The traffic accident hotspot prediction: Based on the logistic regression method

摘要

Traffic accident has posed a threat to the safety of human life. Accident often occurs in some certain areas. In order to achieve the target of the identification and judgment of the accidents hotspots during driving, and improve the driving safety of vehicle and the traffic efficiency through early warning, a research was done based on the recent collected 400 sets of accidents data of 10 major roads in Beijing city. Through the statistics of the typical factors, and the Logistic regression analysis, the relationships between the traffic accident and the road type, the vehicle type, the driver state, the weather, the date etc., were studied. Finally, the prediction model of accident hotspot was established. The results show that the location of car in road transects, the road safety grade, the road surface condition, the visual condition, the vehicle condition and the driver state are the most significant factors which may lead to traffic accident. Meanwhile, the prediction model established in this paper was validated to be capable of predicting the occurrence of accident, and the prediction accuracy is approximate 86.67%. The study provides not only a theoretical basis for vehicle safety assistance driving, but also the guidance for collision avoidance and optimization for path planning of intelligent vehicle.