Review of Scenario-based Virtual Validation Methods for Automated Vehicles

Owing to the advancement in autonomous driving technology, testing tools and testing methods for conventional automobiles cannot meet the validation requirements of autonomous vehicles. Scenario-based virtual validation methods have technical superiority with respect to testing efficiency and time consumption. Such methods can aid in conducting autopilot test verification in the future and have thus drawn significant research interest. In this study, through the systematic analysis of a large number of related literature, the developmental history of scenario-based virtual testing associated with autonomous vehicles is reviewed. The differences among scenario definitions were compared and the connotation of a test scenario was defined. Various types of elements, data sources, and processing methods associated with scenarios were specified, based on which, various virtual testing methods for autonomous vehicles were identified and listed. Typical virtual testing methods, test platforms, and virtual test points were subsequently analyzed, and key technologies corresponding to software-in-the-loop testing, hardware-in-the-loop testing, and vehicle-in-the-loop testing were outlined. To address the issue of inadequate testing efficiency associated with the virtual testing process, scenario-based automated driving acceleration test technology was studied. Typical random scenario test generation methods and crucial scenario reinforcement generation methods were thereby determined and listed. Furthermore, issues and future development trends associated with scenario-based virtual validation of autonomous vehicles were also analyzed. The obtained results indicate that scenario-based virtual testing is essential for promoting the development of autopilot technology. Additionally, further research needs to be conducted on aspects, such as the development of test scenario database based on deconstruction and automatic reconfiguration, high-confidence models for human-vehicle-environment integration system, primary technologies for supporting virtual testing of automated vehicle driving through standard tool chains, mixed traffic simulation with testing under different autonomous vehicle penetration rates, iterative optimization and adaptive acceleration testing of automated driving, and establishment of standard systems for virtual testing of autonomous vehicles. © 2019, Editorial Department of China Journal of Highway and Transport. All right reserved.