Pub Date : 2024-11-01DOI: 10.1016/j.trd.2024.104459
Lingyue Li , Chunzhu Wei , Jing Liu , Jindao Chen , Hongping Yuan
With increasing global trade and frequent occurrence of disruptive events, the resilience of port clusters has emerged as a critical area of concern. However, studies that focus on the resilience of port clusters considering their complex network structure and operational dynamics remain limited. This study proposes a novel model to assess port cluster resilience by integrating hypergraph-based modeling and agent-based simulation. The model captures the complex relationships among ports and vessels, enabling the dynamic modeling of disruption impacts on port cluster resilience. A case study of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) port cluster demonstrates the model’s applicability and effectiveness. Additionally, the significant impact of typhoon duration on resilience and the potential benefits of vessel port skipping behavior and port cargo handling capacity improvements are analyzed. These findings provide valuable insights for stakeholders in developing effective strategies to enhance the resilience of port clusters and the maritime transportation system.
{"title":"Assessing port cluster resilience: Integrating hypergraph-based modeling and agent-based simulation","authors":"Lingyue Li , Chunzhu Wei , Jing Liu , Jindao Chen , Hongping Yuan","doi":"10.1016/j.trd.2024.104459","DOIUrl":"10.1016/j.trd.2024.104459","url":null,"abstract":"<div><div>With increasing global trade and frequent occurrence of disruptive events, the resilience of port clusters has emerged as a critical area of concern. However, studies that focus on the resilience of port clusters considering their complex network structure and operational dynamics remain limited. This study proposes a novel model to assess port cluster resilience by integrating hypergraph-based modeling and agent-based simulation. The model captures the complex relationships among ports and vessels, enabling the dynamic modeling of disruption impacts on port cluster resilience. A case study of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) port cluster demonstrates the model’s applicability and effectiveness. Additionally, the significant impact of typhoon duration on resilience and the potential benefits of vessel port skipping behavior and port cargo handling capacity improvements are analyzed. These findings provide valuable insights for stakeholders in developing effective strategies to enhance the resilience of port clusters and the maritime transportation system.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104459"},"PeriodicalIF":7.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-31DOI: 10.1016/j.trd.2024.104483
Laene Oliveira Soares , José Ricardo Sodré , Luis Hernández-Callejo , Ronney Arismel Mancebo Boloy
This study explores the total cost of ownership (TCO) and green premium of electric vehicles (EVs), including plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles (HEVs), battery electric vehicles (BEVs), and conventional vehicles, focusing on top-selling models in Brazil. A roadmap is devised to ease EV integration into the Brazilian market. The TCO analysis reveals that PHEVs powered solely by gasoline cost up to $0.084 per kilometre, while using gasoline in dual-fuel mode with 80% biogas reduces costs to $0.038. HEVs saw costs drop from $0.077 per kilometre to $0.054 with bioethanol in dual-fuel mode with 80% biogas. Conventional vehicles using dual-fuel with 20% bioethanol and 80% biogas achieved cost reductions from $0.106 to $0.081 per kilometre. HEVs and conventional vehicles with biofuels demonstrated annual cost savings of up to 11.2% and 14.1%, respectively, compared to gasoline-only use. BEVs, however, showed significantly lower annual costs, being up to 63.7% and 55% less than gasoline-powered HEVs and PHEVs, respectively, and between 60.9% and 73% less than conventional vehicles. The study also outlines policy interventions and infrastructure development to promote EV adoption in Brazil, enhancing sustainable transportation.
