An AR-Based Meta Vehicle Road Cooperation Testing Systems: Framework, Components Modeling, and an Implementation Example

Abstract

In this study, we introduce an AR-based Meta-Vehicle Road Collaboration Testing System (AR-MVRTs), a significant advancement in autonomous driving testing. This system utilizes vehicle-road collaboration, Augmented Reality (AR), and Metaverse technologies for high-risk scenario simulation and dynamic interaction between virtual data and actual vehicles and infrastructure, enhancing verification and optimization methods. The core contribution is the innovative framework and component model, integrating AR with vehicle-road collaboration technologies for a comprehensive environment that includes real autonomous vehicles, virtual scenarios, and parameterized test settings. The AR-MVRTs method efficiently generates critical testing scenarios, significantly improving testing efficiency. An implementation case shows the system’s practical application, where AR-MVRTs demonstrated a 658-fold efficiency increase, completing tests in 8.5 hours compared to 5580 hours required by traditional test matrices. This integration accelerates the transition from theoretical research to practical applications and offers deep insights into autonomous vehicle safety and reliability. This research promises to advance autonomous driving technology and lay a solid foundation for its future development.