Autonomous Vehicle Architecture with Emergency Priority and Natural Disaster-Aware Traffic Management

This paper presents an integrated traffic simulation and control framework for autonomous vehicles (AVs) operating under emergency priority and natural disaster conditions. The proposed system models vehicle interactions using the Intelligent Driver Model (IDM) extended for police and emergency preemption and incorporates disaster-based dynamic rerouting and signal control. The simulation demonstrates how autonomous agents (police, emergency, and regular vehicles) can adapt to road closures, signal overrides, and evacuation directives to minimize congestion and improve emergency response time. This paper presents an integrated traffic simulation and control framework for autonomous vehicles (AVs) operating under emergency priority and natural disaster conditions. The proposed system enhances the Intelligent Driver Model (IDM) to support emergency-vehicle preemption, police-assisted clearance, and adaptive headway control under disruptive events. A co-simulation environment combining MATLAB and SUMO, is developed to model both microscopic vehicle dynamics and network-level V2X communication. MATLAB simulates congestion evolution, lane behavior, and speed adaptation during incidents or disasters, while SUMO manages the dissemination of emergency alerts, road-closure broadcasts, and cloud-based routing updates