Pub Date : 2025-03-01Epub Date: 2025-01-10DOI: 10.1016/j.multra.2025.100197
Richard Dzinyela , Bahar Dadashova , Grant Westfall , Subasish Das , Chiara Silvestri-Dobrovolny , Emmanuel Kofi Adanu , Dominique Lord
Crashes involving motorcyclists account for a significant portion of traffic-related injuries and fatalities. Despite motorcycles making only three percent of all registered vehicles, motorcyclists account for 14 percent of all roadway fatalities. As the number of motorcyclists increase, there is an urgent need to understand the factors that affect the severity of injuries they sustain in crashes. In this paper, we use cluster correspondence analysis (CCA) and hierarchical binary logit model to explore the factors associated with motorcyclists’ crash injury severities in Utah between 2016 and 2020. Cluster correspondence analysis was used to cluster the crash data into seven groups, while hierarchical binary logit model was used to identify the significant factors that contributed to the injury severity of motorcycle crashes. The results of this study indicate that among the crash-contributing factors the motorcyclist age, roadway alignment, roadside safety systems and temporal factors significantly contribute to motorcyclist crash severities. The model results further account for the correlation of variables within the clusters in the crash data. With the deeper understanding of the relationship between crash factors and injury severity in this study, the findings can help decision makers to implement targeted countermeasures to improve motorcyclist safety.
{"title":"Analysis of motorcyclists crash severity using cluster correspondence and hierarchical binary logit models","authors":"Richard Dzinyela , Bahar Dadashova , Grant Westfall , Subasish Das , Chiara Silvestri-Dobrovolny , Emmanuel Kofi Adanu , Dominique Lord","doi":"10.1016/j.multra.2025.100197","DOIUrl":"10.1016/j.multra.2025.100197","url":null,"abstract":"<div><div>Crashes involving motorcyclists account for a significant portion of traffic-related injuries and fatalities. Despite motorcycles making only three percent of all registered vehicles, motorcyclists account for 14 percent of all roadway fatalities. As the number of motorcyclists increase, there is an urgent need to understand the factors that affect the severity of injuries they sustain in crashes. In this paper, we use cluster correspondence analysis (CCA) and hierarchical binary logit model to explore the factors associated with motorcyclists’ crash injury severities in Utah between 2016 and 2020. Cluster correspondence analysis was used to cluster the crash data into seven groups, while hierarchical binary logit model was used to identify the significant factors that contributed to the injury severity of motorcycle crashes. The results of this study indicate that among the crash-contributing factors the motorcyclist age, roadway alignment, roadside safety systems and temporal factors significantly contribute to motorcyclist crash severities. The model results further account for the correlation of variables within the clusters in the crash data. With the deeper understanding of the relationship between crash factors and injury severity in this study, the findings can help decision makers to implement targeted countermeasures to improve motorcyclist safety.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100197"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132801","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}
Pub Date : 2025-03-01Epub Date: 2025-01-09DOI: 10.1016/j.multra.2025.100192
Nicholas N. Ferenchak, Brady A. Woods
Bus rapid transit (BRT) is an increasingly popular form of public transportation that seeks to achieve the speed and reliability of fixed rail with the flexibility and affordability of a bus system. In this paper, we examine safety outcomes before and after the construction of BRT infrastructure, specifically investigating how different crash types and contributing factors changed for all motor vehicle crashes and for pedestrian crashes. New Mexico Department of Transportation (NMDOT) provided crash data for the Central Avenue corridor of the Albuquerque Rapid Transit (ART) system in Albuquerque, NM. The construction of ART correlated with significant reductions in crashes attributed to excessive speed (for all modes) and left turning vehicles (for all modes and pedestrians). Crashes attributed to excessive speed decreased by 19.1 % (p = 0.059) after ART construction while crashes attributed to excessive speed resulting in fatal or serious (KA) injury decreased 100.0 % (p < 0.001). Although the number of KA pedestrian crashes increased 15.2 % (p = 0.272), KA pedestrian crashes involving a left-turning motor vehicle decreased by 80.0 % (p = 0.070). For all modes, crashes involving left-turning vehicles decreased by 34.8 % (p < 0.001) and crashes involving left-turning vehicles resulting in a KA injury decreased by 87.5 % (p = 0.009). This research provides insights into the multimodal traffic safety implications of the burgeoning public transportation mode of BRT.
