs, especially between two local intercity transfer hubs, indicating the need for improved rapid transit connections.

本研究探讨了中国苏州城际换乘枢纽网约车服务的时空特征，考察了不同土地利用类型下的网约车出行模式，重点研究了节假日和工作日。提出了一种识别往返城际换乘枢纽的网约车行程的算法。节假日期间，网约车出行距离更长，费用更高，与交通、旅游区和高等教育用地相关的出行显著增加。城际换乘枢纽网约车出行的时空分布在节假日表现出空间集中和时间分散，而在正常工作日则表现出空间分散和时间集中。具体来说，假日旅行在一天中分布更均匀，而正常日子则表现出明显的早晚高峰。研究还发现，网约车出行主要集中在中央商务区、居民区和商业区，假期期间旅游景点出行和教育用地使用明显增加，在假期开始和结束时达到峰值。相比之下，普通工作日在高峰时段的出行需求集中，主要受通勤需求的驱动。此外，网约车服务在地铁覆盖范围有限、公交换乘不方便的地区发挥着至关重要的作用，是城市公共交通系统的重要补充，尤其是在乘客经常携带大件行李的假期。它强调了不同城际换乘中心之间的乘车换乘需求很高，特别是在两个本地城际换乘中心之间，这表明需要改善快速交通连接。

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引用次数: 0

Reinforcement learning based mobile energy disseminator dispatching for on-road electric vehicle charging 基于强化学习的道路电动汽车充电移动能量分发器调度

Multimodal Transportation

Pub Date : 2025-04-24 DOI: 10.1016/j.multra.2025.100232

Jiaming Wang , Jiqian Dong , Haotian Shi , Shreyas Sundaram , Samuel Labi , Sikai Chen

The rapid growth of electric vehicles (EVs) exacerbates the existing challenges of vehicle range anxiety and charging infrastructure inadequacy. To address these concerns, promising solutions have emerged, including vehicle-to-vehicle dynamic wireless charging (V2V-DWC) technologies, particularly Mobile Energy Disseminators (MEDs). A MED is a large vehicle bearing non-contact technology equipment that charges participating EVs in its proximity. This paper establishes a platform for reliable simulation of the energy transfer between the MED and the EV, develops models that describe EV battery consumption and V2V charging dynamics, and develops an AI-based framework for MED dispatching. The first component of the developed platform is a realistic reinforcement learning (RL) based highway environment termed ``ChargingEnv.'' This component incorporates reliable charging simulation that accounts for two common practical issues in wireless charging deployment: charging panel misalignment and realistic EV battery consumption patterns. The second component involves multiple deep RL benchmark models trained in ``ChargingEnv'' to maximize the MED deployment charging service quality within charging resource constraints. Findings from numerical experiments demonstrate that the model trained in the framework substantially alleviates battery depletion concerns. The framework can serve as a tool for road agencies or private-sector investors to efficiently plan their MED deployments.

电动汽车的快速发展加剧了现有的里程焦虑和充电基础设施不足的挑战。为了解决这些问题，有希望的解决方案已经出现，包括车对车动态无线充电（V2V-DWC）技术，特别是移动能量传播器（med）。MED是一种大型车辆轴承非接触式技术设备，可为附近参与的电动汽车充电。建立了MED与电动汽车之间能量传输的可靠仿真平台，建立了描述电动汽车电池消耗和V2V充电动态的模型，并开发了基于人工智能的MED调度框架。开发平台的第一个组成部分是一个基于现实强化学习（RL）的公路环境，称为“ChargingEnv”。“该组件集成了可靠的充电模拟，可以解决无线充电部署中的两个常见实际问题：充电面板错位和现实的电动汽车电池消耗模式。第二个组件涉及在“ChargingEnv”中训练的多个深度RL基准模型，以在收费资源约束下最大限度地提高MED部署收费服务质量。数值实验结果表明，在该框架下训练的模型大大减轻了对电池耗尽的担忧。该框架可作为道路机构或私营部门投资者有效规划其MED部署的工具。

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引用次数: 0

Assessing the economic impacts of labour time in autonomous vehicles 评估自动驾驶汽车劳动时间对经济的影响

