Proposed Approach for Dynamic Automobile Traffic Management System

Road traffic is frequently congested due to the metropolitan cities' fast population expansion and urban mobility. The conventional approaches, including timers or human control, have been shown to be inadequate for resolving this problem. In order to handle a variety of challenges with controlling traffic on roadways and to assist authorities in effective planning, an abstract solution has been proposed to control traffic lights according to the density of vehicles on different lanes of road. The solution shall take input from surveillance cameras, evaluate the density using machine learning algorithm and provide the optimal time duration to manage traffic lights. This approach offers a substitute for the conventional approach, which uses monotonous, fixed-time traffic signals. The suggested strategy attempts to lessen road congestion while simultaneously improving the quality of transportation. Moreover, it also ensures minimum standby timing of vehicles on road intersections using graph structure and polynomials.