  The objective of this paper is to propose a systematic analysis of the sensor
coverage of automated vehicles. Due to an unlimited number of possible traffic
situations, a selection of scenarios to be tested must be applied in the safety
assessment of automated vehicles. This paper describes how phenomenological
sensor models can be used to identify system-specific relevant scenarios. In
automated driving, the following sensors are predominantly used: camera,
ultrasonic, \radar and \lidarohne. Based on the literature, phenomenological
models have been developed for the four sensor types, which take into account
phenomena such as environmental influences, sensor properties and the type of
object to be detected. These phenomenological models have a significantly
higher reliability than simple ideal sensor models and require lower computing
costs than realistic physical sensor models, which represents an optimal
compromise for systematic investigations of sensor coverage. The simulations
showed significant differences between different system configurations and thus
support the system-specific selection of relevant scenarios for the safety
assessment of automated vehicles.
