This study proposes a method for measuring travel delays caused by traffic crashes based on taxi GPS data and other open-source spatial data.Travel delays caused by traffic crashes are quantified according to the diff...This study proposes a method for measuring travel delays caused by traffic crashes based on taxi GPS data and other open-source spatial data.Travel delays caused by traffic crashes are quantified according to the difference between the post-crash and typical travel speeds on affected road segments.Based on multiple sources of data in Hong Kong,we also develop a generalized linear model with explanatory variables including crash characteristics,temporal attributes,road network features,traffic indicators,and built environment features,to unveil the relationship between travel delays and these factors.The findings show that crash characteristics alone inadequately explain variations in delays.The model performance improves after factors about the built environment and the dynamic road conditions are incorporated.This underscores the importance of urban factors in traffic delay analysis.Furthermore,we estimate the total travel delays caused by traffic crashes in the city.It is estimated that Hong Kong has suffered from a total delay of 713,877 vehicle-hours in 2021.The associated economic loss amounts to US$11.02 million.This study contributes to methodological advances in estimating crash-induced travel delays.The explanatory model considers factors which help policy makers and planners to identify risky factors and hot spots for devising more targeted and effective strategies of shortening crash-induced traffic congestion in the future.In addition,the findings highlight the significance and magnitude of another negative externality of traffic crashes-traffic delays-in a complex urban road network.展开更多
INTRODUCTION Societies around the world have committed themselves to achieving the Paris goals of carbon dioxide(CO_(2))reduction and limiting global warming to 1.5Cwith different levels of legal commitment.The transp...INTRODUCTION Societies around the world have committed themselves to achieving the Paris goals of carbon dioxide(CO_(2))reduction and limiting global warming to 1.5Cwith different levels of legal commitment.The transport sector is both a major use of energy and amajor source of air pollutants,including CO_(2),nitrogen oxides,ozone,particularmatter,and volatile organic compounds that cause climate change and harm human health.1,2 The recent Ukraine–Russia war triggered countries to evaluate a fossil–fuel-dependent transport system that is highly vulnerable.展开更多
The health impact of electric vehicles(EVs)is complex and multifaceted,encompassing reductions in air pollutants,improvements in road safety,and implications for social equity.However,existing studies often provide fr...The health impact of electric vehicles(EVs)is complex and multifaceted,encompassing reductions in air pollutants,improvements in road safety,and implications for social equity.However,existing studies often provide fragmented insights,lacking a unified framework to comprehensively assess these public health implications.This paper develops a comprehensive framework to summarize the health outcomes of EVs in urban areas,where the health impacts are more pronounced due to higher levels of traffic congestion and air pollution.Building on previous conceptual work that identified pathways linking general transportation and health,our model illustrates how the characteristics of EVs influence public health through various pathways compared to traditional transportation systems.Additionally,we address socioeconomic factors that introduce variability in EV-related health outcomes,emphasizing the need to consider potential health disparities in policy and intervention development.This comprehensive approach aims to inform holistic policies that account for the complex interplay between transportation,environment,and public health.展开更多
基金General Research Fund(GRF)project on“Improving bus safety in Hong Kong:From advanced spatial analysis to artificial intelligence”(No.17616221)Guangdong-Hong Kong-Macao Joint Laboratory on Smart Cities initiatives funded by the Guangdong Science and Technology Department(No.2020B1212030009).
文摘This study proposes a method for measuring travel delays caused by traffic crashes based on taxi GPS data and other open-source spatial data.Travel delays caused by traffic crashes are quantified according to the difference between the post-crash and typical travel speeds on affected road segments.Based on multiple sources of data in Hong Kong,we also develop a generalized linear model with explanatory variables including crash characteristics,temporal attributes,road network features,traffic indicators,and built environment features,to unveil the relationship between travel delays and these factors.The findings show that crash characteristics alone inadequately explain variations in delays.The model performance improves after factors about the built environment and the dynamic road conditions are incorporated.This underscores the importance of urban factors in traffic delay analysis.Furthermore,we estimate the total travel delays caused by traffic crashes in the city.It is estimated that Hong Kong has suffered from a total delay of 713,877 vehicle-hours in 2021.The associated economic loss amounts to US$11.02 million.This study contributes to methodological advances in estimating crash-induced travel delays.The explanatory model considers factors which help policy makers and planners to identify risky factors and hot spots for devising more targeted and effective strategies of shortening crash-induced traffic congestion in the future.In addition,the findings highlight the significance and magnitude of another negative externality of traffic crashes-traffic delays-in a complex urban road network.
基金supported the University of Hong Kong Distinguished Visiting Professors(DVP)scheme.
文摘INTRODUCTION Societies around the world have committed themselves to achieving the Paris goals of carbon dioxide(CO_(2))reduction and limiting global warming to 1.5Cwith different levels of legal commitment.The transport sector is both a major use of energy and amajor source of air pollutants,including CO_(2),nitrogen oxides,ozone,particularmatter,and volatile organic compounds that cause climate change and harm human health.1,2 The recent Ukraine–Russia war triggered countries to evaluate a fossil–fuel-dependent transport system that is highly vulnerable.
文摘The health impact of electric vehicles(EVs)is complex and multifaceted,encompassing reductions in air pollutants,improvements in road safety,and implications for social equity.However,existing studies often provide fragmented insights,lacking a unified framework to comprehensively assess these public health implications.This paper develops a comprehensive framework to summarize the health outcomes of EVs in urban areas,where the health impacts are more pronounced due to higher levels of traffic congestion and air pollution.Building on previous conceptual work that identified pathways linking general transportation and health,our model illustrates how the characteristics of EVs influence public health through various pathways compared to traditional transportation systems.Additionally,we address socioeconomic factors that introduce variability in EV-related health outcomes,emphasizing the need to consider potential health disparities in policy and intervention development.This comprehensive approach aims to inform holistic policies that account for the complex interplay between transportation,environment,and public health.
