Optimization of traffic lights using supervised learning

Abstract

With the increasing number of vehicles, conventional traffic lights with fixed times are unable to prevent traffic congestion at intersections . In this work, an intelligent traffic simulator is developed based on a Supervised Learning approach using artificial neural networks. The simulator makes decisions about which traffic light should be activated to minimise waiting times and maximise traffic flow, resulting in an intelligent management of green and red times.