One of the biggest challenges in validating the electronic equipment of vehicles is finding suitable methods for virtual testing and simulating real-world scenarios as accurately as possible. Although computer simulations are safe and reproducible, there are significant simulation-to-reality gaps, making safety testing within simulations unreliable. Due to the lack of Precise sensor and traffic models, The data generated through simulation appears to be relatively realistic, still cannot replicate all the details of the real world. In this study, we propose to construct a secure and reliable assessment and validation platform by leveraging the combination of augmented reality technology and vehicle-in-the-loop simulation technique, which is called augmented reality-based proving ground vehicle-in-the-loop test platform. The method aims to combine real-world and virtual testing, making it easier and safer to test autonomous vehicles in critical scenarios while optimizing the validation process. Our proposed system offers an improved approach by combining simulated sensor data with real sensor data collect to generate augmented reality scenario data, which include AR based BUS sensor, AR based camera and AR based Lidar, providing more precise data support for the perception and decision-making processes of autonomous vehicles. In summary, the above-mentioned method provides a more comprehensive and accurate way of simulating scenarios, which can help improve the performance and safety of autonomous vehicles in the real world. Finally, we demonstrate the broader implications that such a simulation paradigm may have for autonomy, specifically showing how realistic sensor simulation can improve perception performance.