ABSTRACT
The basic section and ramp of the expressway have different characteristics in many aspects, the characteristics and causes of traffic accidents are often different. In order to ensure the safety of freeway traffic, it is necessary to deeply study the influencing factors and their internal relations with freeway traffic accidents on basic sections and ramps. In this paper, traffic accidents in expressway basic section and ramp section are selected as the research object, and the influencing factors are analyzed by improved association rules from three aspects of data processing, key indicators, and subjective constraints to explore the mining method of traffic accident association rules. An improved algorithm for mining Apriori association rules considering accident attribute constraints is proposed to improve the efficiency of the algorithm, which needs to search the database many times. Mining and analysis of association rules are carried out for expressway accident data in the study area. Based on the improved Apriori association rule algorithm, this paper studies the relationship between the risk factors of traffic accidents on the freeway base section and ramp. The results show that the improved association rule mining algorithm can well reveal the causes and differences of accidents in different sections of expressways.
