Multimodal Transportation最新文献_第3页

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 : 2026-03-01 Epub Date: 2025-04-24 DOI: 10.1016/j.multra.2025.100235

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

{"title":"Assessing the economic impacts of labour time in autonomous vehicles","authors":"Jason Wang , Sisi Jian , Edward N. Robson , Vinayak V. Dixit , Taha H. Rashidi","doi":"10.1016/j.multra.2025.100235","DOIUrl":"10.1016/j.multra.2025.100235","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"5 1","pages":"Article 100235"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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 : 2026-03-01 Epub Date: 2025-04-26 DOI: 10.1016/j.multra.2025.100240

Jian Liang, Jintao Ke

{"title":"A Markov decision process framework for order dispatching in on-demand delivery services","authors":"Jian Liang, Jintao Ke","doi":"10.1016/j.multra.2025.100240","DOIUrl":"10.1016/j.multra.2025.100240","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"5 1","pages":"Article 100240"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence, machine learning and deep learning in advanced transportation systems, a review 人工智能、机器学习和深度学习在先进交通系统中的应用综述

Multimodal Transportation Pub Date : 2026-03-01 Epub Date: 2025-05-21 DOI: 10.1016/j.multra.2025.100242

Siavash Saki , Mohsen Soori

{"title":"Artificial intelligence, machine learning and deep learning in advanced transportation systems, a review","authors":"Siavash Saki , Mohsen Soori","doi":"10.1016/j.multra.2025.100242","DOIUrl":"10.1016/j.multra.2025.100242","url":null,"abstract":"<div><div>Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are revolutionizing transportation systems, addressing critical challenges such as congestion, inefficiency, safety, and sustainability. This paper provides a comprehensive review of these transformative technologies, exploring their applications across various domains, including traffic management, autonomous vehicles, smart parking systems, public transit optimization, freight and logistics, sustainability initiatives, safety enhancements, and infrastructure monitoring. Real-world implementations are examined, highlighting their successes and limitations in practical contexts. While AI-driven solutions have demonstrated significant potential, they face persistent challenges, including data scarcity, limited model generalization, and high computational demands that hinder scalability and reliability. Ethical and regulatory issues, including bias, accountability, and privacy concerns, further complicate adoption. This paper identifies these challenges and discusses emerging research opportunities, such as federated learning, multimodal transportation optimization, and energy-efficient AI systems, to address gaps and advance the field. By synthesizing current advancements, identifying limitations, and proposing future directions, this paper emphasizes the critical role of AI, ML, and DL in shaping smarter, safer, and more sustainable transportation systems.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"5 1","pages":"Article 100242"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing maritime transport schedule recovery strategies: a novel approach for speeding up and port-skipping in case of disruption 优化海上运输调度恢复策略：在中断情况下加速和跳港的新方法

Multimodal Transportation Pub Date : 2026-03-01 Epub Date: 2025-04-24 DOI: 10.1016/j.multra.2025.100233

Rouzbeh Purshamsian, S.M.J. Mirzapour Al-e-Hashem, Akbar Esfahanipour, Pouria Tajasob

{"title":"Optimizing maritime transport schedule recovery strategies: a novel approach for speeding up and port-skipping in case of disruption","authors":"Rouzbeh Purshamsian, S.M.J. Mirzapour Al-e-Hashem, Akbar Esfahanipour, Pouria Tajasob","doi":"10.1016/j.multra.2025.100233","DOIUrl":"10.1016/j.multra.2025.100233","url":null,"abstract":"<div><div>In case of disruption to the liner-shipping schedule, vessels cannot arrive at port calls on schedule, which creates a loss in service quality and credibility with a simultaneous increase in operating costs. Liner-shipping companies usually adopt two significant strategies: speeding up and skipping port calls to reduce such issues. This paper presents a mixed-integer nonlinear programming model for the simultaneous use of speed-up and port-skipping strategies for schedule recovery. The model, by taking into consideration lost revenue and the costs of transshipment for skipped ports, departs from the traditional cost-minimization approach by prioritizing profit maximization. It incorporates strategies for speed-up and port-skipping with loading and unloading variables in the process of optimally determining port calls as per demand and profitability. Decision variables on alternative port selections allow multiport alternatives that consider delays and transshipment costs. The nonlinear model is linearized using exact and approximate techniques and solved using CPLEX software. For large-scale cases, a self-learning particle swarm optimization algorithm is employed. Several test problems demonstrate the effectiveness of the metaheuristic. A real-world case is used to validate the model, showing its capability to derive optimal routes and schedules through the concurrent use strategies. The results show that the proposed model minimizes time deviations and operational losses. Moreover, sensitivity analysis highlights that while speed-up is adequate for shorter delays and less viable with high fuel costs, skipping strategies complement speed-up under significant delays, reinforcing the importance of integrated recovery strategies to address disruptions in the maritime transportation industry.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"5 1","pages":"Article 100233"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Defense against multi-path attacks on EV charging networks: A dependency chain analysis and DQN-BASED SOLUTION 电动汽车充电网络多路径攻击防御：依赖链分析及基于dqn的解决方案

