Analysis of pedestrian accident severity by considering temporal instability and heterogeneity
Pingfei Li,
Chengyi Zhao,
Min Li,
Daowen Zhang,
Qirui Luo,
Chenglong Zhang,
Wenhao Hu
Affiliations
Pingfei Li
School of Automobile and Transportation, Xihua University, Chengdu, 610039, China; Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province, Xihua University, Chengdu, 610039, China; Sichuan Xihua Jiaotong Forensics Center, Chengdu, 610039, China
Chengyi Zhao
School of Automobile and Transportation, Xihua University, Chengdu, 610039, China
Min Li
School of Automobile and Transportation, Xihua University, Chengdu, 610039, China
Daowen Zhang
School of Automobile and Transportation, Xihua University, Chengdu, 610039, China; Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province, Xihua University, Chengdu, 610039, China; Sichuan Xihua Jiaotong Forensics Center, Chengdu, 610039, China; Corresponding author. School of Automobile and Transportation, Xihua University, Chengdu, 610039, China.
Qirui Luo
Dongfang Electric Bulk Cargo Logistics Co., Ltd., Chengdu, 611731, China
Chenglong Zhang
School of Automobile and Transportation, Xihua University, Chengdu, 610039, China
Wenhao Hu
SAMR Defective Product Recall Technical Center, Beijing, 100000, China
The aim of this study was to investigate the effects of temporal instability and possible heterogeneity on pedestrian accident severity, 48786 accident data from 2018 to 2021 in the UK STATS database were used as the study object, and accident severity was used as the dependent variable, and 49 accident characteristics were selected as independent variables from 6 characteristics of accident pedestrian, driver, vehicle, road, environment and time to construct the pedestrian accident mean heterogeneity random-parameter logit model and examined its temporal stability. The results of model estimation and likelihood ratio tests indicate that the variables affecting pedestrian injury severity are highly variable and not stable over the years. And further demonstrates the potential of models that address unobserved heterogeneity for significant relationships in pedestrian accident severity analyses.
