Smart Control of Traffic Light Using Artificial Intelligence

Abstract

The rapid growth of urbanization has led to increased traffic congestion, making efficient traffic management a critical challenge for smart cities. Traditional traffic light systems operate on fixed timers, which often fail to adapt to real-time traffic conditions, resulting in unnecessary delays and fuel consumption. This project proposes an intelligent traffic light control system powered by Artificial Intelligence (AI) to dynamically manage signal timings based on real-time traffic flow data. By leveraging AI techniques such as machine learning and computer vision, the system analyzes traffic density through camera feeds or sensor data and optimizes signal duration accordingly. The model continuously learns from historical traffic patterns to improve decision-making over time. The implementation of such an AI-based solution aims to reduce waiting time, fuel consumption, and traffic congestion, ultimately enhancing road efficiency and commuter satisfaction. This project demonstrates the potential of AI in building adaptive, responsive, and efficient urban traffic control systems.