Application of YOLO Algorithm for Intelligent Transportation Systems: A Survey and New Perspectives

With the rapid pace of urbanization and the growing complexity of traffic networks, the development of intelligent transportation systems (ITSs) has become increasingly vital for improving traffic efficiency, safety, and management. The You Only Look Once (YOLO) algorithm, a real‐time object detection model known for its high computational efficiency and detection accuracy, has emerged as a prominent tool within ITS applications. This survey presents a comprehensive review of recent advancements in the application of the YOLO algorithm across various ITS domains, including traffic monitoring, vehicle and pedestrian detection, and traffic sign recognition. The paper first outlines the methodology employed for literature selection and categorization, followed by an overview of the YOLO algorithm’s evolution and core technical components. Subsequently, it explores the algorithm’s practical implementations within different ITS scenarios. The review concludes with a synthesis of key findings and proposes future research directions, highlighting emerging trends and potential challenges. This work is aimed at providing researchers and practitioners with a structured understanding of YOLO’s current applications in ITS and at fostering further innovation in this interdisciplinary field.