Towards computer vision-based approach for an adaptive traffic control system
Mohamed Maher Ata, Mohamed El-Darieby, M. Abd Elnaby, Sameh A. Napoleon · The Imaging Science Journal · 2018
In this paper, an adaptive traffic control system (ATCS) is proposed using the state of the art of video processing techniques. We illustrate how the system controls standard four-way intersections using three parameters; namely, average vehicles flow speed, level of crowdedness of vehicles, and a critical state timer. These parameters are detected from traffic videos using our computer vision algorithm. The ATCS decision-making process has been designed to adapt to predefined priorities over the traffic parameters. The validation of the proposed ATCS has been tested using four synchronized test videos in order to feed the proposed ATCS with different traffic information. Experimental results show a complete adaptation for the traffic flow.