Jenish Joshi, Gauri Rao, Bhavya Divecha, Anishk Jaiswal
These days, traffic congestion is a major issue. Urban areas are the ones most impacted by it, despite the fact that it appears to be present practically everywhere. Given that it is always increasing, it is essential to be aware of the road traffic density in real time for better signal control and effective traffic management. Different factors, such as inadequate capacity, unregulated demand, long wait periods, etc., can contribute to traffic congestion. Although insufficient capacity and unchecked demand are somewhat related, each light's delay is hard-coded and unrelated to traffic. In order to effectively meet this growing demand, traffic control needs to be optimised and simulated. For traveller information, ramp metering, and real-time updates, image processing and surveillance systems have been extensively used in traffic management in recent years. Image processing can also be used to estimate traffic density. This project demonstrates how to calculate the real-time traffic density using image processing using live images from the cameras at traffic intersections. It also focuses on the algorithm for adjusting traffic signals in accordance with the number of vehicles on the road, with the goal of minimising traffic congestion and subsequently the frequency of accidents. People will be able to travel safely as a result, and both fuel usage and waiting times will be decreased. Additionally, it will deliver considerable data that will support study and planning of next road projects. With the goal of reducing traffic congestion and promoting free flow of traffic, additional traffic lights may be synchronised with one another. The technology doesn't use electronic sensors buried in the pavement to find the automobiles; instead, it uses photographs. There will be a camera set up next to the traffic light. It will record video clips. A better method to manage the traffic light's state change is image processing. It demonstrates the ability to lessen traffic congestion and prevents time from being lost due to a green signal on an empty road. Because it makes use of actual traffic photos, it is also more accurate in calculating the presence of vehicles. It performs far better than systems that rely on the
Article Details
Unique Paper ID: 155940

Publication Volume & Issue: Volume 9, Issue 2

Page(s): 875 - 887
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