AI-Based Smart Traffic Management System for Emergency Vehicles

Abstract

Modern cities' main traffic congestion problem delays emergency vehicles like ambulances and firetrucks and police cars where every second counts. Fixed signal traditional traffic systems lack real-time adaptability, hence delays and risks are raised. This paper suggests an AI-driven smart traffic management system to priorities emergency vehicles and enhance general traffic flow by means of Raspberry Pi, YOLOv8, and OpenCV. Strategically positioned cameras provide video to a Raspberry Pi, which detects emergency vehicles by using OpenCV and YOLOv8. Dynamic control of traffic lights on detection helps to clear the path, so reducing response times and improving safety. The technology also maximizes road use and helps to ease traffic. For cities with limited infrastructure, using reasonably priced, open-source tools are scalable and ideal.