Development of an IoT-Based Intelligent Traffic Signal Prioritization System for Emergency Vehicles in Congested Urban Environments

Rapid urbanization and rising traffic congestion in developing cities have greatly reduced the effectiveness of emergency response services. In Port Harcourt, Nigeria, emergency vehicles often have to wait a long time at signalized intersections, which raises the risk of death, property loss, and public safety issues. This paper outlines the design, simulation, and performance assessment of an Internet of Things (IoT)-based Emergency Vehicle Prioritization (EVP) system intended to enhance emergency mobility in congested urban traffic. The proposed system employs GPS-enabled emergency vehicles, IoT communication protocols, and adaptive traffic signal control to dynamically adjust signal phases in real time and prioritize vehicles at intersections. A quantitative experimental approach was employed utilizing a unified simulation environment that integrates SUMO and Python. We examined performance in both baseline (non-EVP) and EVP-enabled situations using metrics such as emergency response time, intersection delay, queue length variation, average vehicle delay, system latency, and reliability. Results show that EVP significantly reduces the time it takes for emergency responders to arrive at the scene and for vehicles to cross intersections, while maintaining acceptable service levels for non-emergency traffic. The time from detection to preemption remained within real-time operational limits, and the system was up more than 97% of the time, indicating high reliability. The results show that using IoT to prioritize emergency vehicles is a good, scalable, and context-appropriate way to make emergency response more efficient in crowded urban areas, especially in cities that are still developing.