{"title":"Changes in crash types and contributing factors after bus rapid transit (BRT) infrastructure installation in Albuquerque, New Mexico","authors":"Nicholas N. Ferenchak, Brady A. Woods","doi":"10.1016/j.multra.2025.100192","DOIUrl":"10.1016/j.multra.2025.100192","url":null,"abstract":"<div><div>Bus rapid transit (BRT) is an increasingly popular form of public transportation that seeks to achieve the speed and reliability of fixed rail with the flexibility and affordability of a bus system. In this paper, we examine safety outcomes before and after the construction of BRT infrastructure, specifically investigating how different crash types and contributing factors changed for all motor vehicle crashes and for pedestrian crashes. New Mexico Department of Transportation (NMDOT) provided crash data for the Central Avenue corridor of the Albuquerque Rapid Transit (ART) system in Albuquerque, NM. The construction of ART correlated with significant reductions in crashes attributed to excessive speed (for all modes) and left turning vehicles (for all modes and pedestrians). Crashes attributed to excessive speed decreased by 19.1 % (<em>p</em> = 0.059) after ART construction while crashes attributed to excessive speed resulting in fatal or serious (KA) injury decreased 100.0 % (<em>p</em> < 0.001). Although the number of KA pedestrian crashes increased 15.2 % (<em>p</em> = 0.272), KA pedestrian crashes involving a left-turning motor vehicle decreased by 80.0 % (<em>p</em> = 0.070). For all modes, crashes involving left-turning vehicles decreased by 34.8 % (<em>p</em> < 0.001) and crashes involving left-turning vehicles resulting in a KA injury decreased by 87.5 % (<em>p</em> = 0.009). This research provides insights into the multimodal traffic safety implications of the burgeoning public transportation mode of BRT.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100192"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143133442","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}
Pub Date : 2025-03-01Epub Date: 2025-01-08DOI: 10.1016/j.multra.2025.100195
Mason D. Gemar , Shidong Pan , Zhanmin Zhang , Randy B. Machemehl
Over the past decade, many municipalities have begun to replace incandescent lamps in their traffic signals with light emitting diode (LED) arrays. While LED technology boasts longer lifetimes and superior performance over their counterparts, there are many limitations involved in both testing and evaluating their reliability. As such, the methodology and subsequent analysis procedures used to evaluate the reliability of traffic signal lamps along a corridor is proposed. To accomplish this task, the progression of the reliability assessment from individual lamp to the entire signal light system for a corridor is demonstrated. Furthermore, due to the nature of these systems and reliability assessment strategies, it is suggested that fuzzy, or more specifically, profust reliability theory could be applied to effectively analyze LED arrays, as well as corridor-wide signal light systems. Preliminary case study results, coupled with field observations of partially burned-out LED arrays, support this hypothesis.
{"title":"Fuzzy reliability theory analysis of traffic signal lamp performance","authors":"Mason D. Gemar , Shidong Pan , Zhanmin Zhang , Randy B. Machemehl","doi":"10.1016/j.multra.2025.100195","DOIUrl":"10.1016/j.multra.2025.100195","url":null,"abstract":"<div><div>Over the past decade, many municipalities have begun to replace incandescent lamps in their traffic signals with light emitting diode (LED) arrays. While LED technology boasts longer lifetimes and superior performance over their counterparts, there are many limitations involved in both testing and evaluating their reliability. As such, the methodology and subsequent analysis procedures used to evaluate the reliability of traffic signal lamps along a corridor is proposed. To accomplish this task, the progression of the reliability assessment from individual lamp to the entire signal light system for a corridor is demonstrated. Furthermore, due to the nature of these systems and reliability assessment strategies, it is suggested that fuzzy, or more specifically, profust reliability theory could be applied to effectively analyze LED arrays, as well as corridor-wide signal light systems. Preliminary case study results, coupled with field observations of partially burned-out LED arrays, support this hypothesis.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100195"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509645","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}
Pub Date : 2025-03-01Epub Date: 2024-12-20DOI: 10.1016/j.multra.2024.100184
Jing Wang , Changjian Liu , Zhouhao Wu , Rufeng Liao , Gengze Li , Huapu Lu
With the acceleration of urbanization and continuous population growth in China, transportation issues in central cities, especially large and mega-cities, have become increasingly prominent. A series of problems such as economic efficiency decline and reduced residents' well-being caused by traffic congestion have become significant factors constraining the sustainable development of cities. As a core component of the urban transportation system, the prioritized development of urban public transportation is crucial for alleviating traffic congestion, improving environmental quality, and enhancing residents' quality of life. However, from the beginning of 2023, the share of public transportation in residents' travel has gradually decreased, with the total passenger volume still lower than the same period in 2019. In response to the challenges faced by the public transportation system under the new circumstances, this paper reviews the necessity of prioritized development of urban public transportation, analyzes the reasons for the decline in the share of public transportation in residents' overall travel modes, and proposes targeted suggestions. On this basis, the paper explores the intrinsic connection between the strategy of prioritizing public transportation development and sustainable urban development.
