Research and Analysis of Urban Road Traffic Anomie Behavior Based on Fault Tree Model

Many traffic participants are not aware of traffic misconduct, which leads to frequent traffic accidents, which in turn worsens the traffic environment and increase economic losses. This paper designs a questionnaire survey on the anomie behavior of three types of traffic participants and analyzes influencing factors, such as age and gender, using SPSS21.0 analysis software. A fault tree model is established to determine the key factors affecting the anomie behavior of traffic participants and analyzes the degree to which the key factors produce anomie behavior. FreeFta software is used to analyze and calculate the minimum cut set and structural importance, as well as perform quantitative analysis and calculation of the probability and critical importance. Finally, according to the analysis results, the key factors are summarized, and targeted measures are given to the three types of traffic participants, which is of great significance to alleviate traffic accidents.