Traffic Management System Using YOLO

As the population of cities and the number of vehicles grows, traffic congestion is becoming an important problem. Gridlock not only causes long delays and driver frustration but also results in wasted fuel and air pollution. Although this problem exists everywhere, it is especially prevalent in large cities. Considering this continued urbanization, real-time estimations of road traffic density are critical to optimize signal control and optimal traffic management. Traffic controllers have a significant impact on traffic flow. Therefore, there is an urgent need to enhance traffic management to cope with increasing demands. Our solution is to utilize artificial intelligence and image processing methods to examine real-time video data from traffic intersection cameras to identify traffic density. In addition, the system targets an algorithm that adapts traffic signals developed according to vehicle concentration to ease congestion, improve passenger travel times, and minimize environmental pollution.