Smart Control of Traffic Light Using Image detection

Abstract

Abstract: Urban areas are increasingly grappling with the issue of traffic congestion, a problem exacerbated by growing populations and the proliferation of motor vehicles. This not only leads to delays and increased stress for commuters, but also contributes to greater fuel usage and environmental pollution. This issue is particularly pronounced in large metropolitan areas. The escalating nature of this problem underscores the necessity for real-time assessments of road traffic density, which can lead to more effective traffic management strategies and signal control. The role of the traffic man controller is pivotal in influencing the flow of traffic, necessitating the optimization of traffic management system to cater to this burgeoning demand. Our proposed solution leverages live footage from intersection cameras to estimate traffic density through image processing and AI techniques. The system also incorporates a traffic signal switching algorithm based on vehicle density, aiming to alleviate traffic congestion. This, in turn, facilitates smoother movement for commuters and helps to mitigate pollution