{"title":"The roadmap and strategy for prioritizing the development of public transport in China","authors":"Jing Wang , Changjian Liu , Zhouhao Wu , Rufeng Liao , Gengze Li , Huapu Lu","doi":"10.1016/j.multra.2024.100184","DOIUrl":"10.1016/j.multra.2024.100184","url":null,"abstract":"<div><div>With the acceleration of urbanization and continuous population growth in China, transportation issues in central cities, especially large and mega-cities, have become increasingly prominent. A series of problems such as economic efficiency decline and reduced residents' well-being caused by traffic congestion have become significant factors constraining the sustainable development of cities. As a core component of the urban transportation system, the prioritized development of urban public transportation is crucial for alleviating traffic congestion, improving environmental quality, and enhancing residents' quality of life. However, from the beginning of 2023, the share of public transportation in residents' travel has gradually decreased, with the total passenger volume still lower than the same period in 2019. In response to the challenges faced by the public transportation system under the new circumstances, this paper reviews the necessity of prioritized development of urban public transportation, analyzes the reasons for the decline in the share of public transportation in residents' overall travel modes, and proposes targeted suggestions. On this basis, the paper explores the intrinsic connection between the strategy of prioritizing public transportation development and sustainable urban development.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100184"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143133450","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}
Pub Date : 2025-03-01Epub Date: 2024-12-10DOI: 10.1016/j.multra.2024.100148
Umesh Bodkhe , Sudeep Tanwar
The Internet of Vehicles (IoV) plays a crucial role in intelligent transportation systems (ITS) by enabling communication between interconnected vehicles and supporting infrastructure. Connected vehicles utilize basic safety messages (BSMs) to exchange kinematic data, such as vehicle acceleration, velocity, position, and direction, with neighbouring nodes in the ITS network to enhance road safety. However, these BSMs are susceptible to various security attacks, which disrupt the collaborative functionality of ITS, potentially resulting in accidents or traffic congestion. The scientific community has proposed numerous security mechanisms to protect BSMs. The majority of these assessments have been conducted utilizing either the vehicular reference misbehaviour (VeReMi) dataset or the VeReMi extension dataset. These datasets are specifically designed for the Luxembourg SUMO Traffic (LuST) scenario and are suitable for only evaluating misbehaviour detection methods within a European ITS context. However, there is a notable scarcity of publicly accessible misbehaviour datasets that faithfully depict Indian ITS scenarios. To overcome this limitation, we introduce a new scenario, i.e., the Ahmedabad SUMO Traffic (AhmST) scenario, based on the city of Ahmedabad in Gujarat, India. Moreover, we also introduce the Indian dataset for misbehaviour analysis (AhmST). The proposed dataset includes cases of false data injections affecting the vehicle position, heading, and speed information within BSMs. Finally, we compare the AhmST dataset with recent datasets, assess the proposed dataset using various machine learning techniques and present an optimized model with improved accuracy.