{"title":"Electric vehicle adoption in Brazil: Economical analysis and roadmap","authors":"Laene Oliveira Soares , José Ricardo Sodré , Luis Hernández-Callejo , Ronney Arismel Mancebo Boloy","doi":"10.1016/j.trd.2024.104483","DOIUrl":"10.1016/j.trd.2024.104483","url":null,"abstract":"<div><div>This study explores the total cost of ownership (TCO) and green premium of electric vehicles (EVs), including plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles (HEVs), battery electric vehicles (BEVs), and conventional vehicles, focusing on top-selling models in Brazil. A roadmap is devised to ease EV integration into the Brazilian market. The TCO analysis reveals that PHEVs powered solely by gasoline cost up to $0.084 per kilometre, while using gasoline in dual-fuel mode with 80% biogas reduces costs to $0.038. HEVs saw costs drop from $0.077 per kilometre to $0.054 with bioethanol in dual-fuel mode with 80% biogas. Conventional vehicles using dual-fuel with 20% bioethanol and 80% biogas achieved cost reductions from $0.106 to $0.081 per kilometre. HEVs and conventional vehicles with biofuels demonstrated annual cost savings of up to 11.2% and 14.1%, respectively, compared to gasoline-only use. BEVs, however, showed significantly lower annual costs, being up to 63.7% and 55% less than gasoline-powered HEVs and PHEVs, respectively, and between 60.9% and 73% less than conventional vehicles. The study also outlines policy interventions and infrastructure development to promote EV adoption in Brazil, enhancing sustainable transportation.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"137 ","pages":"Article 104483"},"PeriodicalIF":7.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1016/j.trd.2024.104489
Zhipeng Peng , Hao Ji , Said M Easa , Chenzhu Wang , Yonggang Wang , Hengyan Pan
This study investigates the spatial distribution pattern of CO2 emissions from Heavy duty trucks (HDTs) in Xi’an City across different periods and their influencing factors. Five study periods were initially proposed considering the temporal distribution of emissions and the city’s traffic restriction policy. The study area was divided into 2,839 spatial grids. Then, CO2 emissions from HDTs were calculated at the spatial grid scale, and variables related to road density, accessibility to freight hubs, POI density, and demographic indicators were also integrated into the spatial grids. Finally, five XGBoost models were constructed using the spatial data from different periods, and the spatial and temporal heterogeneity of each variable’s impact on CO2 emissions was thoroughly analyzed using the SHAP (SHapley Additive exPlanations) explainer. The results demonstrate that the predictive ability of the XGBoost model surpasses that of the OLS model and the GWR model, providing better insight into the spatiotemporal heterogeneity.
{"title":"Analyzing spatiotemporal truck emission pattern using explainable machine learning: A case study in Xi’an, China","authors":"Zhipeng Peng , Hao Ji , Said M Easa , Chenzhu Wang , Yonggang Wang , Hengyan Pan","doi":"10.1016/j.trd.2024.104489","DOIUrl":"10.1016/j.trd.2024.104489","url":null,"abstract":"<div><div>This study investigates the spatial distribution pattern of CO<sub>2</sub> emissions from Heavy duty trucks (HDTs) in Xi’an City across different periods and their influencing factors. Five study periods were initially proposed considering the temporal distribution of emissions and the city’s traffic restriction policy. The study area was divided into 2,839 spatial grids. Then, CO<sub>2</sub> emissions from HDTs were calculated at the spatial grid scale, and variables related to road density, accessibility to freight hubs, POI density, and demographic indicators were also integrated into the spatial grids. Finally, five XGBoost models were constructed using the spatial data from different periods, and the spatial and temporal heterogeneity of each variable’s impact on CO<sub>2</sub> emissions was thoroughly analyzed using the SHAP (SHapley Additive exPlanations) explainer. The results demonstrate that the predictive ability of the XGBoost model surpasses that of the OLS model and the GWR model, providing better insight into the spatiotemporal heterogeneity.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"137 ","pages":"Article 104489"},"PeriodicalIF":7.3,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1016/j.trd.2024.104471
Angela Smith , Janet E. Dickinson , Taalia Nadeem , Ben Snow , Rama Permana , Tom Cherrett , Jason Drummond
Advanced Air Mobility (AAM) is being progressed, yet evidence suggests low levels of public salience and minimal debate. Efforts to engage the public have been framed around achieving acceptance made with little clarity of the potential impacts and benefits. This paper analyses an approach which sought to overcome low interest and to make technical information accessible to a general audience. The research used virtual reality (VR) to represent AAM technologies in public spaces proximal to where participants lived. During a second phase of research, additional supporting materials (an animation, a short game, and a recorded presentation) were developed to respond to gaps in understanding. The research was undertaken at five sites in England (N = 603). The representativeness of the sample is analysed, and the value of the VR, additional materials, and siting of the research are reviewed. Drawing upon detailed responses to open questions, the extent of meaningful involvement is explored showing how the additional supporting materials increased the depth of understanding amongst participants.
