Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure

Abstract

This study aims to identify and analyze risk factors affecting serious multi-fatality crashes using Bayesian networks. First, a Bayesian network structure was constructed based on expert experience and the Dempster-Shafer evidence theory. Second, the structure was amended to satisfy the conditional-independence test. Finally, 484 serious multi-fatality crashes for the period 2000-2012 in China were inputted into the Bayesian network to calculate the posterior probability of each factor. Results showed that the most influential factor was driver behavior, followed by vehicle condition, road condition, and external environment. And compared to the other behaviors, speeding and mistaken adjustment had greater influence on serious crashes. The findings in this study provide useful and valuable information for engineers to take corrective and preventative measures to reduce the probability for serious multi-fatality crashes.