AI traffic light mangement system

This project presents a traffic management system that integrates computer vision and embedded control to enhance road monitoring and vehicle regulation at a four-way junction. A USB camera captures traffic flow from each direction, and the visual data is processed through a YOLOv8-based image processing framework to identify and count vehicles. The Arduino UNO serves as the central controller, interfacing with LEDs that act as traffic signals and a DC motor mechanism that rotates the camera to sequentially observe all road segments. The motor is operated through an L293D motor driver module, enabling directional control for comprehensive coverage. Based on the processed data, the system prioritizes the road segment with the highest vehicle density by assigning a green signal, while other roads remain halted through red or yellow signals. The design employs a 5V regulated power supply supported by a 12V adapter to operate sensors, indicators, and control units. This integration of computer vision with microcontroller-based actuation demonstrates a structured approach to traffic regulation, reducing congestion and improving traffic flow management at intersections.