• Christo Alias
• Muhsin Muhammed
• Jerin Peause
• Pranav S Nair
• Meenu Varghese

Efficient traffic control management is one of the foremost important challenges of our country. Several efforts are implemented within the country to manage traffic including road expansion, highway development, and application of several traffic schemes. one among the researches thrust being studied is that the solution to the limitation of traditional traffic signal systems. the answer to the present control problem should be ready to prioritize congested lanes consistent with corresponding traffic density. The proposed system discussed an approach in developing a traffic signaling system capable of prioritizing congested lanes supported Vehicle Counting System (VCS) and real-time traffic density data. The VCS uses computer vision technology which is a sub field of Machine Learning. The vehicle counting system is formed from three main components: a detector, tracker, and counter. The detector identifies vehicles within this frame of video and returns a listing of bounding boxes around the vehicles to the tracker. The tracker uses the bounding boxes to trace the vehicles in subsequent frames. The detector is additionally wont to update the trackers periodically to make sure that they're still tracking the vehicles correctly. The system works with CCTV cameras positioned at every lane of the intersection in each direction for the acquisition of traffic density data. This data is then used for deciding after processing and prediction. The system will effectively manage holdup by keeping the flow of traffic in each lane through real-time monitoring.

Traffic control management, Vehicle Counting System, Machine Learning, Vehicle Count, Prioritizing, Frames

"INTELLIGENT TRAFFIC CONTROL SYSTEM USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.87-90, June-2021, Available :http://www.jetir.org/papers/JETIRET06017.pdf

"INTELLIGENT TRAFFIC CONTROL SYSTEM USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. pp87-90, June-2021, Available at : http://www.jetir.org/papers/JETIRET06017.pdf