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The verification and validation of autonomous driving vehicles remains amajor challenge due to the high complexity of autonomous driving functions.Scenario-based testing is a promising method for validating such a complexsystem. Ontologies can be utilized to produce test scenarios that are bothmeaningful and relevant. One crucial aspect of this process is selecting theappropriate method for describing the entities involved. The level of detailand specific entity classes required will vary depending on the system beingtested. It is important to choose an ontology that properly reflects theseneeds.  This paper summarizes key representative ontologies for scenario-basedtesting and related use cases in the field of autonomous driving. Theconsidered ontologies are classified according to their level of detail forboth static facts and dynamic aspects. Furthermore, the ontologies areevaluated based on the presence of important entity classes and the relationsbetween them.

A Comprehensive Review on Ontologies for Scenario-based Testing in the Context of Autonomous Driving