  Corner cases for driving automation systems can often be detected by the
system itself and subsequently resolved by remote humans. There exists a wide
variety of technical approaches on how remote humans can resolve such issues.
Over multiple domains, no common taxonomy on those approaches has developed
yet, though. As the scaling of automated driving systems continues to increase,
a uniform taxonomy is desirable to improve communication within the scientific
community, but also beyond to policymakers and the general public. In this
paper, we provide a survey on recent terminologies and propose a taxonomy for
remote human input systems, classifying the different approaches based on their
complexity.
