Research on Autopilot Trajectory Planning Based on Deep Learning

Abstract

Vehicle trajectory is usually used in driving behavior modeling and traffic safety. In order to obtain vehicle tracks in traffic video, an automatic acquisition method based on depth learning is proposed. In this paper, the YOLOV5 detector is used to detect vehicles in the region of interest in continuous frames, and the DEEPSORT tracker is used to track robust and fast vehicles. This tracker can effectively reduce the jump of target ID, improve tracking stability, obtain the real-world coordinates of vehicles through perspective transformation, and use a locally weighted regression algorithm to smooth the track. The experimental results show that the average multi-target tracking accuracy of the method in the expressway monitoring data set is 96.1%, and the average accuracy of trajectory acquisition is more than 93%. The smoothing algorithm can effectively remove the trajectory noise.