Analysis of influence factors on severity for traffic accidents of expressway tunnel

Zhuanglin Ma*, Chunfu Shao, Xia Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

According to the accident information of Shaoguan tunnels for Beijing-Zhuhai expressway in China, a neural network model was constructed for the purpose of predicting the severity of accidents. In this model, 9 input variables were selected from three aspects, which are the time of traffic accident, tunnel environment and traffic dynamic factors, and the output variable was the severity of accident. Then the sensitivity analysis method was selected to study the effects of input variables on output variable. Three conclusions can be obtained. Firstly, the most contribution to the severity of accidents are the ratio of daily traffic volume and the AADT, and the proportion of large vehicles. Secondly, four input variables, which are weather, alignment, grade and accident location, have equal contribution to the severity of accidents. Thirdly, it is negligible that the time of accidents happened contributes to the severity of accidents.

Original languageEnglish
Pages (from-to)52-55
Number of pages4
JournalBeijing Jiaotong Daxue Xuebao/Journal of Beijing Jiaotong University
Volume33
Issue number6
Publication statusPublished - Dec 2009
Externally publishedYes

Keywords

  • Expressway tunnel
  • Neural network
  • Sensitivity analysis
  • Severity
  • Traffic accident

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