Real Time Traffic Management System Using Machine Learning

Abstract

The increasing quantity of automobiles on the road presents difficulties for conventional traffic control strategies. With heavy traffic levels, these traditional methods find it difficult to handle. They only work well in light traffic situations; when there is a large difference in traffic volume on one side of the road or when vehicle density increases on one side, they are unable to adjust. Therefore, by adding dynamic signal switching capabilities, we want to modernise the static signal system. The updated system will continuously check and modify the timing of the signals in real time. In this project, we want to use real-time image detection to precisely measure traffic density and figure out the best times to switch signals, especially when traffic is heavy. Putting this strategy into practice should effectively reduce traffic jams and accelerate traffic flow.