Traffic Vision: AI-Powered Traffic Monitoring System and Signal Optimization

This paper is focused on Traffic Vision, an integrated AI-powered traffic monitoring and management system built on computer vision, machine learning, and adaptive control strategies to optimize urban traffic flows. The major functions of the system include real-time processing of video feeds for vehicle, pedestrian, emergency vehicle, and accident detection and tracking, as well as traffic density and flow parameters. A new adaptive traffic signal control algorithm employs this information to dynamically adapt traffic light timings according to current conditions. Experimental results show a wait time reduction of up to 30% in intersections and highly improved emergency vehicle response times. This modular architecture allows it to easily fit into any urban framework and match existing infrastructure monitoring systems.