{"title":"Indian SUMO traffic scenario-based misbehaviour detection dataset for connected vehicles","authors":"Umesh Bodkhe , Sudeep Tanwar","doi":"10.1016/j.multra.2024.100148","DOIUrl":"10.1016/j.multra.2024.100148","url":null,"abstract":"<div><div>The Internet of Vehicles (IoV) plays a crucial role in intelligent transportation systems (ITS) by enabling communication between interconnected vehicles and supporting infrastructure. Connected vehicles utilize basic safety messages (BSMs) to exchange kinematic data, such as vehicle acceleration, velocity, position, and direction, with neighbouring nodes in the ITS network to enhance road safety. However, these BSMs are susceptible to various security attacks, which disrupt the collaborative functionality of ITS, potentially resulting in accidents or traffic congestion. The scientific community has proposed numerous security mechanisms to protect BSMs. The majority of these assessments have been conducted utilizing either the vehicular reference misbehaviour (VeReMi) dataset or the VeReMi extension dataset. These datasets are specifically designed for the Luxembourg SUMO Traffic (LuST) scenario and are suitable for only evaluating misbehaviour detection methods within a European ITS context. However, there is a notable scarcity of publicly accessible misbehaviour datasets that faithfully depict Indian ITS scenarios. To overcome this limitation, we introduce a new scenario, i.e., the Ahmedabad SUMO Traffic (AhmST) scenario, based on the city of Ahmedabad in Gujarat, India. Moreover, we also introduce the Indian dataset for misbehaviour analysis (AhmST). The proposed dataset includes cases of false data injections affecting the vehicle position, heading, and speed information within BSMs. Finally, we compare the AhmST dataset with recent datasets, assess the proposed dataset using various machine learning techniques and present an optimized model with improved accuracy.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132796","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}
Pub Date : 2025-03-01Epub Date: 2025-01-07DOI: 10.1016/j.multra.2025.100189
Sai Sneha Channamallu, Deema Almaskati, Sharareh Kermanshachi, Apurva Pamidimukkala
The increasing utilization of autonomous vehicles (AVs) makes it critical to understand and mitigate their involvement in traffic accidents. This study, therefore, addresses a significant gap in the research on AV safety by focusing on predicting the possibility of injuries in AV-involved crashes. The California Department of Motor Vehicles’ comprehensive dataset of accidents that occurred from 2014 to May 2024 was utilized, and advanced machine learning techniques were applied to develop a model capable of predicting the outcomes of accidents involving AVs. The study found that the bagging classifier model outperforms other models in reliably predicting and identifying severe crashes and minimizing misclassification. Evaluations made through precision-recall, validation, and learning curves confirm the model's robustness, ability to generalize across data subsets, and effectiveness in increasing training data. Key predictors of crash severity include the extent of damage to the AV, vehicle type, manufacturer, and presence of a traffic signal. The study highlights the importance of tailored safety measures, robust safety mechanisms, and advanced traffic management systems to mitigate crash severity. The real-world application of this advanced model promises substantial benefits for vehicle manufacturers, urban planners, policymakers, and end-users, and will contribute to safer roadways.
{"title":"Autonomous vehicle safety: An advanced bagging classifier technique for crash injury prediction","authors":"Sai Sneha Channamallu, Deema Almaskati, Sharareh Kermanshachi, Apurva Pamidimukkala","doi":"10.1016/j.multra.2025.100189","DOIUrl":"10.1016/j.multra.2025.100189","url":null,"abstract":"<div><div>The increasing utilization of autonomous vehicles (AVs) makes it critical to understand and mitigate their involvement in traffic accidents. This study, therefore, addresses a significant gap in the research on AV safety by focusing on predicting the possibility of injuries in AV-involved crashes. The California Department of Motor Vehicles’ comprehensive dataset of accidents that occurred from 2014 to May 2024 was utilized, and advanced machine learning techniques were applied to develop a model capable of predicting the outcomes of accidents involving AVs. The study found that the bagging classifier model outperforms other models in reliably predicting and identifying severe crashes and minimizing misclassification. Evaluations made through precision-recall, validation, and learning curves confirm the model's robustness, ability to generalize across data subsets, and effectiveness in increasing training data. Key predictors of crash severity include the extent of damage to the AV, vehicle type, manufacturer, and presence of a traffic signal. The study highlights the importance of tailored safety measures, robust safety mechanisms, and advanced traffic management systems to mitigate crash severity. The real-world application of this advanced model promises substantial benefits for vehicle manufacturers, urban planners, policymakers, and end-users, and will contribute to safer roadways.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100189"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132800","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}
Pub Date : 2025-03-01Epub Date: 2025-01-09DOI: 10.1016/j.multra.2025.100196
Siti Norida Wahab , Muhammad Iskandar Hamzah , Norazah Mohd Suki , Yueh Suan Chong , Chin Pei Kua
This study aims to investigate passenger satisfaction in rail transit systems within emerging economies, utilizing a theory of consumption values. It seeks to understand how various values, such as functional, social, emotional, conditional, and epistemic, influence passenger perceptions and experiences providing insights for enhancing rail transit services. This study employs a self-administered questionnaire distributed to 418 passenger rail transit users in Kuala Lumpur city centre over a three-month period. Smart-PLS software was utilized to examine relationships between consumption values and passenger satisfaction. The study findings reveal strong support for functional and social values in influencing passenger satisfaction within rail transit systems of emerging economies. Similarly, emotional and conditional values also play a significant role. Surprisingly, epistemic value does not exhibit substantial influence, highlighting potential disparities in passenger perceptions and priorities. Rail transit operators and regulators should focus on these facets of consumption values in order to maximize passenger satisfaction in rail transit. Conditional aspects such as safety, punctuality, frequency, and accessibility should also be given priority. What is new to the existing literature is that epistemic value was confirmed as the trivial predictor of passengers' satisfaction in rail transit. Hence, clear signage, informative announcements, or accessible digital resources provided by the transit authority will enhance passengers' knowledge and overall experience. Being among a few studies in measuring rail transit satisfaction using the consumption values approach, particularly in the context of Asia-Pacific emerging economies, the empirical results attained broadened the growing literature pertinent to consumer behaviour, consumption values, and sustainable transportation. The findings offer new insights into enhancing rail transit services, emphasizing the need for clear communication and informative resources to boost passenger satisfaction.
