Paper Title
Traffic Signal Pre-Emption for Emergency Vehicle

Abstract
Urban traffic congestion, particularly at intersections with traditional traffic signals, can cause significant delays for emergency vehicles like ambulances and fire trucks, affecting their ability to respond swiftly in critical situations. This research introduces an intelligent system designed to optimize the movement of emergency vehicles by reducing delays through smarter traffic management. Built using the SUMO simulation platform and Python with the TraCI interface, the system employs advanced algorithms such as Dijkstra's to calculate the best routes. These routes take into account real-world factors like road conditions, traffic congestion, and the number of intersections. To ensure smoother passage for emergency vehicles, the system dynamically adjusts traffic signals in real-time, allowing them to move through traffic more efficiently while minimizing the impact on regular commuters. The solution was rigorously tested in a variety of traffic scenarios, including heavy congestion, to demonstrate its reliability and adaptability. By incorporating modern tools and techniques, this system provides a practical approach to addressing the challenges of emergency response in urban environments, offering the potential for safer and more efficient traffic management in cities. Keywords - Congestion, Sumo, Traci, Emergency Vehicles, Urban Traffic Management