Multimodal Transportation

Pub Date : 2025-04-24 DOI: 10.1016/j.multra.2025.100235

Jason Wang , Sisi Jian , Edward N. Robson , Vinayak V. Dixit , Taha H. Rashidi

Previous studies have analysed the impacts of the introduction of autonomous vehicles on transport networks and estimated the safety, congestion, freight, parking and vehicle ownership impacts to social welfare and the economy. However, there appears to be a gap in the literature on the economic impacts of individuals allocating travel time in an autonomous vehicle to labour activities. This additional labour time could then have resulting impacts to productivity and the broader economy. This paper addresses this gap through the development of a novel microeconomic model incorporating time use in autonomous vehicles. The model captures an individual’s consumption behaviour, demand for leisure and supply of labour while accounting for the allocation of travel time to labour and leisure. It is an extension of existing microeconomic models of time use for two features: (1) travel utility, and (2) labour while travelling. This model is then implemented in an integrated computable general equilibrium and transport model for Sydney, Australia, and is tested to understand the order of magnitude of impacts. From this model, the increase in autonomous vehicle penetration rate and the resultant increases to household budget from travelling wages will result in a total welfare increase but with a decreasing rate, which are mainly due to congestion effects. Interestingly, the congestion effects also result in the production and value of time first increase, followed by a decrease, which are counter intuitive.

之前的研究分析了引入自动驾驶汽车对交通网络的影响，并估计了安全、拥堵、货运、停车和车辆所有权对社会福利和经济的影响。然而，关于个人将自动驾驶汽车的旅行时间分配给劳动活动的经济影响，文献中似乎存在空白。这种额外的劳动时间可能会对生产率和更广泛的经济产生影响。本文通过开发一种新的微观经济模型来解决这一差距，该模型将自动驾驶汽车的时间使用纳入其中。该模型捕捉了个人的消费行为、休闲需求和劳动供给，同时考虑了劳动和休闲的旅行时间分配。它是现有微观经济时间使用模型的延伸，具有两个特征：(1)旅行效用，(2)旅行时的劳动。然后在澳大利亚悉尼的综合可计算一般平衡和运输模型中实施该模型，并对其进行测试以了解影响的数量级。从这个模型来看，自动驾驶汽车普及率的提高以及由此带来的旅行工资对家庭预算的增加将导致总福利增加，但下降率，这主要是由于拥堵效应。有趣的是，拥堵效应还会导致时间的产出和价值先增加后减少，这是与直觉相反的。

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引用次数: 0

Analysis of the impact of E-commerce activities on residents' commute trips 电子商务活动对居民通勤出行的影响分析

Multimodal Transportation

Pub Date : 2025-04-24 DOI: 10.1016/j.multra.2025.100230

Gengze Li , Changjian Liu , Rufeng Liao , Zhouhao Wu , Huapu Lu

E-commerce has the capacity to redirect certain individuals from physical transportation to online services, gradually altering human travel behaviours. This paper establishes a theoretical model to analyse the impact of e-commerce on the Land Use and Transport Interaction (LUTI) model. To achieve this goal, we employ the Metropolitan Activity Relocation Simulator (MARS) - attractiveness by car model to assess the sensitivity to e-commerce. The results demonstrate that e-commerce significantly affects the curve of attractiveness by car, and there is a positive correlation between them. The revised model offers insight into and explanation of how e-commerce impacts the LUTI model, providing a valuable tool for policymakers and planners to adapt to the current situation and effectively address issues.

电子商务有能力将某些人从实体运输转向在线服务，逐渐改变人类的旅行行为。本文建立了一个理论模型来分析电子商务对土地利用与交通相互作用（LUTI）模型的影响。为了实现这一目标，我们采用大都市活动迁移模拟器(MARS) -汽车吸引力模型来评估对电子商务的敏感性。结果表明，电子商务显著影响了乘车吸引力曲线，两者之间存在正相关关系。修正后的模型提供了对电子商务如何影响LUTI模型的洞察和解释，为政策制定者和规划者适应当前形势并有效解决问题提供了有价值的工具。

引用次数: 0