Systematically Generated and Complete Tests for Complex Driving Scenarios

A key success factor when realizing autonomous vehicles is the validation of their functionality. Due to their system architecture involving multiple environmental sensors, such as video cameras and LIDAR sensors, the input vector into the Advanced Driver Assistance System (ADAS) is high dimensional. The signal processing has to reliably execute the perception and cognition of the current driving situation. The environment consists of an arbitrary number of elements, including traffic participants, material properties, weather conditions, road signs or buildings. Based on the availability of a semantic, machine-readable representation of scenarios, such driving situations can be described. This allows the realization of a continuously growing test case database for the validation of autonomous driving functions.