Multimodal Transportation最新文献

{"title":"Corrigendum to Autonomous fleet management system in smart ports: Practical design and analytical considerations [Multimodal Transp. 4 (2025) /100211]","authors":"Rui Chen , Jing Zhang , Hua Wang","doi":"10.1016/j.multra.2025.100267","DOIUrl":"10.1016/j.multra.2025.100267","url":null,"abstract":"","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 4","pages":"Article 100267"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790179","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}

{"title":"Resilience assessment for bus-metro multimodal networks considering various attacking scenarios","authors":"Wenjun Jia ,&nbsp;Ke Zhang ,&nbsp;Xiaolei Ma ,&nbsp;Meng Li","doi":"10.1016/j.multra.2025.100238","DOIUrl":"10.1016/j.multra.2025.100238","url":null,"abstract":"<div><div>Multimodal transportation systems significantly enhance travel convenience but also introduce vulnerabilities. Disruptions in one segment can cascade across the network, compromising overall network performance. These disruptions, often stemming from diverse attack scenarios, highlight the critical need to study and enhance resilience in transportation networks. This paper introduces a resilience assessment model that considers the characteristics of abrupt events in passenger networks. A series of attack scenarios are set up, categorized by the extent of node capability degradation, the number and types of nodes subjected to attack, and the duration of the attack. Focusing on Beijing's bus-metro multimodal network, the results show that in certain scenarios, recovery performance is worse when passengers transfer to both nearby bus and subway stations after a subway station attack, compared to transferring only to bus stations. This is due to longer walking transfer times and higher passenger volumes at subway stations, which increase flow delays and risk cascading failures. Furthermore, off-peak node failures also worsen network performance due to reduced scheduling frequency. Consequently, the entire transportation system requires an extended recovery period. These insights are critical for informing targeted emergency recovery strategies in the aftermath of public transportation disruptions.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 4","pages":"Article 100238"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549015","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}

{"title":"An optimization similarity fuzzy inference method for traffic signal control at an isolated intersection","authors":"Mahin Esmaeili ,&nbsp;Ali Anjomshoae ,&nbsp;Nasser Shahsavari-Pour ,&nbsp;Punyaanek Srisurin ,&nbsp;Ruth Banomyong","doi":"10.1016/j.multra.2025.100234","DOIUrl":"10.1016/j.multra.2025.100234","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 4","pages":"Article 100234"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144535775","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}

{"title":"Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data","authors":"Teng Li ,&nbsp;Zhuo Chen ,&nbsp;Shuli Luo ,&nbsp;Alexa Delbosc","doi":"10.1016/j.multra.2025.100243","DOIUrl":"10.1016/j.multra.2025.100243","url":null,"abstract":"<div><div>This study investigates the impacts of urban heat island (UHI) effects on active travel by leveraging social media data. A multiscale geographically weighted regression (MGWR) model is utilized to investigate the spatial heterogeneity of integrated influences of UHI effects, built environment, and sociodemographic factors on travel frequency for both peri-summer and all-year trips. The investigation is showcased in Greater Melbourne, Australia, where Twitter posts related to active travel were collected and analyzed to identify active travelers’ travel frequency in different suburbs. The results reveal that UHI effects had a significant negative impact on all suburbs, with greater intensity during peri-summer trips. Moreover, the results proved the spatial heterogeneity of the influence of UHI effects on active trips, with a more intensive influence in residential regions with high urban heat index values. Additionally, the density of tram stops, parkland areas, population density, and young adults had significant positive effects, while the unemployment rate and dwellings with one motor vehicle had negative impacts. This study contributes to the field of travel behavior analysis by completing location-contained social media data. Moreover, it identifies areas heavily impacted by UHI effects, enabling targeted measures such as expanding green spaces, using cooling materials, and enhancing energy practices to reduce UHI effects and promote a sustainable urban environment.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 4","pages":"Article 100243"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631798","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}

