Assessing the Impact of Different Population Density Scenarios on Two-Wheeler Accident Characteristics at Intersections
Ziwei Wang,
Lin Hu (),
Fang Wang,
Miao Lin and
Ning Wu
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Ziwei Wang: School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
Lin Hu: School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
Fang Wang: School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
Miao Lin: China Automobile Technology Research Center Co., Ltd., Tianjin 300300, China
Ning Wu: Institute for Traffic Engineering and Management, Ruhr-University, 44801 Bochum, Germany
Sustainability, 2024, vol. 16, issue 5, 1-14
Abstract:
Examining 1192 intersection car and two-wheeled vehicle collision accidents from the China In-Depth Accident Study (CIDAS) database, this study employs population density heat maps for precise assessment of surrounding population densities at accident sites. The K-Medoid clustering algorithm and silhouette coefficient were used to classify accidents into two distinct groups based on population density. Subsequent application of the random parameter logit model revealed key contributing factors to these accidents in varying population densities. The results show notable differences in factors such as collision direction of two-wheeled vehicles, types of accident conflict, road conditions, and traffic flow, depending on the population density. Based on these conclusions, the research can inform differentiated risk prediction for two-wheeled vehicle accidents at intersections and provide insights for intersection design in various population density scenarios.
Keywords: traffic safety; injury severity; intersection; random parameters logit model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)
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