A Smart AI Based Solution for Traffic Management with Adaptation of Traffic Light

This paper introduces a smart traffic light management system designed to prioritize emergency vehicles while optimizing overall traffic flow. The system integrates two advanced algorithms: YOLOv9 (You Only Look Once) is utilized for real-time object detection and Deep Reinforcement Learning (DRL) for the control of adaptive traffic signal. YOLO identifies vehicles in real-time, while DRL manages to dynamically adjusts traffic light timings based on current traffic conditions and the presence of emergency vehicles. Ensure emergency vehicles are given priority through green lights at intersections while minimizing disruption to traffic. The proposed solution looks forward to improve response times for emergency services, reduce congestion, and generally enhance road safety, making it making it good fit for deployment in smart cities under the factors of scalability, adaptability, and efficiency in addressing the growing challenges of urban traffic management.