| Abstract |
Urban areas face significant challenges in managing traffic congestion caused by heavy-load vehicles, hindering safe and efficient transportation. This study introduces an innovative method utilizing CCTV images and vehicle density analysis to identify trucks and large vans. The system employs the YOLO version 8 algorithm with Python, PyTorch, OpenCV, and Deep SORT to detect heavy-load vehicles in real-time and offer optimized routes to circumvent traffic jams. Through YOLO algorithms and vehicle density analysis, the system strategically directs heavy-load trucks across road networks, reducing congestion. Furthermore, the transportation management system improves overall traffic control by enforcing penalties for violations and ensuring lane adherence. This inventive approach shows promise in enhancing transportation efficiency and alleviating urban traffic congestion |
