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In-Depth Analysis of Pedestrian-Vehicle Accidents Based on Chi-Square Test and Logistic Regression
ISSN: 0148-7191, e-ISSN: 2688-3627
Published November 4, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
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.
CitationLian, 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.
Data Sets - Support Documents
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