{"title":"Unveiling passenger satisfaction in rail transit through a consumption values perspective","authors":"Siti Norida Wahab , Muhammad Iskandar Hamzah , Norazah Mohd Suki , Yueh Suan Chong , Chin Pei Kua","doi":"10.1016/j.multra.2025.100196","DOIUrl":"10.1016/j.multra.2025.100196","url":null,"abstract":"<div><div>This study aims to investigate passenger satisfaction in rail transit systems within emerging economies, utilizing a theory of consumption values. It seeks to understand how various values, such as functional, social, emotional, conditional, and epistemic, influence passenger perceptions and experiences providing insights for enhancing rail transit services. This study employs a self-administered questionnaire distributed to 418 passenger rail transit users in Kuala Lumpur city centre over a three-month period. Smart-PLS software was utilized to examine relationships between consumption values and passenger satisfaction. The study findings reveal strong support for functional and social values in influencing passenger satisfaction within rail transit systems of emerging economies. Similarly, emotional and conditional values also play a significant role. Surprisingly, epistemic value does not exhibit substantial influence, highlighting potential disparities in passenger perceptions and priorities. Rail transit operators and regulators should focus on these facets of consumption values in order to maximize passenger satisfaction in rail transit. Conditional aspects such as safety, punctuality, frequency, and accessibility should also be given priority. What is new to the existing literature is that epistemic value was confirmed as the trivial predictor of passengers' satisfaction in rail transit. Hence, clear signage, informative announcements, or accessible digital resources provided by the transit authority will enhance passengers' knowledge and overall experience. Being among a few studies in measuring rail transit satisfaction using the consumption values approach, particularly in the context of Asia-Pacific emerging economies, the empirical results attained broadened the growing literature pertinent to consumer behaviour, consumption values, and sustainable transportation. The findings offer new insights into enhancing rail transit services, emphasizing the need for clear communication and informative resources to boost passenger satisfaction.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100196"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143133447","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}
Public transit is considered a compelling alternative to the car, renowned for its affordability and sustainability, given that a single transit vehicle can accommodate a substantially higher number of passengers compared to regular passenger vehicles. In urban areas, a significant portion of the travel time spent by street-running transit vehicles is consumed waiting at traffic signals. Thus, transit signal priority (TSP) strategies have evolved over the years to give preference to transit vehicles at signalized intersections. Traffic signals are usually optimized for the general vehicular traffic flow, with TSP logic subsequently inserted as an add-on to modify the underlying signal timing plans, thereby granting priority to transit vehicles. However, one major issue associated with the implementation of TSP is its negative impact on the surrounding traffic, creating a conflict between prioritizing passenger vehicles versus transit vehicles. This paper proposes a novel decentralized multimodal multiagent reinforcement learning signal controller that simultaneously optimizes the total person delays for both traffic and transit. The controller, named embedding communicated Multi-Agent Reinforcement Learning for Integrated Network-Multi Modal (eMARLIN-MM), consists of two components: the encoder that is responsible for transforming the observations into latent space and the executor that serves as the Q-network making timing decisions. eMARLIN-MM establishes communication between the control agents by sharing information between neighboring intersections. eMARLIN-MM was tested in a simulation model of five intersections in North York, Ontario, Canada. The results show that eMARLIN-MM can substantially reduce the total person delays by 54 % to 66 % compared to pre-timed signals at different levels of bus occupancy, outperforming the independent Deep Q-Networks (DQN) agents. eMARLIN-MM also outperforms eMARLIN which does not incorporate buses and bus passengers in the signal timing optimization process.
