Objective: Particular testing by functional decomposition of the automated driving function can potentially contribute to reducing the effort of validating highly automated driving functions. In this study, the required size of test suites for scenario-based testing and the potential to reduce it by functional decomposition are quantified for the first time. Methods: The required size of test suites for scenario-based approval of a so-called Autobahn-Chauffeur (SAE Level 3) is analyzed for an exemplary set of scenarios. Based on studies of data from failure analyses in other domains, the possible range for the required test coverage is narrowed down and suitable discretization steps, as well as ranges for the influence parameters, are assumed. Based on those assumptions, the size of the test suites for testing the complete system is quantified. The effects that lead to a reduction in the parameter space for particular testing of the decomposed driving function are analyzed and the potential to reduce the validation effort is estimated by comparing the resulting test suite sizes for both methods. Results: The combination of all effects leads to a reduction in the test suites' size by a factor between 20 and 130, depending on the required test coverage. This means that the size of the required test suite can be reduced by 95-99% by particular testing compared to scenario-based testing of the complete system. Conclusions: The reduction potential is a valuable contribution to overcome the parameter space explosion during the validation of highly automated driving. However, this study is based on assumptions and only a small set of exemplary scenarios. Thus, the findings have to be validated in further studies. ARTICLE HISTORY

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A statistical, distance-based validation of highly automated vehicles is not feasible due to the high required testing distance. Scenario-based validation approaches promise to solve this issue. However, due to the high number of influence parameters, the number of possible parameter combinations is exploding. Therefore, exhaustive testing of all possible combinations is not feasible as well. Thus, a coverage criterion for scenario-based validation is required. Hereby, it is crucial that all stakeholders accept the coverage criterion. This paper proposes an approach to determine the number of scenarios that correspond to the required testing distance of the known distance-based approach. Furthermore, the number of scenarios that can be feasibly simulated for validation is estimated under certain assumptions. Comparing the required and the feasible number of scenarios shows that there is still a gap of around one order of magnitude. Nevertheless, combining this approach with other methods that aim to reduce the approval effort has the potential to get the required test coverage to a feasible level and therefore contribute to solving the validation challenge. However, there are still many remaining challenges, such as the availability of representative scenario catalogs or sufficient simulation models for environment perception sensors.

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