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

  • Zhuanglin Ma*
  • , Chunfu Shao
  • , Xia Li
  • *此作品的通讯作者
  • Beijing Jiaotong University

科研成果: 期刊稿件文章同行评审

摘要

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.

源语言英语
页(从-至)52-55
页数4
期刊Beijing Jiaotong Daxue Xuebao/Journal of Beijing Jiaotong University
33
6
出版状态已出版 - 12月 2009
已对外发布

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 3 - 良好健康与福祉
    可持续发展目标 3 良好健康与福祉

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