Communication Dans Un Congrès Année : 2025

Enhancing Scenario-based Testing for Automated Driving Systems: An Ontology-Based Scenario Modeling Framework

Résumé

Scenario-based Testing (SbT)

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.

Fichier principal
Vignette du fichier
VEHITS_2025_89_CR.pdf (704.38 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-05034174 , version 1 (25-04-2025)

Licence

Identifiants

Citer

Zhenguo Cui, Svetlana Dicheva, Adam Abdin, Bernard Yannou, Jean-Marc Giroux. Enhancing Scenario-based Testing for Automated Driving Systems: An Ontology-Based Scenario Modeling Framework. 11th International Conference on Vehicle Technology and Intelligent Transport Systems, Apr 2025, Porto, Portugal. pp.622-630, ⟨10.5220/0013438800003941⟩. ⟨hal-05034174⟩
289 Consultations
313 Téléchargements

Altmetric

Partager

  • More