A New Hybrid Architecture for Real-Time Detection of Emergency Vehicles

Abstract

VANET is a vital part of wireless networking. Vehicular movement is expanding indefinitely everywhere and is causing terrible problems to daily life. Almost all of the traffic lights now feature a fixed green light sequence and so green light sequence is determined without taking the existence of emergency vehicles into consideration. Consequently emergency vehicles such as ambulances, fire engines, police vehicles etc. are struck in traffic which might cause loss of valuable life and property. In this paper we present a new hybrid architecture for detection of emergency vehicles in real time. This hybrid architecture is based on the mixed features of image processing and machine learning. We also show the percentage decrease in the search space for the processing which results in faster detection of emergency vehicles.