Vehicle Collision Warning Method Based on Trajectory Prediction

Abstract

Traffic intersections are hubs in the transportation network, but traffic intersections have become areas with a high incidence of traffic accidents due to their many branch intersections, dense vehicles, and complex traffic conditions. However, the use of Internet of Vehicles related technologies to solve such problems has Think it is an effective program. Although many collision warning schemes based on the Internet of Vehicles have been proposed, most of the schemes still have problems that need to be improved. The purpose of this article is to study the vehicle collision warning method based on trajectory prediction. This article introduces the improved vehicle collision warning algorithm based on trajectory prediction, and introduces the framework and composition of the vehicle collision warning system. Then we use the characteristics of vehicle driving to establish trajectory models for straight vehicles and turning vehicles, and use the established trajectories for the model, we calculate the trajectory prediction and collision warning of the vehicle at a traffic intersection for a period of time in the future. Aiming at how to make the collision warning performance better, we propose a collision warning method based on trajectory prediction, and then carry out the improved algorithm proposed. Simulation and performance evaluation, and finally design and realize an anti-collision safety early warning system combining vision and hearing. Experimental research shows that the CICW early warning algorithm in this paper has a collision hit rate of more than 80%, which can basically guarantee the accuracy of early warning of collisions between vehicles in the case of heavy traffic.