Traffic jams are still a major problem that makes it hard to speed up emergency response times in cities. Standard sirens and lights aren't enough to make sure that ambulances, police cars, and fire trucks can always get through intersections. This study proposes a VANET-based emergency vehicle priority routing framework that incorporates vehicle-to-vehicle (V2V) cooperation, roadside unit (RSU) coordination, and adaptive traffic signal pre-emption to address this issue. The methodology utilizes priority beaconing, collaborative lane-clearing protocols, and dynamic green-wave formation regulated by RSUs. To test how well the system worked with different traffic densities, a co-simulation environment that combined SUMO for traffic modeling and OMNeT++/Veins for network simulation was used. Results show that even in heavy traffic, the one-hop latency is less than 100 ms and the packet delivery rate is more than 95%. The protocol cut the time it took for emergency vehicles to get to their destinations by as much as 37% and the time it took for cars to clear intersections by 35%. It had little effect on non-emergency vehicles. Lightweight authentication methods made the system safe from spoofing, which made it more secure. The results show that this could work well in the real world, and that AI-based predictive traffic control and blockchain-assisted message verification could make it even better.