Real-time traffic congestion detection based on frame difference function and virtual loop

Traffic congestion has become one of the major concerns of policy-makers in modern metropolises. Accurate real-time traffic congestion alert is of great importance for alleviating congestion. In this paper, we propose a fast, unsupervised, video-based approach using average frame difference function (AFDF) and virtual loop to identify real-time traffic congestion. This novel method calculates the frame differences of specified order in a loop area to determine the speed of the vehicles. The proposed method has been integrated in the intelligent transport system (ITS) of Wuhan City, China for testing, and results show that the method is efficient and robust for real-time traffic congestion detection..