An optimal control strategy for emergency vehicle priority system in smart cities using edge computing and IOT sensors

Abstract

Smart city mission is a concept which improves economic growth and quality of life of people by using Information and Communication Technology (ICT). Smart cities collect data from various Internet of Things (IoT) sensors and manage the resources and provide service to the public. Emergency Vehicle Priority/Pre-emption (EVP) is one of the major IoT components in smart cities which saves many lives by giving right of way green signal to the Emergency Vehicles (EVs) such as ambulances and fire engines. The existing EVP system gives green signal to the EVs immediate by stopping the conflicting movements. The sudden stoppage of normal traffic as well as the sequence change generates confusion to the road users and drivers. This needs an optimal control strategy which gives green signal to EVs as well as it should not affect the normal traffic flow. This paper proposes an optimal control strategy for EVP using edge computing and IoT sensor for smart cities. The experiment was conducted using a GPS based IoT sensor which keeps on sending the Location Information (LI) to the edge server. The edge server computes the optimum timings based on the proposed control strategy algorithm and clears the emergency vehicles. Waiting time of other road vehicles before and after implementing the system have been studied at a traffic junction at Thiruvananthapuram, India. The comparison result shows that the average waiting time of vehicles on the other road is reduced by 73.23% in the proposed system when compared with the existing system. Since, edge computing has been deployed the latency in communication has been reduced less than 100 ms. So, the proposed solution reduces the waiting time of other road vehicles and reduces the latency in communication simultaneously.