Intelligent VANET-based traffic signal control system for emergency vehicle prioritization and improved traffic management

Emergency vehicles (EmVs) are essential for saving lives and reducing damage in critical situations, yet their movement is often hindered by urban traffic congestion and inefficient signal control. Traditional fixed-time and pre-timed traffic signals lack the adaptability needed to prioritize EmVs, causing significant delays. This paper proposes an advanced, intelligent traffic signal control system based on Vehicular Ad-hoc Networks (VANETs) and Vehicle-to-Infrastructure (V2I) communication to optimize EmV passage and improve traffic flow. The system dynamically adjusts signal timings in real time, utilizing an adaptive control algorithm that calculates EmV arrival times, adjusts signal phases, and maintains balance to minimize disruptions to regular traffic. By leveraging V2I communication, traffic controllers receive instant updates on EmV locations and traffic conditions, enabling prioritized EmV passage. Simulation results using SUMO and OMNeT++ demonstrate that this approach can reduce EmV travel time compared to conventional systems, with minimal impact on regular traffic. The system also achieves a high success rate of preemption requests, ensuring that EmVs can pass through intersections without stopping. Furthermore, optimization results reveal that the proposed system outperforms Fixed-Time Control Methods (FTCM) with an average of 66.45% reduction in EmV travel times, Flexible Signal Preemption Methods (FSPM) by an average of 57.08%, and Intrusive Signal Preemption Methods (ISPM) by an average of 12.90%. Above findings highlight the potential of the proposed method in optimizing traffic flow, reducing emergency response times, and improving overall road safety. This research provides a scalable, real-world applicable model for enhancing emergency response efficiency in urban environments.