Traffic Control Using Ai Smart Control System

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.