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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