Investigating the Impact of Various Risk Factors on Victims of Traffic Accidents

Jianyu Wang, Huapu Lu, Zhiyuan Sun, Tianshi Wang and Katrina Wang
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Jianyu Wang: Institute of Transportation Engineering and Geomatics, Tsinghua University, Beijing 100084, China
Huapu Lu: Institute of Transportation Engineering and Geomatics, Tsinghua University, Beijing 100084, China
Zhiyuan Sun: Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
Tianshi Wang: Institute of Transportation Engineering and Geomatics, Tsinghua University, Beijing 100084, China
Katrina Wang: Division of Biosciences, University College London, London WC1E 6BT, UK

Sustainability, 2020, vol. 12, issue 9, 1-12

Abstract: In this study, our goal was to determine the impact of various risk factors on traffic accidents in the city of Shenyang, China, and to discuss the various common factors that influence pedestrian and non-motor vehicle accidents. A total of 1227 traffic accidents from 2015 to 2017 were analyzed, of which, 733 were accidents involving pedestrians and 494 were non-motor vehicle accidents. Among these traffic accidents, pedestrians and non-motor vehicle users had either minor or no responsibility. Sixteen influencing factors, including main responsible party attributes, pedestrian/non-motor vehicle user attributes, time attributes, space attributes, and environmental attributes were analyzed with regards to their impact on accidents using the binary logistic regression model (BLR) and the classification and regression tree analysis model (CART). Age, administrative division, and time of year were the three most common factors for pedestrian and non-motor vehicle accidents. For pedestrian accidents, the personal influencing factors of the main responsible party included illegal acts while driving and hit-and-run behavior. Factors affecting pedestrian and non-motor vehicle accidents also had different orders of importance.

Keywords: binary logistic regression (BLR); classification and regression tree (CART); victims; pedestrians; non-motor vehicles; impact on accidents (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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