Vehicle Actuated Traffic Signal using AI

Traffic congestion in urban areas leads to capacity issues, intersection delays, increased congestion, fuel consumption, and air pollution. Advanced traffic management systems, including adaptive signals and intelligent transportation systems, offer solutions to mitigate congestion and improve road network efficiency. Utilizing live camera imagery and AI for real-time traffic density assessment, alongside adaptive signal control algorithms, reduces congestion and optimizes traffic flow, aligning with the trend of technology-driven transportation systems for environmental benefits. YOLO (You Only Look Once) is a renowned AI object detection algorithm, enabling a vehicle-activated traffic signal to adjust timing based on traffic density, reducing congestion, wait times, and pollution. A simulation and prototype demonstrate the proposed system's effectiveness compared to fixed-time signals. It dynamically adjusts green signal durations based on traffic density, prioritizing high-traffic directions to minimize delays, congestion, and fuel consumption. Results show significant improvements in vehicles crossing intersections, with potential enhancements through real-world data calibration. Leveraging existing CCTV infrastructure, the system reduces deployment and maintenance costs compared to other intelligent traffic control systems. Integrating into major cities can enhance traffic management, with future features like traffic rule violation detection, accident identification, signal synchronization, and emergency vehicle adaptation, offering comprehensive traffic flow and safety solutions.