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.
Highlights
A serious multi-fatality crash is defined as a motorvehicle crash resulting in more than 10 deaths,[1] which causes catastrophic losses of human life and property and even threats social stability
Bayesian networks were used to investigate the influence of risk factors on serious multifatality crashes
The Bayesian network was developed based on expert experience and the D-S theory, modified based on the test for conditional independence, and supplied with data from 484 serious crashes from 2000 to 2012 in China
Summary
A serious multi-fatality crash is defined as a motorvehicle crash resulting in more than 10 deaths,[1] which causes catastrophic losses of human life and property and even threats social stability. To date, little information about crashes resulting in many deaths and injuries has been published. Based on the Annual Reports of Road Accidents of the People’s Republic of China, there were in total 484 serious multi-fatalities crashes resulting in 7467 deaths and 7376 injuries from 2000 to 2012. The number of crashes was becoming less and less during this period, average deaths per crash kept stable and located between 14 and 17, meaning that the severity of crashes remains serious and worrying. It is necessary to analyze the factors affecting serious multi-fatality crashes and propose possible countermeasures to reduce the frequency and severity of such crashes
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