{"title":"STG-LSTM: Spatial-temporal graph-based long short-term memory for vehicle trajectory prediction","authors":"Daniela Daniel Ndunguru ,&nbsp;Fan Xing ,&nbsp;Chrispus Zacharia Oroni ,&nbsp;Arsenyan Ani ,&nbsp;Chao Li","doi":"10.1016/j.multra.2025.100222","DOIUrl":"10.1016/j.multra.2025.100222","url":null,"abstract":"<div><div>Vehicle trajectory prediction plays a crucial role in enhancing the safety, efficiency, and effectiveness of intelligent transportation systems. Accurate predictions of future vehicle movements are essential for applications such as autonomous driving, traffic management, and collision avoidance systems. However, many existing methods either focus solely on spatial or temporal dimensions, neglecting the dynamic interactions between vehicles, which reduces prediction accuracy, especially in complex traffic scenarios. To address these limitations, the study proposes a Spatial-Temporal Graph-Based Long Short-Term Memory model, which integrates graph convolutional networks with long short-term memory networks to effectively capture both spatial relationships and temporal dependencies in vehicle trajectories. The proposed model employs a proximity-based method to construct dynamic adjacency matrices that represent real-time vehicle interactions. To capture spatial dependencies between vehicles, the study uses graph convolutional networks to model the relationships between neighboring vehicles. The long short-term memory network is then applied to capture temporal dynamics by learning the sequential dependencies in vehicle movement patterns. The output from the long short-term memory network is passed through a fully connected layer, which generates trajectory predictions for each vehicle. The study experimental results demonstrate that the proposed model outperforms existing state-of-the-art models across various prediction metrics. Specifically, at 3s and 4s prediction horizons, the model reduces the root mean square error by 22.4 % and 25.5 %, respectively, compared to the best performing interaction-aware long short-term memory model. At the 5s prediction horizon, the model achieves a significant root mean square error reduction of 26.6 %. These findings highlight the model's potential to improve safety and decision-making in autonomous driving systems and traffic management applications.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100222"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable urban transportation planning: Integrating an electrified metro system into Kampala metropolis","authors":"Ismail Kimuli ,&nbsp;John Baptist Kirabira ,&nbsp;Ismael Nkambwe ,&nbsp;Saadat L.K. Nakyejwe ,&nbsp;Michael Lubwama ,&nbsp;Kasimu Sendawula ,&nbsp;Nashua K Nabaggala","doi":"10.1016/j.multra.2025.100220","DOIUrl":"10.1016/j.multra.2025.100220","url":null,"abstract":"<div><div>With the United Nations (UN) predicting that 60% of the global population will reside in cities by 2050, sustainable transportation planning is a prominent global trend. This study examines Kampala's transportation sustainability and addresses existing knowledge gaps. It leverages the TIMES-VEDA model, an acronym for “The Integrated MARKAL-EFOM System - Versatile Data Analyst.” TIMES-VEDA is an engineering optimizer used to explore four scenarios: Business-as-Usual (BAU), Reduction in Electricity Consumption (REC), Renewable Electricity Portfolio (REP), and Carbon Reduction Target (CRT). These scenarios analyze the inherent aspects of the Kampala metropolis energy system, providing a foundation for evidence-based decision-making. The approach aligns with the United Nations’ Sustainable Development Goals (UN's SDGs 7, 11, &amp; 13), Uganda's Vision 2040, and the third National Development Plan (NDPIII). The analysis demonstrates that sustainability is within range and highlights the imperative of a holistic approach, the potential of mass rapid transit, anchored by an electrified metro system, to advance green mobility. It sheds light on sustainable practices and trade-offs among distinctive pathways, suggesting a mix of policy measures to combat climate change. The KAMPALA-TIMES model, a bottom-up framework, reveals that a region-specific policy package, particularly the CRT scenario, achieves significant decarbonization, promoting eco-friendly multimodal transportation and paving the way for a more sustainable future for Kampala until 2060. The findings inform policy on urban planning and sustainable transportation that is adaptable elsewhere, ensuring long-term environmental and economic resilience.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100220"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring walkability patterns in diverse urban landscapes: A comprehensive spatial geographic analysis of a megacity in Thailand","authors":"Pawinee Iamtrakul ,&nbsp;Sararad Chayphong ,&nbsp;Varameth Vichiensan ,&nbsp;Paramet Luathep ,&nbsp;Nuwong Chollacoop ,&nbsp;Atsushi Fukuda ,&nbsp;Tuenjai Fukuda","doi":"10.1016/j.multra.2025.100226","DOIUrl":"10.1016/j.multra.2025.100226","url":null,"abstract":"<div><div>Urbanization, urban sprawl, and the increasing population contribute to challenges in density and diversity within each metropolitan area, creating the need to find sustainable solutions for urban transport. This study investigates the correlation between the urban context and walkability, specifically in Bangkok, Thailand. A spatial geographic approach was employed for urban typology analysis, utilizing multivariate clustering, including walkability assessment through a geographic information system and urban and mobility indices. The findings of the urban context analysis revealed five distinct forms: rural, rural town, suburban, urban, and urban core, each characterized by varying levels of walking abilities. The findings contribute to understanding the nature of activities characteristic of both urban environments and mobility in terms of spatial environmental conditions present in each urban context. Urban and transport planners should explore strategies that align with the specific environmental context of each area to promote walking effectively.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100226"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A coordinated passenger flow control model for urban rail transit considering willingness to board","authors":"Guanghui Su ,&nbsp;Pei Li ,&nbsp;Deheng Lian ,&nbsp;Pengli Mo","doi":"10.1016/j.multra.2025.100225","DOIUrl":"10.1016/j.multra.2025.100225","url":null,"abstract":"<div><div>Effective control of passenger flow is essential for optimizing train capacity utilization in urban rail transit systems, enhancing operational efficiency and service quality. Passenger travel demand patterns and platform preferences significantly influence train capacity utilization, as passengers often exhibit preferences for specific trains, reflecting their willingness to board. This paper proposes a coordinated passenger flow control model that incorporates passengers’ willingness to board, further improving travel efficiency and fairness. The model applies the First-Come-First-In (FCFI) rule to represent passenger demand within flow control strategies and introduces a mechanism that permits the limited left-behind passenger volume to prevent trip abandonment caused by restrictive controls.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100225"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807329","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}

