Study on Intelligent Driving School Vehicle System Based on Digital Twin Technology

Abstract

AbstractThe development of intelligent vehicle systems has progressed through multiple stages, evolving from initial basic functionalities to the integration of intelligent and automated technologies, achieving significant advancements. With technological advancements, intelligent vehicle systems have gradually introduced driving assistance features such as autonomous driving assistance and adaptive cruise control. In response to the developmental needs of intelligent driving school vehicle systems, a comprehensive research proposal is presented based on digital twin technology. By incorporating a multi-source data acquisition module, real-time collection and monitoring of various sensor data within the driving school vehicles are achieved, ensuring the acquisition of crucial information during the driving process. To facilitate efficient communication between the data monitoring center and the driving school vehicles, a driving school local area network is established, providing a solid foundation for data transmission and real-time monitoring. A user-friendly and intuitive front-end interface is designed to visualize vehicle status information and student driving data for instructors, enhancing the efficiency and effectiveness of driving school education. Finally, based on practical application tests, data processing of coordinate information is conducted and showcased in the front-end interface, validating the feasibility and practicality of the designed system in driving school vehicle management and educational training.