Vehicle Detecting and Tracking Method Based on Range Information

An adaptive point-distance-based clustering method was developed based on the traits of the range information obtained by laser scanner. The point distance threshold could be automatically adjusted in this method according to both the distance and orientation of the objective car to the subjective one.Thereby the clustering accuracy was improved. A deterministic data association method, which took the motion property as the main constraints and the figuration as minor ones for cost function, was applied for the object tracking in order to improve the accuracy of correspondence. Considering the fact that the number of objects had to be given prior to tracking for the present deterministic data association methods, a modified data association method and tracker management strategy were developed. The trackers could be dynamically added and deleted according to the real road scene and the tracking process for the temporarily occluded and undetected objects could be maintained for a set period in this tracking method.The validity of the detection and tracking algorithm was verified by experiments.