Smart Traffic Management System for Urban Congestion

Abstract

This project presents an AIdriven Smart Traffic Management System for Urban Congestion that uses artificial intelligence and computer vision to improve traffic flow and road safety. The system enhances urban transportation by monitoring traffic conditions in real time, detecting vehicles, and analyzing traffic density at road intersections. It ensures efficient traffic signal management and intelligent decision-making through AI-based analysis. The system uses camera-based monitoring and image processing techniques to detect vehicles, identify traffic congestion, and provide adaptive traffic control. It can also detect road hazards such as potholes to improve road safety. Traditional traffic management systems rely on fixed traffic signal timings and manual monitoring, which are inefficient during peak hours and unexpected traffic conditions. These systems are unable to dynamically adjust to changing traffic patterns, resulting in increased congestion, longer travel times, fuel wastage, and higher pollution levels. There is a need for an intelligent, automated, and cost-effective traffic management system that can accurately monitor road conditions, optimize traffic flow, and support safer and smarter urban transportation.