{"title":"Supporting inclusive debate on Advanced Air Mobility: An evaluation","authors":"Angela Smith , Janet E. Dickinson , Taalia Nadeem , Ben Snow , Rama Permana , Tom Cherrett , Jason Drummond","doi":"10.1016/j.trd.2024.104471","DOIUrl":"10.1016/j.trd.2024.104471","url":null,"abstract":"<div><div>Advanced Air Mobility (AAM) is being progressed, yet evidence suggests low levels of public salience and minimal debate. Efforts to engage the public have been framed around achieving acceptance made with little clarity of the potential impacts and benefits. This paper analyses an approach which sought to overcome low interest and to make technical information accessible to a general audience. The research used virtual reality (VR) to represent AAM technologies in public spaces proximal to where participants lived. During a second phase of research, additional supporting materials (an animation, a short game, and a recorded presentation) were developed to respond to gaps in understanding. The research was undertaken at five sites in England (N = 603). The representativeness of the sample is analysed, and the value of the VR, additional materials, and siting of the research are reviewed. Drawing upon detailed responses to open questions, the extent of meaningful involvement is explored showing how the additional supporting materials increased the depth of understanding amongst participants.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104471"},"PeriodicalIF":7.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-25DOI: 10.1016/j.trd.2024.104477
Yijia Hu , Mushu Zhao , Zhan Zhao
This study investigates how the street environment influences e-bike and e-scooter flows at the link level, considering their distinct spatial travel patterns. An angle-based spatial autoregressive quantile regression (SAQR) model is developed to analyze fine-scale street environments in Washington, D.C. We observe distinct spatial travel patterns between e-bikes and e-scooters, and e-scooter usage is more concentrated in city centers. Link design and network design have stronger impacts on the usage of e-bike and e-scooter than land use features. However, land use features are more likely to affect the flow of these two modes differently. Specifically, streets with dedicated bike lanes, traffic signals, wider width, higher betweenness centrality, and a higher proportion of entertainment and office land tend to attract more e-bike and e-scooter trips. In addition, bike-friendly facilities, particularly buffered bike lanes, exhibit more pronounced impacts. The findings provide policy implications for nuanced street design guidelines to facilitate electric micromobility usage.
