Analysis of factors influencing traffic accidents on special road sections based on association rules data mining

Aiming at the problems of low data recall and precision, as well as low accuracy, in traditional methods for analyzing factors affecting traffic accidents, an analysis method of factors influencing traffic accidents on special road sections based on association rules data mining is proposed. Firstly, the Apriori algorithm with matrix optimization is used to efficiently mine traffic accident data on special road sections, Secondly, based on the 3σ principle, identify data anomalies and perform data repair, Finally, a hybrid Logit model is constructed to analyze the coupled effects of human vehicle road environment factors on accident morphology, in order to determine the influencing factors of traffic accidents on special road sections. The experimental results show that the proposed method achieves the highest recall, precision, and accuracy of accident data analysis, reaching 98.75%, 99.16%, and 98.63%, respectively, effectively improving the analysis accuracy of traffic accident influencing factors.