Welcome to Journal of Automotive Safety and Energy,

Journal of Automotive Safety and Energy ›› 2022, Vol. 13 ›› Issue (4): 643-650.DOI: 10.3969/j.issn.1674-8484.2022.04.005

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Analysis of the severity of vehicle to vehicle accidents considering the interaction of factors

ZHANG Daowen1,2,3(), WANG Chaojian1(), JIANG Jun1, LI Huawei4   

  1. 1. School of Automobile and Transportation, Xihua University, Chengdu 610039, China
    2. Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province, Chengdu 610039, China
    3. Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan, Chengdu 610039, China
    4. Chengdu Industrial Vocational Technical College, Chengdu 610218, China
  • Received:2022-05-09 Revised:2022-07-18 Online:2022-12-31 Published:2023-01-01

Abstract:

This paper investigated the key factors affecting the severity of vehicle to vehicle (V2V) accidents and the influence of the interaction of key factors on fatal- accident rate. Taking the 583 V2V accidents selected from the National Automobile Accident In-Depth Investigation System (NAIS) database (China) as samples, an analytical model of the V2V accident severity was established by the Bayesian network (BN). The association rule method was integrated to mine the rules with high frequency and strong coupling degree. The results showed that the factors, such as the at-fault party vehicle type, the at-fault party state, the injured party vehicle type, the accident time period, the accident place, and the traffic lights, have significant effects on fatal-accidents rate. The joint effect of factors was significant under the interaction of factors, and the effect was higher than the respective marginal effects. Road junctions had a higher incidence of accidents involving two passenger-cars, but the fatal accident rate is 18.4% lower than the a priori probability of the fatal accident rate. The fatal accident rate of a large car on the common roadway without traffic signals would be 42.6% higher than the a priori probability of the fatal accident rate.

Key words: traffic safety, vehicle to vehicle (V2V) accident, accident severity, Bayesian networks, association rules, interaction

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