Dynamic Path Planning and Traffic Light Coordination for Emergency Vehicle Routing

An ambulance or fire truck arriving a couple of seconds late can be the difference between life and death for some. As different technologies emerge, various approaches to expediting the movement of emergency vehicles have evolved. Horns, sirens and flashing lights were early attempts that are no longer sufficient in most places to clear traffic on the emergency vehicle’s route. In these situations, traffic signal preemption has made it possible to guide traffic to move in favor of clearing the emergency vehicle’s route. Early traffic signal preemption approaches depended on direct communication between an emergency vehicle’s signal emitter and a corresponding signal receiver on the traffic light it was approaching. Accordingly, the location of the vehicle could be detected. Later, (D)GPS was used to more accurately locate the emergency vehicle. This solution was further enhanced by using efficient or even optimal path planning algorithms to choose the route of the emergency vehicle. In the state-of-the-art in emergency vehicle routing, online static route selection is combined with traffic-light preemption to make emergency vehicle travel faster and safer along the chosen optimal path. In this thesis, we propose an enhancement to the state-of-theart approaches for reducing the emergency vehicle’s travel time. Our hypothesis is that combining traffic signal preemption with dynamic path planning will increase the efficiency of routing an emergency vehicle. We implement a graph version of the D*Lite informed search algorithm to efficiently and dynamically plan optimal paths for the emergency vehicle while taking into consideration the real-time updates of congestion levels and other delays to travel time. To further improve our solution, we propose a traffic light preemption strategy that seeks to ensure fast and safe travel of the emergency vehicle while, as a secondary priority, maximizes other traffic flow through the intersection. We evaluate our hypothesis through analytical experiments using our implementation of D* Lite, and further validate our proposed solution through scenarios developed using the VISSIM specialized microscopic traffic simulator [15]. The results validate our hypothesis demonstrating that dynamic path planning can improve travel time under uncertain congestion conditions, and that incorporating an appropriate traffic light preemption mechanism can further improve travel time for an emergency vehicle; potentially saving lives. Keywords— Emergency vehicle routing, Traffic signal preemption, Dynamic path planning, Signal phase selection