Real-Time Detection and Tracking of Traffic Shock Waves by Conjugated Low-Angle Cameras

This paper proposes a method to detect and to track in real time three traffic shock waves (i.e., queuing, discharge, and departure) that appear in a section at a signalized intersection. Detection and tracking of the shock waves are accomplished by conjugated low-angle cameras, one of which is installed in front of the stop line and the other at a proper place behind the stop line. The cameras jointly monitor the regions of interest in the section with opposite and long-range views. On the basis of the weighted least squares method, the video data captured by the conjugated cameras are fused at the pixel level. Then the fused images are adapted to track the queuing and discharge shock waves in real time by a duplex, flexible window algorithm. Simultaneously, the Haar feature–based AdaBoost cascade classifiers are adopted to identify the vehicle tails and heads and to adjust the tracking results in the flexible window. To track the departure shock wave in real time, the discharge speed of vehicles is obtained through the combined tracking of sparse feature points of the vehicles in the regions of interest of the conjugated cameras. Experimental results show that the proposed method can track the traffic shock waves accurately in real time under changed light conditions during evening rush hour. The tracking results of the shock waves can be further applied to obtain various traffic parameters (e.g., queue length, stop delay, discharge time).