Driving Automation System Test Scenario Development Process Creation and Software-in-the-Loop Implementation 2021-01-0062
Automated driving systems (ADS) are one of the key modern technologies that are changing the way we perceive mobility and transportation. In addition to providing significant access to mobility, they can also be useful in decreasing the number of road accidents. For these benefits to be realized, candidate ADS need to be proven as safe, robust, and reliable; both by design and in the performance of navigating their operational design domain (ODD). This paper proposes a multi-pronged approach to evaluate the safety performance of a hypothetical candidate system. Safety performance is assessed through using a set of test cases/scenarios that provide substantial coverage of those potentially encountered in an ODD. This systematic process is used to create a library of scenarios, specific to a defined domain. Beginning with a system-specific ODD definition, a set of core competencies are identified. These core competencies are then considered both in isolation and in conjunction with other potential confounding factors (e.g. other traffic or atmospheric conditions); with “edge cases” being represented as compounded or unique sets of confounding factors. Using this approach, a candidate scenario set is presented, along with a discussion of nuances and necessary considerations in scenario selection. These approaches are combined in a simulated environment to demonstrate their use. Finally, a strategy is proposed to automate the overall scenario testing process to make the execution less cumbersome. This process of test scenario creation strictly follows the ISO 26262 concept phase to verify the safety goals and functional safety requirements.
Citation: Patil, M., Lybarger, A., Midlam-Mohler, S., and Stoddart, E., "Driving Automation System Test Scenario Development Process Creation and Software-in-the-Loop Implementation," SAE Technical Paper 2021-01-0062, 2021, https://doi.org/10.4271/2021-01-0062. Download Citation
Mayur Patil, Alexander Lybarger, Shawn Midlam-Mohler, Evan Stoddart
Transportation Research Center Inc., The Ohio State University, General Motors LLC
SAE WCX Digital Summit
Simulation and modeling
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