Vehicle Traffic Management Using CNN Algorithm

The goal is to build a traffic light system that changes based on how many people are in the area. When there is a lot of traffic at an intersection, the signal time automatically changes. Many major cities around the world have a lot of traffic, which makes it hard to get to work every day. Traditional traffic signal systems are based on the idea that each side of the intersection has a set amount of time. They can’t be changed to account for more traffic. People can’t change the times of the intersections that have been set up for them. There may be more traffic on one intersection, which could make it more difficult for the typical green period to end. After processing and translating the traffic signal object detection into a simulator, a threshold is set and a contour is drawn many cars are in the area. After , we can figure out which side has the most cars based on the signals sent to each side. Paper provides a solution based on camera feed at crossing for each lane process the data through and allocates the ”green” time according to its traffic flow density using YOLO v3 and also takes care of starvation issue that might arise of the solution. As a result ,the flow of traffic on each lane is automatically optimized and the congestion that used to happen unnecessarily is eliminated earlier and results show significant benefits in reducing traffic waiting time