Dynamic Traffic Control System Using Video and Image Processing

Abstract

Traffic congestion is a serious problem in cities, leading to delays, wasted fuel, and more accidents. Current traffic signal systems often use fixed timing, which doesn’t change based on traffic levels. This makes managing traffic less effective. The motivation behind this project is to create a better traffic control system that adapts to real-time traffic. By using live camera feeds and image processing, we can count vehicles at intersections and adjust traffic lights based on the number of cars present. This helps traffic flow more smoothly, reduces waiting times, and saves fuel. The outcome of this system is improved traffic management. Traffic lights will be smarter, only turning green when needed, and preventing empty roads from having green lights. This saves time and fuel, making travel easier and safer. The innovation in this project comes from using image processing instead of old sensor-based systems. Image processing gives a clearer and more accurate view of traffic, making the system more reliable and effective for modern cities.