Towards an Ontology for Scenario Definition for the Assessment of Automated Vehicles: An Object-Oriented Framework
Not on the map. