Ontology-based corner case scenario simulation for autonomous driving

Safety assessment of autonomous driving functions is an emerging topic in the automotive industry. In order to launch an autonomous vehicle on the road, the system running it needs to be able to react adequately in most of the cases, just like a human driver, if not even better. Furthermore, the amount of existing data that contains corner cases is nowhere near the amount of data needed to sufficiently train autonomous driving systems. The identification, classification and generation of corner cases for autonomous driving is a crucial part of scenario-based validation. In today’s world, a method that describes,generates and classifies those at the same time, is not available. In this thesis, a method for the description and generation of corner cases for autonomous driving is proposed. The method uses a template ontology, as a base for the scenario generation of corner cases with established definitions. The proposed approach also allows combining already described scenarios into new ones without any further actions. For an easy usage of the template ontology, an OntologyGenerator library for the simplified generation of corner cases is provided. ... mehrThe library completely eliminates the need for the user to work directly with the ontology and provides a method for creating scenarios even for users with little or no experience with ontologies. Moreover, the proposed approach is clean and understandable, making it easily scalable and extensible. The technique, follows the structure of OpenSCENARIO, thus making it easy to use, if one already understands OpenSCENARIO. In addition, the proposed ontology provides the base for the classification of the described scenarios to a specific corner case category. With the proposed technique, I was able to describe and generate seven scenarios, one for each of the earlier mentioned corner case categories. The resulting ontologies(created using the template ontology), that describe different corner cases, deliver correctly defined Open-SCENARIO files, after going through the Onto2OpenSCENARIOConverter. The resulted files deliver a correct simulation within CARLA, corresponding to the scenario description,which shows that the proposed method functions as expected.