In-Depth Analysis of Pedestrian-Vehicle Accidents Based on Chi-Square Test and Logistic Regression

2019-01-5050

11/04/2019

Features
Event
New Energy & Intelligent Connected Vehicle Technology Conference
Authors Abstract
Content
Taking the pedestrian-vehicle accidents in the China in-Depth Accident Study (CIDAS) database as a sample case, 13 accidents morphological parameters were selected from three aspects: human, vehicle and environmental factors, and their depth analysis was carried out to obtain their distribution law through the card. The chi-square test and logistic regression method are used to analyze the correlation between the injury severity of pedestrians and other accidental morphological parameters in pedestrian-vehicle accidents. The results show that there is no significant correlation between gender/season and injury severity of pedestrians. The age of pedestrians and the collision speed is the strongest correlation with injury severity of pedestrians. When a pedestrian is over 65 years old, the pedestrian height is in the range of 160-170cm, the collision speed is greater than 60 kilometers per hour, and the pedestrian speed is greater than 8 kilometers per hour, the probability of pedestrian injury is significantly increased.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-01-5050
Pages
7
Citation
Lian, X., Deng, J., Li, X., and Cui, F., "In-Depth Analysis of Pedestrian-Vehicle Accidents Based on Chi-Square Test and Logistic Regression," SAE Technical Paper 2019-01-5050, 2019, https://doi.org/10.4271/2019-01-5050.
Additional Details
Publisher
Published
Nov 4, 2019
Product Code
2019-01-5050
Content Type
Technical Paper
Language
English