Ontology based Scene Creation for the Development of Automated Vehicles
This addresses the need for economical and thorough testing processes in the development of automated vehicles, though it appears incremental as it builds on existing knowledge-based systems.
The paper tackles the challenge of generating comprehensive test scenarios for automated vehicles by proposing an ontology-based approach to create traffic scenes in natural language, aiming to supplement expert knowledge and enable large-scale scenario identification for safety analysis.
The introduction of automated vehicles without permanent human supervision demands a functional system description, including functional system boundaries and a comprehensive safety analysis. These inputs to the technical development can be identified and analyzed by a scenario-based approach. Furthermore, to establish an economical test and release process, a large number of scenarios must be identified to obtain meaningful test results. Experts are doing well to identify scenarios that are difficult to handle or unlikely to happen. However, experts are unlikely to identify all scenarios possible based on the knowledge they have on hand. Expert knowledge modeled for computer aided processing may help for the purpose of providing a wide range of scenarios. This contribution reviews ontologies as knowledge-based systems in the field of automated vehicles, and proposes a generation of traffic scenes in natural language as a basis for a scenario creation.