• Dr.S.Bhavani
• Ajithkumar.C
• Darshini.K
• Kirubashini.R.S
• Kalaiselvan.M

Efficient traffic management is essential for ensuring safe and secure travel in high-traffic urban areas. Delays caused by congestion in densely populated regions with high mobility and commercial population adversely affects the day-to-day life of the public directly or indirectly. This project focuses on implementing a dynamic signal control system that leverages AI-driven technology to adjust traffic signal timings based on real-time traffic density. Using YOLO-based object detection and MOG2-moving object detection algorithm, the system processes video feeds from CCTV cameras to calculate vehicle density and optimize signal flow dynamically. By calculating the density at the signal, congestion can be cleared in optimized usage of time. This system mitigates delays, particularly during peak hours, ensuring smoother urban transportation without requiring manual intervention.

Dynamic Traffic Signal Control, Object detection algorithms – YOLO (You Only Look Once), MOG2(Mixture Of Gaussians)

"Dynamic Traffic Signal System in Urban Areas YOLO vs MOG2 ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.d255-d259, February-2025, Available :http://www.jetir.org/papers/JETIR2502330.pdf

"Dynamic Traffic Signal System in Urban Areas YOLO vs MOG2 ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppd255-d259, February-2025, Available at : http://www.jetir.org/papers/JETIR2502330.pdf