Z.K. Chang, Y.W. Chen, X. Feng

Pages: 57-66

Abstract
Traffic accident analysis refers to mining the regularity of traffic data through effective analysis of traffic data, so as to take preventive measures to reduce accidents and ensure safety. In order to improve the effectiveness of traditional traffic accident factor analysis methods, a traffic accident multi factor analysis method based on driving behavior is proposed in this paper. Firstly, collect traffic driving behavior data to determine the types of traffic driving violations; Secondly, the constraint conditions of traffic accidents are determined by using fault tree; Finally, according to the generated sequence, the traffic accident multi factor analysis model is established, and the first-order ordinary differential equation is established to solve the parameters in the model, so as to realize the traffic accident multi factor analysis. The experimental results show that the accuracy of this method is as high as 97.68%, and it has better effect of traffic accident factor analysis.
Keywords: fault tree; correlation analysis; first order ordinary differential equation; cumulative generation sequence