Development of a vehicle image-tracking system based on a long-distance detection algorithm

Abstract

If image-processing systems are developed to track individual vehicles, and thus, trace vehicle trajectories, many existing transportation models will benefit from more detailed information on individual vehicles. Furthermore, the additional information that can be obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration / deceleration patterns. Unlike human vision, however, image-processing cameras have difficulty in recognizing vehicle movements within a long detection zone because the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera relies on short-distance detection. This paper describes the methodology developed for monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long-distance tracking algorithm was developed with multiple closed-circuit television cameras. The algorithm can recognize individual vehicle maneuvers, and thereby increases the effectiveness of the incident detection process.