Twin Scenarios Establishment for Autonomous Vehicle Digital Twin Empowered SOTIF Assessment
Zhonglin Hou, Shouwei Wang, Hong Liu, Yanzhao Yang, Yan Zhang
Abstract
The scenario-based tests have been an important means of improving the safety and reliability of autonomous vehicles (AVs). Moreover, ensuring the fidelity of generated scenarios is a safeguard for scenario-based tests. This article presents a new approach to generate twin scenarios for the virtual testing of AVs using meta scenarios. By extracting key parameter clusters from real-world scenarios and redefining and reassembling them, a large number of twin scenarios are generated. This approach addresses the need for diverse scenarios in AV virtual testing and enhances efficiency and hazard detection in the Safety of the Intended Functionality (SOTIF) assessment. The validity of twin scenarios, their temporal logic, and social attributes are verified using the UPPAAL tool, ensuring reliability and fidelity in virtual testing with AV digital twins. This innovative method offers a valuable solution to address challenges in AV virtual testing and improve the overall assessment process.