Visible to the public Dynamic Traffic Control System Using Edge Detection Algorithm

TitleDynamic Traffic Control System Using Edge Detection Algorithm
Publication TypeConference Paper
Year of Publication2018
AuthorsRayavel, P., Rathnavel, P., Bharathi, M., Kumar, T. Siva
Conference Name2018 International Conference on Soft-Computing and Network Security (ICSNS)
KeywordsCameras, Communication networks, composability, congestion frequency detection, digital image processing techniques, dynamic traffic control system, edge detection, edge detection algorithm, electronic sensors, Image edge detection, image processing, image sequence, image sequences, magnetic coils, Metrics, pubcrawl, queueing theory, resilience, Resiliency, road traffic control, road vehicles, Roads, Scalability, security, smart city-smart travel, smart phone applications, smart phones, Traffic congestion, traffic engineering computing, Traffic light, traffic monitoring, traffic signal lights, transport network, Vehicles, vehicular queuing, Workstations

As the traffic congestion increases on the transport network, Payable on the road to slower speeds, longer falter times, as a consequence bigger vehicular queuing, it's necessary to introduce smart way to reduce traffic. We are already edging closer to ``smart city-smart travel''. Today, a large number of smart phone applications and connected sat-naves will help get you to your destination in the quickest and easiest manner possible due to real-time data and communication from a host of sources. In present situation, traffic lights are used in each phase. The other way is to use electronic sensors and magnetic coils that detect the congestion frequency and monitor traffic, but found to be more expensive. Hence we propose a traffic control system using image processing techniques like edge detection. The vehicles will be detected using images instead of sensors. The cameras are installed alongside of the road and it will capture image sequence for every 40 seconds. The digital image processing techniques will be applied to analyse and process the image and according to that the traffic signal lights will be controlled.

Citation Keyrayavel_dynamic_2018