{"title":"Uncovering heterogeneous effects of link-level street environment on e-bike and e-scooter usage","authors":"Yijia Hu , Mushu Zhao , Zhan Zhao","doi":"10.1016/j.trd.2024.104477","DOIUrl":"10.1016/j.trd.2024.104477","url":null,"abstract":"<div><div>This study investigates how the street environment influences e-bike and e-scooter flows at the link level, considering their distinct spatial travel patterns. An angle-based spatial autoregressive quantile regression (SAQR) model is developed to analyze fine-scale street environments in Washington, D.C. We observe distinct spatial travel patterns between e-bikes and e-scooters, and e-scooter usage is more concentrated in city centers. Link design and network design have stronger impacts on the usage of e-bike and e-scooter than land use features. However, land use features are more likely to affect the flow of these two modes differently. Specifically, streets with dedicated bike lanes, traffic signals, wider width, higher betweenness centrality, and a higher proportion of entertainment and office land tend to attract more e-bike and e-scooter trips. In addition, bike-friendly facilities, particularly buffered bike lanes, exhibit more pronounced impacts. The findings provide policy implications for nuanced street design guidelines to facilitate electric micromobility usage.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104477"},"PeriodicalIF":7.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.trd.2024.104475
Mohamad Yaman Fares, Ahmad Albdour, Michele Lanotte
The adoption of Electric Vehicles (EVs), driven by policies like the Zero Emission Vehicle (ZEV) mandate, is rapidly transforming transportation infrastructure. In 2021, over 1.25-million light-duty EVs were registered in the United States, signaling a shift that extends to heavy vehicle categories. This study evaluates the implications of this transition on road networks, focusing on the increased gross weight of EVs compared to traditional Internal Combustion Engine (ICE) vehicles and its impact on flexible pavement structures. The study investigates the deterioration patterns and potential damage to road infrastructures resulting from integrating EVs into the traffic mix, utilizing both the AASHTO 1993 and Mechanistic-Empirical (ME) pavement evaluation methodologies. The analyses reveal a significant acceleration in road degradation, necessitating urgent consideration of EV-induced stresses by transportation authorities. Recommendations for future research and practical strategies for mitigating these impacts are provided to guide policymakers and engineers in adapting to this evolving vehicular landscape.
{"title":"Evaluation of potential electric vehicles load-induced damage on flexible pavements","authors":"Mohamad Yaman Fares, Ahmad Albdour, Michele Lanotte","doi":"10.1016/j.trd.2024.104475","DOIUrl":"10.1016/j.trd.2024.104475","url":null,"abstract":"<div><div>The adoption of Electric Vehicles (EVs), driven by policies like the Zero Emission Vehicle (ZEV) mandate, is rapidly transforming transportation infrastructure. In 2021, over 1.25-million light-duty EVs were registered in the United States, signaling a shift that extends to heavy vehicle categories. This study evaluates the implications of this transition on road networks, focusing on the increased gross weight of EVs compared to traditional Internal Combustion Engine (ICE) vehicles and its impact on flexible pavement structures. The study investigates the deterioration patterns and potential damage to road infrastructures resulting from integrating EVs into the traffic mix, utilizing both the AASHTO 1993 and Mechanistic-Empirical (ME) pavement evaluation methodologies. The analyses reveal a significant acceleration in road degradation, necessitating urgent consideration of EV-induced stresses by transportation authorities. Recommendations for future research and practical strategies for mitigating these impacts are provided to guide policymakers and engineers in adapting to this evolving vehicular landscape.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104475"},"PeriodicalIF":7.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.trd.2024.104464
Aso Validi, Yuzhou Liu, Cristina Olaverri-Monreal
Recent developments in connected and automated vehicle technologies have opened up new possibilities but also posed enduring challenges. One of the primary challenges is the efficient coordination of vehicles in urban environments, specifically through scalable and destination-based platooning. While considerable research has focused on platooning with a limited number of vehicles demonstrating seamless connectivity and coordination on highways, there remains a significant gap in understanding and implementing scalable platoons in more dynamic urban settings. This paper bridges these gaps by developing a novel extension to the 3DCoAutosim simulation platform. Our model introduces ’Scalable Semi-autonomous Destination-based Multiplayer E-Platoons’, accommodating different automation levels and simulation characteristics of vehicles in five distinct platoons. We employed seven electric vehicles to create these platoons, each consisting of an autonomous lead vehicle, followers that are either autonomous or semi-autonomous (accompanied by drivers), customised according to the specific requirements of each platoon. Utilising Time Series Analysis, Multiple Linear Regression and a comprehensive, comparative scenario-based analysis, we assessed and validated our developed model’s impact on battery energy consumption under varying road slopes and car-following models. Our assessment employs real-world trip data from Upper Austria, with results indicating a potential reduction in total battery energy consumption when operating in platoon mode.
