Real Time Density Based Traffic Surveillance System Integrated with Acoustic Based Emergency Vehicle Detection

Abstract

As the problem of traffic congestion is prevalent in many metropolitan cities there is an urgent need for a traffic surveillance system which regulates the traffic in an efficient way. The current conventional methods such as timer based traffic control system is proved to be inferior to solve this issue and also the current systems does not give priority in the cases where emergency vehicles are detected. In this paper a smart traffic surveillance system has implemented where the access will be given to the lane having the highest density of traffic in the absence of emergency vehicle. When an emergency vehicle is detected in any lane, the priority shifts to the lane in which the emergency vehicle is present. Digital image processing techniques are used to compute the density of traffic and signal processing techniques are used to detect the presence of an emergency vehicle. The complete proposed system, from image and sound acquisition to canny edge detection and noise removal by Least Mean Square(LMS) filter and finally the green signal allotment to the lanes depending on the output results are illustrated with proper schematics and the final results are validated by hardware implementation.