Smart Traffic Control and Management System using Machine Learning Techniques

Abstract

This paper explores a Smart Traffic Control System incorporating dynamic signal switching and Intelligent Transport Systems (ITS) to combat urban traffic congestion. It focuses on dynamic signal adjustments based on real-time vehicle density, aided by YOLOv4 vehicle detection. This fusion of dynamic signal switching, ITS, and YOLOv4 aims to optimize traffic flow. The paper discusses technical aspects, benefits, and challenges, offering the potential to revolutionize urban transportation. With data-driven adaptability, this system promises to transform traffic into a more efficient urban ecosystem. The overall results found is satisfactory.