Multimodal Transportation最新文献

{"title":"Evaluating defensive driving behaviour based on safe distance between vehicles: A case study using computer vision on UAV videos at urban roundabout","authors":"Yagnik M. Bhavsar ,&nbsp;Mazad S. Zaveri ,&nbsp;Mehul S. Raval ,&nbsp;Shaheriar B. Zaveri","doi":"10.1016/j.multra.2025.100227","DOIUrl":"10.1016/j.multra.2025.100227","url":null,"abstract":"<div><div>While driving, maintaining a sufficient distance helps reduce collision risk. A time gap of two or three seconds on urban roads from a vehicle ahead is advised in defensive driving. The scenario becomes even more challenging in densely populated and developing countries because of limited road infrastructure, lane indiscipline, and heterogeneous traffic. The safe distance between vehicles and the driver’s reaction can be used as surrogate safety measures (SSMs) to evaluate defensive driving behaviour. This paper presents a case study evaluating defensive driving behaviour using the vision-based methodology and UAV video. This paper proposes two novel SSMs based on distance and acceleration and studies defensive driving behaviour, such as “for how long did a vehicle keep driving under another vehicle’s blind spots?” and “how is a vehicle driving (an interaction pattern) when another vehicle ahead is in its stopping distance range?.” Finally, each driver’s star rating depends on their interactions with other vehicles. We observed that around 48 % of the vehicles did not follow defensive driving practices. In our vehicle inter-class interaction analyses, we also found 16.6 % Rear-End, 6.3 % Side-Swipe, and 1.5 % Angled collision risks occurred between car-car, car-car, and 2Wheeler(2W)-car, respectively. Our methodology could help traffic law enforcement agencies and policy-makers elevate road traffic safety by taking counter-measures against the low-star vehicle categories in developing countries. Example videos of star rating are available on <span><span>https://www.youtube.com/@YagnikBhavsar</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100227"},"PeriodicalIF":0.0,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902344","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":"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":"2025-03-26","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":"2025-03-22","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":"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":"2025-03-22","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}

{"title":"Evaluating the usefulness of VGI for citizen co-producing city services from citizen perspective: A case study of crowdsourcing pedestrian navigation","authors":"Shanqi Zhang ,&nbsp;Maju Sadagopan ,&nbsp;Xiao Qin","doi":"10.1016/j.multra.2025.100223","DOIUrl":"10.1016/j.multra.2025.100223","url":null,"abstract":"<div><div>With over 50 % of the world's population now living in the cities and the number continuing to grow, cities are increasingly responsible for delivering services to people and businesses. Recent developments in volunteered geographic information (VGI) have provided new opportunities for improving city services by enabling citizens instantly and collectively share and report issues. However, the usefulness of VGI for such use has not been evaluated from a citizen perspective. This paper aims to bridge this research gap through a case study that innovatively uses geosocial media, as an example of VGI, for reporting accessibility issues to local governments and for providing customized navigation services to the general public. Particularly, a study website was developed that allows citizen participants to evaluate the usefulness of geosocial media for issue reporting and for pedestrian navigation. The results suggest that citizens consider geosocial media useful for helping them maneuver dynamic urban environments and for providing a convenient tool for issue reporting. These results suggest that citizens evaluate the usefulness of VGI differently from government officials and that VGI can facilitate government-citizen communication as well as the provision of customized public services, both of which are important to the development of smart cities.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100223"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738695","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":"2025-03-18","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":"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":"2025-03-14","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":"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":"2025-03-10","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":"Quantifying the life-saving impact of seatbelt usage: A random forest analysis of unobserved heterogeneity and latent risk factors in vehicular fatalities","authors":"Ittirit Mohamad","doi":"10.1016/j.multra.2025.100221","DOIUrl":"10.1016/j.multra.2025.100221","url":null,"abstract":"<div><div>Seatbelt use significantly reduces the severity of injuries and fatalities in vehicular accidents. This study leverages the Random Forest algorithm to evaluate the impact of seatbelt usage on fatality probabilities in Thailand, with a novel focus on drivers who caused the accidents. The model demonstrated high accuracy, correctly identifying 95.10 % of non-fatal cases and 91.60 % of fatal cases, though some misclassifications were observed. A key contribution of this research is the identification of hidden risk factors influencing fatality rates, including temporal patterns that revealed a surge in fatalities after 17:00, with increased risks associated with non-seatbelt use during late evening and early morning hours. Younger drivers, particularly active at night, were found to exhibit higher rates of non-seatbelt usage and were more likely to be involved in severe accidents. These findings highlight the critical need for targeted seatbelt enforcement and safety interventions during high-risk periods, especially among younger drivers who are at fault in accidents.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100221"},"PeriodicalIF":0.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705819","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":"Autonomous fleet management system in smart ports: Practical design and analytical considerations","authors":"Rui Chen ,&nbsp;Jing Zhang ,&nbsp;Hua Wang","doi":"10.1016/j.multra.2025.100211","DOIUrl":"10.1016/j.multra.2025.100211","url":null,"abstract":"<div><div>Automated horizontal transportation in container terminals represents a significant advancement in the field of autonomous commercial vehicles. Traditionally, these systems rely on the individual intelligence of each vehicle, similar to autonomous passenger vehicles. However, recent uses of automated technology in select container terminals have demonstrated the benefits of integrating vehicles with a centralized Autonomous Fleet Management System (AFMS). This collaboration not only mitigates information silos but also enhances operational efficiency, safety, and fosters fleet cluster intelligence. This study examines current applications in automated container terminals, analyses practical scenarios, and identifies the essential characteristics of an effective AFMS to support horizontal transportation management. The insights from this comprehensive analysis assist port operators in designing and operating their systems and help scholars better understand and define research questions in this field.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 3","pages":"Article 100211"},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600762","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}