A Proposal of the OWL-Python Framework for the Systematic Generation of Comprehensive Patterns of Scenarios in the Road

Abstract

In automatic driving technology, various technological developments was highlighted recently, and it goes to a serious discussion for making a standard criterion of the safety assessment. According to an international leading project, such as PEGASUS project in Germany, test scenarios are need to be clarified. As the important concept, they provided the scenarios can be classified as three abstract levels, called Functional Scenario (FS), Logical Scenario(LS), Concrete Scenario(CS). LS is highly important to establish as the open format as discussed in those international community. In this study, we focused on the LS and proposed a generative use-cases in the test scenario, which can automatically imported the ontology data format. This framework is based on the mesoscopic model that we proposed in 2018, which detect representative cases to face the car-collision with respect to the representative trajectory description. This approach will contribute to the refinement of the logical scenarios according to requirements, effective reduction the number of scenarios rather than CS and bridge between FS and CS.