Design of a Smart Traffic System for Vehicle Speed Measurement Based on YOLO v11 Video Analysis

Recent urbanization and population growth have created significant challenges in transportation due to increased residential density and the growing number of vehicles. Issues such as traffic congestion, accidents, and environmental pollution are major factors hindering sustainable urban development. To address these challenges, the necessity for Smart Traffic Systems has emerged, which can optimize vehicle flow and enhance safety through real-time data collection and analysis. This study aims to design a smart traffic system and video processing analysis system based on the latest image recognition technology, YOLO v11 (You Only Look Once). To achieve this, we implemented a mapping system (Cam2WorldMapper) utilizing the YOLOv11-n learning model and OpenCV's perspective transform method, enabling real-time monitoring of the traffic system in conjunction with speed coordinate systems. YOLOv11 demonstrates a high inference speed of 588 FPS, achieving a [email protected] of 66% and an F1 score of 69.6%, indicating its capability for accurate traffic situation detection. Furthermore, the system visualizes traffic data and provides intuitive information to users, thereby enhancing the efficiency of traffic management.