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Citation |
Hu L, Wu X, Huang J, Peng Y, Liu W. Safety Sci. 2020; 127: e104710. |
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Copyright |
(Copyright © 2020, Elsevier Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
Improving the pedestrian traffic environment is important for the sustainable development of the city. This study goes beyond the traditional analysis of traditional traffic accident police reports by integrating them with rich geographic information system (GIS) resources to analyze a sample of 791 pedestrian crashes that occurred in the main urban area of Changsha city, China, from 2014 to 2016. The use of Baidu or Google Street View maps improves the accident reports and facilitates the detailed description of the characteristics that are related to pedestrian crashes. The focus of the analysis is to use GIS to visualize the distribution of pedestrian crashes in cities to explore the relationships between pedestrian crashes and the population, road network, land use and social services and activities and to analyze the impacts of the building environment and road characteristics on the severity of pedestrian crashes by combining the binary logistic regression and tree-based models. The results demonstrate that there are several clusters of pedestrian crashes in urban areas, which are related to the population, road network, regional functional zoning and social and economic characteristics. However, the severity of pedestrian casualties has strong relationships with darkness, lighting conditions, road isolation facilities and pedestrian age and behavior. Casualties are more severe at night than during the day, and school-age children and elderly pedestrians tend to suffer more. This study identifies the important influencing factors of urban pedestrian safety and of the risk awareness of pedestrians and other road users and proposes solutions from the perspectives of behavior and infrastructure. Language: en |
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Keywords |
Clusters; Geographic information system (GIS); Injury severity; Logit analysis; Pedestrian crashes; Tree-based model |