TY - JOUR
T1 - Analysis of influence factors on severity for traffic accidents of expressway tunnel
AU - Ma, Zhuanglin
AU - Shao, Chunfu
AU - Li, Xia
PY - 2009/12
Y1 - 2009/12
N2 - 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.
AB - 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.
KW - Expressway tunnel
KW - Neural network
KW - Sensitivity analysis
KW - Severity
KW - Traffic accident
UR - http://www.scopus.com/inward/record.url?scp=74249108824&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:74249108824
SN - 1673-0291
VL - 33
SP - 52
EP - 55
JO - Beijing Jiaotong Daxue Xuebao/Journal of Beijing Jiaotong University
JF - Beijing Jiaotong Daxue Xuebao/Journal of Beijing Jiaotong University
IS - 6
ER -