AI Based Traffic Control

Traffic congestion is a major challenge in modern urban areas, leading to increased travel time, fuel consumption, pollution, and road safety concerns. Conventional traffic signal systems operate on fixed-time schedules and are unable to adapt to real-time traffic conditions. To overcome these limitations, this project proposes an AI-Based Traffic Controller using Arduino Mega 2560 that dynamically controls traffic signals based on traffic density, emergency vehicle priority, and safety monitoring. The proposed system integrates ultrasonic sensors for vehicle detection, RFID technology for emergency vehicle identification, servo motors for signal control, and a camera-based AI module for helmet detection. The Arduino Mega 2560 functions as the central controller, processing sensor inputs and executing real-time decision logic, while AI-based image processing is carried out on an external system. The system improves traffic flow efficiency, reduces waiting time, enhances road safety, and provides a cost-effective and scalable solution suitable for smart city traffic management applications.