  The selection of relevant test scenarios for the scenario-based testing and
safety validation of automated driving systems (ADSs) remains challenging. An
important aspect of the relevance of a scenario is the challenge it poses for
an ADS. Existing methods for calculating the challenge of a scenario aim to
express the challenge in terms of a metric value. Metric values are useful to
select the least or most challenging scenario. However, they fail to provide
human-interpretable information on the cause of the challenge which is critical
information for the efficient selection of relevant test scenarios. Therefore,
this paper presents the Challenge Description Method that mitigates this issue
by analyzing scenarios and providing a description of their challenge in terms
of the minimum required lane changes and their difficulty. Applying the method
to different highway scenarios showed that it is capable of analyzing complex
scenarios and providing easy-to-understand descriptions that can be used to
select relevant test scenarios.
