Software-defined traffic light preemption for faster emergency medical service response in smart cities

Proper management of rescue operations following an accident is one of the most fundamental challenges faced by today's smart cities. Taking advantage of vehicular communications, in this paper we propose novel mechanisms for the acceleration of the rescue operation resulting in a reduction in fatalities in accidents. We propose a Software-Defined Traffic Light Preemption (SD-TLP) mechanism that enables Emergency Medical Vehicles (EMVs) to travel along the rescue route with minimal interruptions. The SD-TLP makes preemption decisions based on global knowledge of the traffic conditions in the city. We also propose mechanisms for the selection of the nearest emergency center and fast discharge of the route of EMVs. Furthermore, depending on the dynamic traffic conditions on the streets at the time of the accident, an appropriate rescue route is selected for the EMV before its departure. The proposed approach is evaluated using the OMNET++ and SUMO tools over part of the Megacity of Tabriz, Iran. The simulation results demonstrate that the method can reduce the average rescue time significantly. The proposed approach keeps the resulting disruption in city traffic acceptably low while trying to shorten the rescue time as much as possible.