Controllable Path Planning and Traffic Scheduling for Emergency Services in the Internet of Vehicles

Dispatching emergency vehicles (EVs) to fatal accidents or fires as fast as possible is vital to save lives; however, minimizing an EV's travel time to the rescue spot is still an open challenge. This work presents a path planning and traffic clear-out scheduling scheme to lessen the EV's travel time in the vision of the Internet of Vehicles (IoV). Initially, the system searches a list of candidate paths to the rescue spot with the estimated time of arrival (ETA) at the EVs' maximum speed, regardless of the traffic conditions. After that, a vehicle clear-out process evaluates the delay time of clearing out the traffic obstacles on each path to identify the fastest driving path. Finally, the system estimates and issues the signal preemption schedules for the junctions of the selected route to coordinate the traffic flows and let the EV pass through smoothly. From the macro perspective, this work seeks to control the dynamic traffic proactively to reserve a lane for the EV - a feasible approach in the future of connected vehicles. This controllable model apparently contrasts with the conventional techniques of finding the least-cost paths with the uncertainty of traffic state prediction or traffic light preemption alone at the intersections. The simulation shows that our approach can outperform the state-of-the-art solutions in terms of the EV's travel time reduction, particularly if the congestion or heavy load road segments appear on the selected route but far from the departure location of the EV.

Automated summary

This study proposes a path planning and traffic clear-out scheduling scheme to reduce the travel time of emergency vehicles. By controlling dynamic traffic and coordinating traffic lights, the system outperforms traditional methods in simulation, especially in congested or heavily trafficked road segments.