Abstract 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.
Systematically Generated and Complete Tests for Complex Driving Scenarios
2019-01-01
11 pages
Article/Chapter (Book)
Electronic Resource
German
Ship Model Tests in Ice with Systematically Varied Ice Parameters
British Library Conference Proceedings | 1990
|Towards Procedures for Systematically Deriving Hybrid Models of Complex Systems
German Aerospace Center (DLR) | 2000
|Systematically testing optical MEMS speeds production
British Library Online Contents | 2001
|Upgrading of highways for safety -- Systematically
Engineering Index Backfile | 1968
|