Tracking Algorithm Application Integrating Visual and Radar Information in Intelligent Vehicle Target Tracking

Abstract

Abstract With the continuous development of various automobile technologies, the concept of intelligent automobile automatic driving has been introduced into people's lives, and it has great research value in traffic safety, traffic efficiency, and other aspects. Intelligent vehicles can accurately identify and track the target vehicle, which is one of the important preconditions for safe driving. However, a single tracking algorithm is often used in traditional intelligent vehicles with a low tracking accuracy under adverse circumstances. To solve this problem, a fusion tracking algorithm combining visual tracking and radar tracking algorithm is proposed, and intelligent vehicle target-tracking technology is constructed based on the fusion algorithm. Through the performance comparison test, it was found that the fusion algorithm proposed in the study had the highest accuracy of 93% and the highest F measure of 0.98, both of which were superior to the comparison algorithm. Then, an empirical analysis is made of the target-tracking technology proposed in the study. The results showed that the error range of yaw angle velocity of the target vehicle was −0.48 to 0.36, and the maximum root-mean-square error of lateral and longitudinal distance of the target vehicle detected by the technology was 0.03, which was superior to other tracking technologies. To sum up, the intelligent vehicle target-tracking technology proposed in the research can improve the accuracy of intelligent vehicle target tracking and provide a guarantee for the safe driving of intelligent vehicles.