{"title":"A learning-to-rank method to identify crash hotspots based on large-scale ride-hailing crash data","authors":"Xiang Wen ,&nbsp;Pengfei Cui ,&nbsp;Yuanwei Luo ,&nbsp;Runbo Hu ,&nbsp;Yanyong Guo","doi":"10.1016/j.multra.2025.100219","DOIUrl":"10.1016/j.multra.2025.100219","url":null,"abstract":"<div><div>Machine learning have been widely used in crash hotspot identification due to its superior prediction accuracy. Existing studies mainly treat hotspot identification as a classification or regression problem. This paper proposed a learning-to-rank(LTR) method to identify hotspots on a single trip and deviced a risk warning system based on the method to verify its effectiveness in crash mitigation. Ride-hailing crashes for a year in China were used as training and testing data. Three kinds of features were extracted to describe the safety level of each road segments, namely, road design features, time-related features, and traffic features. LambdaMART, a pairwise LTR algorism was applied to rank the road segments based on the extracted features. The experiment results suggested that the proposed LTR model outperforms three traditional machine learning models in terms of NDCG@10. The proposed LTR risk warning system integrated with Didi's ride-hailing service outperforms traditional zone-based warning system and bring a significant drop in Average Death Rate per Billion Kilometers.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100219"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The comparison of main features and minimum service standards of air-rail integrated services (ARIS) implementation in Indonesia","authors":"Danny Setiawan ,&nbsp;Sigit Priyanto ,&nbsp;Mukhammad Rizka Fahmi Amrozi ,&nbsp;Imam Muthohar","doi":"10.1016/j.multra.2025.100224","DOIUrl":"10.1016/j.multra.2025.100224","url":null,"abstract":"<div><div>Air-rail integrated services (ARIS) is a recent innovation in multimodal transport integration that combines air and rail transportation. This study investigates fundamental questions related to the development of ARIS in Indonesia: (1) does the existence of ARIS positively impact airplane passenger satisfaction? (2) how can airplane passenger satisfaction with ARIS be maintained and optimized? This study explores ARIS passenger satisfaction based on occupancy rate and social media big data. Optimization of ARIS in Indonesia is based on implementing main features and aligning them with minimum service standards (MSS) regulations by applying comparative methods and factor analysis. Passenger complaints are related to error systems while attempting to book and pay for tickets online using the airport train mobile application. In addition, there is no infant fare policy, travel schedules that cause long waiting times, and improvement in the quality of customer services. Standardization of the main features of ARIS in Indonesia is urgently needed and will provide time and cost-efficiency benefits for airplane passengers.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100224"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}