Analysis of Influencing Factors for Traffic Violations Based on Intelligent Traffic Monitoring Systems
Wang Xinyan
Liang Haiqiong
Chen Jiahang
Li Shizhong
Li Bingzhang
Zhang Ping
Abstract：With the acceleration of urbanization,the impact of traffic violations on traffic safety and efficiency has become increasingly significant.To reveal the influencing factors and their mechanisms for traffic violations,this pa-per explored the influence mechanisms of four environmental factors,namely,time,space,traffic flow and weather for traffic violations based on the traffic violation data collected from Chengguan District,Lhasa in June 2023 by an intelligent traffic monitoring system,combined with multi-source heterogeneous data such as meteorological condi-tions,traffic flow,time and road attributes using machine learning models such as Random Forest(RF),XGBoost,C5.0 Decision Tree and Multi-Layer Perceptron(MLP).The research results showed that the Random Forest model significantly outperformed other models in prediction performance,with an accuracy rate of 93.17%,and yielded the best results in ROC(AUC=0.99)and PR curve(AP=0.989)evaluation.The feature contribution analysis based on SHAP showed that traffic flow,road type and time factors were key variables affecting violations,and the influence mechanisms of different types of violations(such as running red lights,violating traffic signs,etc.)are sig-nificantly different.This study quantifies the differentiated effect of environmental factors on traffic violations,pro-viding data support and theoretical basis for optimizing law enforcement resource allocation and formulating precise traffic management strategies.
Keywords：Intelligent traffic monitoring systemTraffic violationMulti-source dataMachine learning modelEn-vironmental factor
Publication Date：2025-07-30
Online Publishing Date：2025-08-18(First online date of this platform, not the publication date of the document)
Pages：7( 63-69 )