{"title":"Assessing energy consumption in scalable semi-autonomous destination-based E-platoons: A multiplayer approach","authors":"Aso Validi, Yuzhou Liu, Cristina Olaverri-Monreal","doi":"10.1016/j.trd.2024.104464","DOIUrl":"10.1016/j.trd.2024.104464","url":null,"abstract":"<div><div>Recent developments in connected and automated vehicle technologies have opened up new possibilities but also posed enduring challenges. One of the primary challenges is the efficient coordination of vehicles in urban environments, specifically through scalable and destination-based platooning. While considerable research has focused on platooning with a limited number of vehicles demonstrating seamless connectivity and coordination on highways, there remains a significant gap in understanding and implementing scalable platoons in more dynamic urban settings. This paper bridges these gaps by developing a novel extension to the 3DCoAutosim simulation platform. Our model introduces ’Scalable Semi-autonomous Destination-based Multiplayer E-Platoons’, accommodating different automation levels and simulation characteristics of vehicles in five distinct platoons. We employed seven electric vehicles to create these platoons, each consisting of an autonomous lead vehicle, followers that are either autonomous or semi-autonomous (accompanied by drivers), customised according to the specific requirements of each platoon. Utilising Time Series Analysis, Multiple Linear Regression and a comprehensive, comparative scenario-based analysis, we assessed and validated our developed model’s impact on battery energy consumption under varying road slopes and car-following models. Our assessment employs real-world trip data from Upper Austria, with results indicating a potential reduction in total battery energy consumption when operating in platoon mode.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104464"},"PeriodicalIF":7.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.trd.2024.104470
Haohao Qu , Han Li , Linlin You , Rui Zhu , Jinyue Yan , Paolo Santi , Carlo Ratti , Chau Yuen
The increasing popularity of electric vehicles (EVs) in recent times has introduced considerable load conditions for urban power grids and transportation systems, which highlights the importance of accurately predicting charging demand to enhance charging efficiency. However, current forecasting methods still face challenges in effectively aligning diverse data and generating accurate predictions that can be applied to unseen scenarios. To overcome the challenges, this work introduces a novel perspective: employing large language models (LLMs) as EV charging demand predictors. First, we reformulate the prediction task into a text-to-text format, enabling seamless and effective alignment of various features within a unified language semantic space. Subsequently, we fine-tune a LLM using a meta-learning framework to adapt it specifically for EV charging prediction. Through comprehensive evaluations, it has been demonstrated that the proposed model, ChatEV, achieves outstanding performance in EV charging demand forecasting, particularly in scenarios with limited data.
{"title":"ChatEV: Predicting electric vehicle charging demand as natural language processing","authors":"Haohao Qu , Han Li , Linlin You , Rui Zhu , Jinyue Yan , Paolo Santi , Carlo Ratti , Chau Yuen","doi":"10.1016/j.trd.2024.104470","DOIUrl":"10.1016/j.trd.2024.104470","url":null,"abstract":"<div><div>The increasing popularity of electric vehicles (EVs) in recent times has introduced considerable load conditions for urban power grids and transportation systems, which highlights the importance of accurately predicting charging demand to enhance charging efficiency. However, current forecasting methods still face challenges in effectively aligning diverse data and generating accurate predictions that can be applied to unseen scenarios. To overcome the challenges, this work introduces a novel perspective: employing large language models (LLMs) as EV charging demand predictors. First, we reformulate the prediction task into a text-to-text format, enabling seamless and effective alignment of various features within a unified language semantic space. Subsequently, we fine-tune a LLM using a meta-learning framework to adapt it specifically for EV charging prediction. Through comprehensive evaluations, it has been demonstrated that the proposed model, ChatEV, achieves outstanding performance in EV charging demand forecasting, particularly in scenarios with limited data.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104470"},"PeriodicalIF":7.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.trd.2024.104478
Jiemin Zheng , Yuting Hou , Mingxing Hu , Junheng Qi , Chunxin Wang , Jianyu Li
Rail transit’s safety and convenience have made it a preferred option for people with disabilities. In this study, utilizing the geographically weighted regression based on the network weight matrix (NWM GWR) model, we investigated the spatiotemporal patterns and influencing factors of metro ridership among this group in Nanjing, China. Our findings revealed significant fluctuations in metro ridership across seasons, with a decrease observed during summer. We also discovered that people with disabilities had evening peak hours one hour earlier than regular peak hours on weekdays, while weekends did not exhibit a significant peak. Geographically, metro trips of individuals with disabilities were concentrated in Old City and Main City. Furthermore, the results revealed that except distance to CBD and access to barrier-free facilities, the other factors positively influenced weekday and weekend ridership of people with disabilities. These insights provide valuable guidance for enhancing the mobility and accessibility of people with disabilities.