{"title":"Multimodal adaptive traffic signal control: A decentralized multiagent reinforcement learning approach","authors":"Kareem Othman , Xiaoyu Wang , Amer Shalaby , Baher Abdulhai","doi":"10.1016/j.multra.2025.100190","DOIUrl":"10.1016/j.multra.2025.100190","url":null,"abstract":"<div><div>Public transit is considered a compelling alternative to the car, renowned for its affordability and sustainability, given that a single transit vehicle can accommodate a substantially higher number of passengers compared to regular passenger vehicles. In urban areas, a significant portion of the travel time spent by street-running transit vehicles is consumed waiting at traffic signals. Thus, transit signal priority (TSP) strategies have evolved over the years to give preference to transit vehicles at signalized intersections. Traffic signals are usually optimized for the general vehicular traffic flow, with TSP logic subsequently inserted as an add-on to modify the underlying signal timing plans, thereby granting priority to transit vehicles. However, one major issue associated with the implementation of TSP is its negative impact on the surrounding traffic, creating a conflict between prioritizing passenger vehicles versus transit vehicles. This paper proposes a novel decentralized multimodal multiagent reinforcement learning signal controller that simultaneously optimizes the total person delays for both traffic and transit. The controller, named embedding communicated Multi-Agent Reinforcement Learning for Integrated Network-Multi Modal (eMARLIN-MM), consists of two components: the encoder that is responsible for transforming the observations into latent space and the executor that serves as the Q-network making timing decisions. eMARLIN-MM establishes communication between the control agents by sharing information between neighboring intersections. eMARLIN-MM was tested in a simulation model of five intersections in North York, Ontario, Canada. The results show that eMARLIN-MM can substantially reduce the total person delays by 54 % to 66 % compared to pre-timed signals at different levels of bus occupancy, outperforming the independent Deep Q-Networks (DQN) agents. eMARLIN-MM also outperforms eMARLIN which does not incorporate buses and bus passengers in the signal timing optimization process.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100190"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143133443","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}
Pub Date : 2025-03-01Epub Date: 2025-01-04DOI: 10.1016/j.multra.2025.100193
Amira Hammami, Attila Borsos, Ágoston Pál Sándor
The aim of this research is to objectively and subjectively validate the virtual reality Bicycle Simulator (BS) developed using off-the-shelf components at the University of Győr, Hungary.
To this end, this research compares the performance of 32 participants in two real-world environments (Site 1: separated bicycle-pedestrian path and Site 2: advisory bicycle lane) and in their replication in virtual reality (VR). The objective measures collected for the comparison include speed and Cumulative Lateral Position (CLP), whereas subjective measures include the Perceived Level of Realism (PLR) based on participants’ self-reported perceptions in a post-experiment questionnaire. PLR is a new indicator that we propose using subjects' perceptions of speed, BS control, and VR representation. The combination of these subjective and objective measures is proposed as the Degree of Realism (DR) to standardise the classification of the realism level of a bicycle simulator.
Subjectively, the results indicate that the BS provides a high level of safety and comfort for conducting such research. Subject characteristics have no significant influence on VR sickness scores or Perceived Level of Realism. Objectively, for both speed and CLP, we found no significant difference between on-site and the simulation measurements in the case of Site 1, but otherwise for Site 2. However, subjects were not able to accurately perceive either the actual or the relative differences.
In conclusion, our bicycle simulator is a safe and comfortable traffic safety research tool that needs further improvement. The proposed preliminary concept of the degree of realism requires further investigation.
