YOLO-Powered Traffic Sign Detection and OpenStreetMap Integration for Intelligent Navigation
Duc-Hieu Hoang, Dinh Thuan Nguyen, Quoc Huy Tran, Thanh Trung Nguyen, Nhut Minh Nguyen, Duc Ngoc Minh Dang · 2025
This study presents the development of a deep learning-based traffic sign recognition system integrated with OpenStreetMap (OSM) to enhance smart navigation and traffic management. The system utilizes a You Only Look Once (YOLO)based model trained on the Vietnamese Camera-based Traffic Sign Recognition 47 (VCTSR47) dataset to detect and classify Vietnamese traffic signs accurately. A dashboard camera mounted on motorbikes or cars collects real-world traffic data, automatically recognizing traffic signs, extracting Global Positioning System (GPS) coordinates, and storing relevant information in a structured database. The extracted data is integrated into OSM via Application Programming Interfaces (APIs), enabling precise visualization and real-time alerts for critical traffic signs. The system’s performance is rigorously evaluated through various metrics, including mean Average Precision (mAP), Precision, Recall, and Frames Per Second (FPS). Experimental results confirm high recognition accuracy and real-time processing efficiency, demonstrating the feasibility and potential applications of deep learning and digital mapping in modern intelligent transportation systems.