Traffic mangement system

Traffic congestion is one of the major challenges faced in urban areas, often caused by inefficienttraffic signal systems that operate on fixed time intervals regardless of vehicle density. This leads tounnecessary delays, fuel consumption, and increased pollution. To overcome this limitation, ourproject proposes an Intelligent Traffic Management System that dynamically controls signal timingbased on real-time traffic density at a junction. The system utilizes sensors or cameras to detect thenumber of vehicles on each side of the junction. A decision-making algorithm then analyzes thetraffic flow and allocates green signal priority to the side with the highest density, while ensuringfairness by setting maximum wait limits for other directions. This adaptive approach reduces idletime, improves traffic flow, and provides scope for emergency vehicle prioritization. By integratingreal-time analysis and smart allocation of signal timings, the proposed system demonstrates a moreefficient, reliable, and sustainable alternative to traditional fixed-time traffic signals. It has thepotential to reduce congestion, save travel time, and contribute to lower fuel consumption andemissions in modern cities.

Built With

• machine-learning
• python