{"title":"How realistic a bicycle simulator can be? - A validation study","authors":"Amira Hammami, Attila Borsos, Ágoston Pál Sándor","doi":"10.1016/j.multra.2025.100193","DOIUrl":"10.1016/j.multra.2025.100193","url":null,"abstract":"<div><div>The aim of this research is to objectively and subjectively validate the virtual reality Bicycle Simulator (BS) developed using off-the-shelf components at the University of Győr, Hungary.</div><div>To this end, this research compares the performance of 32 participants in two real-world environments (Site 1: separated bicycle-pedestrian path and Site 2: advisory bicycle lane) and in their replication in virtual reality (VR). The objective measures collected for the comparison include speed and Cumulative Lateral Position (CLP), whereas subjective measures include the Perceived Level of Realism (PLR) based on participants’ self-reported perceptions in a post-experiment questionnaire. PLR is a new indicator that we propose using subjects' perceptions of speed, BS control, and VR representation. The combination of these subjective and objective measures is proposed as the Degree of Realism (DR) to standardise the classification of the realism level of a bicycle simulator.</div><div>Subjectively, the results indicate that the BS provides a high level of safety and comfort for conducting such research. Subject characteristics have no significant influence on VR sickness scores or Perceived Level of Realism. Objectively, for both speed and CLP, we found no significant difference between on-site and the simulation measurements in the case of Site 1, but otherwise for Site 2. However, subjects were not able to accurately perceive either the actual or the relative differences.</div><div>In conclusion, our bicycle simulator is a safe and comfortable traffic safety research tool that needs further improvement. The proposed preliminary concept of the degree of realism requires further investigation.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132797","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}
Pub Date : 2025-03-01Epub Date: 2025-01-04DOI: 10.1016/j.multra.2025.100188
Yang Liu, Donglin He, Jiayou Lei, Mingwei He, Zhuangbin Shi
Understanding the travel behavior of transit passengers and its influencing factors is crucial for promoting transit use and alleviating urban traffic congestion. However, limited studies have examined the determinants of spatial expansion in multimodal public transportation and overlooked the nonlinear influence between variables. To address these gaps, this study employs the travel distance indicator to portray the spatial expansion of transit passengers. Using smart card data collected from Beijing, China, we propose a comprehensive trip chain extraction method within the metro and bus network, considering transfer behaviors. From the extracted trip chain data, we calculate travel distances and observe significant variations across different transit networks: an average travel distance of 8.09 km in the bus network, 14.93 km in the metro network, and 23.10 km in the integrated network. Further, we explore the non-linear relationship between transit travel distance and the built environment by employing a Gradient Boosting Regression Tree (GBRT) model. The finding reveals that the built environment exerts the most significant influence on travel distance (46.80 %), particularly regarding the distance to the nearest metro station and the central business district (CBD). Additionally, all variables exhibit non-linear effects on travel distance, with many exhibiting relevance only within specific ranges. For instance, there is a noticeable decline in travel distance when the bus stop density falls within the range of 15 units/km² and the bus coverage rate within a range of 0.8. Beyond these threshold values, the decline in travel distance becomes gradual. These findings emphasize the significance of considering non-linear relationships and threshold effects in transit and urban planning. Finally, this study provides practicable recommendations regarding non-linearities for the government that could be beneficial in promoting transit usage.
{"title":"Investigating the non-linear influence of the built environment on passengers’ travel distance within metro and bus networks using smart card data","authors":"Yang Liu, Donglin He, Jiayou Lei, Mingwei He, Zhuangbin Shi","doi":"10.1016/j.multra.2025.100188","DOIUrl":"10.1016/j.multra.2025.100188","url":null,"abstract":"<div><div>Understanding the travel behavior of transit passengers and its influencing factors is crucial for promoting transit use and alleviating urban traffic congestion. However, limited studies have examined the determinants of spatial expansion in multimodal public transportation and overlooked the nonlinear influence between variables. To address these gaps, this study employs the travel distance indicator to portray the spatial expansion of transit passengers. Using smart card data collected from Beijing, China, we propose a comprehensive trip chain extraction method within the metro and bus network, considering transfer behaviors. From the extracted trip chain data, we calculate travel distances and observe significant variations across different transit networks: an average travel distance of 8.09 km in the bus network, 14.93 km in the metro network, and 23.10 km in the integrated network. Further, we explore the non-linear relationship between transit travel distance and the built environment by employing a Gradient Boosting Regression Tree (GBRT) model. The finding reveals that the built environment exerts the most significant influence on travel distance (46.80 %), particularly regarding the distance to the nearest metro station and the central business district (CBD). Additionally, all variables exhibit non-linear effects on travel distance, with many exhibiting relevance only within specific ranges. For instance, there is a noticeable decline in travel distance when the bus stop density falls within the range of 15 units/km² and the bus coverage rate within a range of 0.8. Beyond these threshold values, the decline in travel distance becomes gradual. These findings emphasize the significance of considering non-linear relationships and threshold effects in transit and urban planning. Finally, this study provides practicable recommendations regarding non-linearities for the government that could be beneficial in promoting transit usage.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100188"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143133444","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}
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