An Adaptive Traffic Control System Using Raspberry PI

By increasing of population the usage of vehicles have been increasing and controlling of traffic is one of the challenging works. The frequent traffic jams at major junctions call for an efficient traffic management system in place. The resulting wastage of time and increase in pollution levels can be eliminated on a city-wide scale by these systems. Previously the traffic control techniques used like magnetic loop detectors, induction loop detectors are buried on the road side provide the limited traffic information and require separate systems for traffic counting and for traffic surveillance. Here the project proposes to implement an artificial density traffic control system using image processing and Raspberrypi. The hardware here we are using is webcam, pc, Raspberry pi and the software used is OCCIDENTALIS and MATLAB. In this project the camera is get interfaced with a Raspberry pi. The image sequences from a camera are analyzed using thresholding method to find the density of vehicles. Subsequently, the number of vehicles at the intersection is evaluated and traffic is efficiently managed. In this project we implemented a real-time emergency vehicle detection system. In case an emergency vehicle is detected, the lane is given priority over all the others.