Analysis of factors affecting accident severity in highway tunnels based on logistic model

Based on the traffic accident data collected from the 4 tunnels in Shaoguan section of Beijing-zhuhai freeway, taking the accident severity as dependent variable, selecting 9 candidate independent variables from 3 aspects: the time of the accident happened, the tunnel environment, and the traffic dynamic factors, the relevance between the candidate independent variables and the dependent variable was analyzed by the reverse selection method. It was found that the time of the accident happened, the collision type, the weather condition, and the ratio of daily PCU to AADT are the factors that most significantly related to the accident severity. The effects of these most related factors on the accident severity was analyzed using a logistic regression model. A statistical interpretation was given to the modeled estimates in terms of the odds ratio concept. The proposed logistic regression model was tested on the goodness-of-fit and predictive accuracy and the encouraging result was achieved.