Enhancing Scenario-based Testing for Automated Driving Systems: An Ontology-Based Scenario Modeling Framework
Résumé
emerges as a pivotal approach for validating the safe behaviors of Automated Driving (AD) and Advanced Driver-Assistance Systems (ADAS). Using virtual simulation, SbT allows for generating and running massive testing cases. This approach gathers typical driving situations and critical edge cases. Properly modeling representative scenarios is a primary challenge. A scenario model needs to account for complex components, such as roads, infrastructure, road users, and their behaviors and interactions. Ontology-based frameworks are proposed to model scenarios in a detailed manner. However, some limitations exist, such as (i) expressing dynamic behaviors, (ii) the capacity in complex scenario modeling to achieve more realistic simulation; and (iii) ensuring comprehensive ontology coverage and plausibility. This paper proposes an ontology framework addressing these shortcomings. A comparative evaluation is conducted using the developed quantitative metrics to assess the ontology framework against two other industrial ontologies.
| Origine | Fichiers produits par l'(les) auteur(s) |
|---|---|
| Licence |