Paper Details

The number of vehicles on the road is increasing every day, and standard traffic management methods areinsufficient to deal with such a big volume of traffic. In today's scenario, the traditional strategy works well only whenthe count is low; if the density of vehicles on one side of the road increases, or if traffic is disproportionately heavier onone side than the other, the approach fails. As a result, we want to modify the traffic signal system from static to signalswitching, so that we can monitor and handle signals in real time. As a result, in this project, the signal switching timewill be determined using real-time image detection with high accuracy in crowded traffic. This approach has shown to bequite helpful in releasing congested traffic in a timely and efficient manner.

Prathamesh Kshirsagar, Pooja Nagawade, “Real Time Traffic Management Using Machine Learning”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 8, Issue 10, pp. 10-14, October 2021.