Volume 39 Issue 4
Aug.  2021
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ZHENG Lai, GU Peng, LU Jian. A Cause Analysis of Extraordinarily Severe Traffic Crashes Based on T-S Fuzzy Fault Tree and Bayesian Network[J]. Journal of Transport Information and Safety, 2021, 39(4): 43-51+59. doi: 10.3963/j.jssn.1674-4861.2021.04.006
Citation: ZHENG Lai, GU Peng, LU Jian. A Cause Analysis of Extraordinarily Severe Traffic Crashes Based on T-S Fuzzy Fault Tree and Bayesian Network[J]. Journal of Transport Information and Safety, 2021, 39(4): 43-51+59. doi: 10.3963/j.jssn.1674-4861.2021.04.006

A Cause Analysis of Extraordinarily Severe Traffic Crashes Based on T-S Fuzzy Fault Tree and Bayesian Network

doi: 10.3963/j.jssn.1674-4861.2021.04.006
  • The T-S fuzzy fault tree and Bayesian network are integrated for an in-depth analysis to identify the main causes of extraordinarily severe traffic crashes. A T-S fuzzy fault tree is established, with the extraordinarily severe traffic crash taken as the top event, the human, vehicle, road, and environmental factors taken as the intermediate events, and 24 sub-factors taken as the basic events. The fuzzy fault tree is transformed into a Bayesian network, and the importance and posterior probability of the basic events can be inferred biaxially to determine the main causes. The results show that the method of fusing T-S fuzzy fault tree and Bayesian network can improve the accuracy and reliability of the analysis results of the causes of extraordinarily severe traffic crashes through forward and reverse reasoning and can determine improper operation, speeding, imperfect protection facilities, and bending. Slope combination, slippery road surface, and failure to drive following regulations are the six major causes of extraordinarily severe traffic crashes. The six major causes are analyzed, revealing that improper operation and speeding are more critical for extraordinarily severe traffic crashes.

     

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