Digital Twin Test Method for Autonomous Vehicles based on PanoSim



This paper proposes an intelligent car testing and evaluation methodbased on digital twins, which is crucial for ensuring the properfunctioning of autonomous driving systems. This method utilizes digital twin testing technology to effectively map and integrate real vehicles in real-world testing scenarios with virtual test environments. By enriching the testing and validation environment for smart cars, this approach improves testing efficiency and reduces costs. Thisstudy connects real test vehicles with simulation software testingtoolchains to build a digital twin autonomous driving testing platform. This platform facilitates the validation, testing, and evaluation offunctional algorithms, and case study is conducted through testingand validation of an emergency collision avoidance system. Byrapidly applying digital twin testing and evaluation techniques forintelligent cars, this approach accelerates the development anddeployment of autonomous vehicles.