Denver-Baraka/real_time_traffic_control

AI driven traffic control sytsem # Real Time Traffic Signal Control System Using AI ## Overview This project implements an AI-driven real-time traffic control system designed to optimize urban traffic flow, reduce congestion, and minimize environmental impact. By leveraging artificial intelligence, real-time data, and advanced simulation techniques, this system dynamically adjusts traffic light timings and provides intelligent routing assistance to vehicles. The project includes both a comprehensive SUMO (Simulation of Urban MObility) simulation environment and a physical prototype built with Raspberry Pi and YOLO (You Only Look Once) for vehicle detection. ## Features - **AI-Powered Traffic Signal Optimization:** Dynamic adjustment of traffic light timings based on real-time traffic density and flow, utilizing machine learning algorithms. - **SUMO Simulation Environment:** A detailed simulation of a city network (based on Nairobi) with over 20 routes and interconnected intersections to test and validate AI algorithms under various traffic scenarios. - **Intelligent Vehicle Routing:** AI-assisted routing mechanisms that provide optimal path recommendations to drivers, minimizing travel time and avoiding congested areas. - **Physical Prototype:** A small-scale physical intersection model using Raspberry Pi 3B+, camera modules, and LED arrays to demonstrate real-time vehicle detection (YOLOv5s) and adaptive signal control at the edge. - **Communication Protocols:** Implementation of communication protocols (e.g., MQTT) for seamless data exchange and coordination between different components and intersections. - **Data Analysis and Visualization:** Tools and scripts for analyzing simulation results, traffic patterns, and system performance metrics. - **Incident Detection:** Automated reporting of simulated traffic incidents within the SUMO environment. ## Project Structure ``` real-time-traffic-signal-ai/ ├── .github/ │ └── workflows/ │ └── main.yml # CI/CD pipeline (optional …