{"title":"Spatiotemporal patterns and factors influencing metro ridership of people with disabilities","authors":"Jiemin Zheng , Yuting Hou , Mingxing Hu , Junheng Qi , Chunxin Wang , Jianyu Li","doi":"10.1016/j.trd.2024.104478","DOIUrl":"10.1016/j.trd.2024.104478","url":null,"abstract":"<div><div>Rail transit’s safety and convenience have made it a preferred option for people with disabilities. In this study, utilizing the geographically weighted regression based on the network weight matrix (NWM GWR) model, we investigated the spatiotemporal patterns and influencing factors of metro ridership among this group in Nanjing, China. Our findings revealed significant fluctuations in metro ridership across seasons, with a decrease observed during summer. We also discovered that people with disabilities had evening peak hours one hour earlier than regular peak hours on weekdays, while weekends did not exhibit a significant peak. Geographically, metro trips of individuals with disabilities were concentrated in Old City and Main City. Furthermore, the results revealed that except distance to CBD and access to barrier-free facilities, the other factors positively influenced weekday and weekend ridership of people with disabilities. These insights provide valuable guidance for enhancing the mobility and accessibility of people with disabilities.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104478"},"PeriodicalIF":7.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.trd.2024.104458
Natalia Vincens , Elise van Kempen , Mikael Ögren , Kerstin Persson Waye
Rail traffic is increasing following policy recommendations for a sustainable transportation model. However, the health effects of rail traffic vibration on residents living close to railways remain underexplored. We aimed to investigate the relationships between rail traffic vibration and vibration annoyance from different types of trains and to explore the influence of railway noise on these relationships. The study population (N = 7280) was randomly selected from adults living within 1 km of a trafficked railway in Sweden. Survey data were combined with modelled rail traffic vibration and noise. A cross-sectional design and logistic regression analysis were used. Results support a dose–response relationship between vibration and annoyance (stronger for freight trains and weaker for passenger trains). In the adjusted analysis, we observe a robust association between vibration and annoyance from all types of trains, accounting for socioeconomic factors. Furthermore, railway noise appears to modulate the vibration annoyance response.
{"title":"Living close to railways: Cross-sectional analysis of ground-borne vibrations and vibration annoyance","authors":"Natalia Vincens , Elise van Kempen , Mikael Ögren , Kerstin Persson Waye","doi":"10.1016/j.trd.2024.104458","DOIUrl":"10.1016/j.trd.2024.104458","url":null,"abstract":"<div><div>Rail traffic is increasing following policy recommendations for a sustainable transportation model. However, the health effects of rail traffic vibration on residents living close to railways remain underexplored. We aimed to investigate the relationships between rail traffic vibration and vibration annoyance from different types of trains and to explore the influence of railway noise on these relationships. The study population (N = 7280) was randomly selected from adults living within 1 km of a trafficked railway in Sweden. Survey data were combined with modelled rail traffic vibration and noise. A cross-sectional design and logistic regression analysis were used. Results support a dose–response relationship between vibration and annoyance (stronger for freight trains and weaker for passenger trains). In the adjusted analysis, we observe a robust association between vibration and annoyance from all types of trains, accounting for socioeconomic factors. Furthermore, railway noise appears to modulate the vibration annoyance response.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104458"},"PeriodicalIF":7.3,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}