DENSITY-BASED TRAFFIC CONTROL USING MACHINE LEARNING
International Journal for Research in Engineering Application & Management · 2024
Density-Based Traffic Control Using Machine Learning is a project used to develop a dynamic traffic signal system based on traffic density. The system can detect traffic densities at intersections and change the signal timing accordingly. In many big cities worldwide, traffic congestion is a significant challenge. The traditional traffic light schemeallocates a fixed amount of time for each side of the intersection, which is not adjustable for varying traffic densities. This project utilizes image processing, feature extraction, and segmentation techniques to manage traffic efficiently and improve traffic flow.