Multimodal Transportation Pub Date : 2026-03-01 Epub Date: 2025-09-03 DOI: 10.1016/j.multra.2025.100254

Xin Chen , Jiaxin Peng , Luanjuan Jiang , Jixiang Cheng , Shouyu Wu

{"title":"Defense against multi-path attacks on EV charging networks: A dependency chain analysis and DQN-BASED SOLUTION","authors":"Xin Chen , Jiaxin Peng , Luanjuan Jiang , Jixiang Cheng , Shouyu Wu","doi":"10.1016/j.multra.2025.100254","DOIUrl":"10.1016/j.multra.2025.100254","url":null,"abstract":"<div><div>As electric vehicle (EV) charging infrastructures evolve to become more intelligent, integrated, and interconnected, they encounter escalating cybersecurity threats. Existing studies largely emphasize single-component vulnerabilities while overlooking systemic risks arising from multi-path dependency chains. This paper conceptualizes electric vehicle charging networks as a cyber-physical system (CPS) integrated with power, communication, and control layers. To tackle the issue of multi-path attack propagation within the EV charging network, we present a risk assessment method combined with graph-based system modeling with Deep Q-Networks (DQN). The attacker’s behavior is modeled as a Markov decision process, utilizing DQN to learn optimal attack paths based on cumulative rewards. This method identifies the most vulnerable components and critical propagation pathways, facilitating the development of optimized defense strategies for the deployment of constrained security resources. Comparative experiments indicate that the proposed DQN-based defense strategy outperforms random and traditional dependency-based allocations, leading to diminished cumulative attacker rewards and enhanced network resilience through more efficient resource utilization. These findings can offer practical insights for strengthening the robustness of smart grid ecosystems against multi-stage cyberattacks.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"5 1","pages":"Article 100254"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation-based optimization for transportation system analysis: State-of-the-art research and future endeavors 基于仿真的交通系统分析优化：最新研究和未来努力

Multimodal Transportation Pub Date : 2026-03-01 Epub Date: 2025-07-18 DOI: 10.1016/j.multra.2025.100253

Ziyuan Gu , Bowei Ru , Yifan Li , Wei Ma , Hai L. Vu , Qixiu Cheng , Yuan Kuang

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 : 2025-12-01 Epub Date: 2025-04-25 DOI: 10.1016/j.multra.2025.100229

Ananthakrishnan Vaikkathe, Abdelhamid Benaini, Jaouad Boukachour

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 : 2025-12-01 Epub Date: 2025-04-24 DOI: 10.1016/j.multra.2025.100239

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

{"title":"Holiday ride-hailing at intercity transfer hubs: Where space squeezes and time stretches","authors":"Zhuonan Jiang , Tianqi Gu , Zhuo Chen , Hua Liang , Jiao Jiao , Han Li","doi":"10.1016/j.multra.2025.100239","DOIUrl":"10.1016/j.multra.2025.100239","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 4","pages":"Article 100239"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144632370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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 : 2025-12-01 Epub Date: 2025-04-26 DOI: 10.1016/j.multra.2025.100228

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

{"title":"Uncovering individual-level determinants of shared e-scooting travel frequency","authors":"Sajad Askari , Mahsa Merikhipour , Ehsan Rahimi , Farideddin Peiravian , Abolfazl (Kouros) Mohammadian","doi":"10.1016/j.multra.2025.100228","DOIUrl":"10.1016/j.multra.2025.100228","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 4","pages":"Article 100228"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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 : 2025-12-01 Epub Date: 2025-04-30 DOI: 10.1016/j.multra.2025.100241

Qing Li , Zihao Yan , Ke Lu , Feixiong Liao

{"title":"A duopoly competition problem of shared autonomous vehicles in a multimodal transportation system with government regulation","authors":"Qing Li , Zihao Yan , Ke Lu , Feixiong Liao","doi":"10.1016/j.multra.2025.100241","DOIUrl":"10.1016/j.multra.2025.100241","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 4","pages":"Article 100241"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0