• B Amaan Ahmed
• Prajwal
• Indu J A
• Serene Joshi
• Dr. Suma Swamy

The limited ever-increasing facilities and everincreasing demand for vehicular transportation have led to the development of Automated traffic management systems. Automated traffic management systems are cost-effective and require less human interaction in the management of traffic. Video processing/Image processing captures and processes real-world traffic scenarios such as a traffic signal at the junction. Various object detection algorithms are trained to count the number of vehicles struck in the traffic in each direction and an ML model is designed to output which direction of vehicles must be allowed to move first, based upon the weight of vehicles detected in the traffic in each direction. Most of the energy and time of human beings is spent on roads struck by traffic and thereby increasing air pollution as well. Therefore an efficient Automated transport management system helps in the management of traffic and overcomes the above-said problems.

Image Processing, object detection, Machine learning, Artificial Intelligence, Deepstream, Automated Traffic management system, Intelligent transport systems, Traffic Congestion, Identification, Classification, YOLO.

"Smart AI-Based Traffic control System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.d378-d382, May-2023, Available :http://www.jetir.org/papers/JETIR2305352.pdf

"Smart AI-Based Traffic control System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppd378-d382, May-2023, Available at : http://www.jetir.org/papers/JETIR2305352.pdf