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Journal Article

Citation

Hu L, Li H, Huang J, Wang F, Lin M, Wu X, Wu N. Traffic Injury Prev. 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2022.2062333

PMID

35537007

Abstract

OBJECTIVE: The traffic characteristics of Sichuan and Guizhou differ from those of other regions due to its unique geographical features. In addition, accident studies in China mainly focus on urban roads in the eastern and central regions. However, studies on western regions, especially non-urban roads, are scarce. Thus, this study aims to explore the factors that influence the severity of accidents on non-urban roads in typical regions of Sichuan and Guizhou.

METHODS: A total of 541 cases from 2014 to 2020 were selected from the database of the China In-Depth Accident Study, where 18 variables, which may exert an impact on accident severity, were extracted after screening. First, heterogeneity of data was eliminated through latent class analysis (LCA). The ordered probit (OP) model was then conducted for each class to obtain significant variables that exert an impact on accident severity. The study quantified the degree of influence of the significant variables using marginal effect analysis.

RESULTS: The LCA results demonstrate that data were categorized into the following classes, namely, (a) two-vehicle accidents involving trucks, (b) pedestrian and multiple-vehicle accidents, (c) two-wheeler accidents, and (d) single-vehicle accidents. The OP results show that most variables could exert impact on accident severity, and some of them exerted varying levels of influence on the severity of different classes, whereas others only influence a specific class.

CONCLUSION: According to this study, we obtained the accident characteristics of these regions and put forward some targeted suggestions to further improve the level of road traffic safety. The findings can provide support for the construction of transportation in line with the regional characteristics in China.


Language: en

Keywords

ordered probit; accident severity; latent class analysis; Non-urban roads

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