An efficient algorithm for detecting traffic congestion and a framework for smart traffic control system

Abstract

As the number of vehicles is increasing day by day; traffic jams are becoming very common in big cities like Dhaka. Due to this frequent traffic jams at major junctions, lots of man hours are being wasted. Lack of trained traffic police officers and old manual traffic light control system made this problem worse in many cities like Dhaka, Chittagong. Thus it creates a need for an efficient traffic management system. The paper proposes to implement an intelligent traffic control system which is based on the measurement of traffic density on the road using real time video and image processing techniques. The image sequences from a camera are analyzed using object detection and counting methods to obtain the most effective techniques. As in Bangladesh Rickshaw is the most popular vehicle and detection of Rickshaw was never done before efficiently. This model has addressed that problem efficiently. The number of vehicles at the intersections is evaluated and traffic condition could be smartly managed. The computed vehicle density can be compared with other parts of the traffic lanes in order to control the traffic signal intelligently. The system will detect vehicles under different challenging conditions and it has an advantage that we will use RFID sensors to ensure law enforcement. Thus any car or vehicle which breaks traffic rules can be easily caught. By this paper we intend to present an improvement in existing manual traffic control system. It also discusses about using the timer for each phase and detecting vehicles through images instead of using electronic sensors embedded in the road. Finally the traffic lights will be controlled according to the traffic conditions on road.