  Safety assurance of automated driving systems must consider uncertain
environment perception. This paper reviews literature addressing how perception
testing is realized as part of safety assurance. We focus on testing for
verification and validation purposes at the interface between perception and
planning, and structure our analysis along the three axes 1) test criteria and
metrics, 2) test scenarios, and 3) reference data. Furthermore, the analyzed
literature includes related safety standards, safety-independent perception
algorithm benchmarking, and sensor modeling. We find that the realization of
safety-aware perception testing remains an open issue since challenges
concerning the three testing axes and their interdependencies currently do not
appear to be sufficiently solved.
