Traffic congestion and vehicular emission are some of the foremost issues faced by road users today. The traffic congestions can be caused by large red-light delays. The delays of respective red lights have been hard coded in the traffic light rather than being dependent on the traffic at each lane. In developing a solution to this problem, we will design a Smart Vison based Urban Traffic control system that optimizes signal timings while allocating green time to different intersection phases based on vehicle presence, vehicle count and flow-through data collected by Intelligent Cameras at intersections.
Autonomous traffic monitoring and control has been emerging research area from last 20 years. The systems are composed of vehicle detection and classification, road detection and obstacle detection. Advancement in surveillance systems and state of art algorithms in computer vision and pattern recognition has facilitated to detect features in images and determine the desired vehicles position with respect to road boundary.