Vision-based vehicle queue detection at traffic junctions

Real-time traffic queue detection can directly aid in dynamic traffic light control at road junctions. In this paper, we propose an efficient technique to detect vehicle queue lengths at traffic junctions based on progressive block based image processing. We also propose a two-step approach for vehicle detection that relies on edges and dark features in the image. It is shown that this vehicle detection approach is robust to heavy and light shadows. Further, the threshold adapts itself dynamically to handle varying light conditions. Evaluation of the proposed method using over 45 real video sequences shows nearly 100% accuracy in vehicle detection and queue length estimation.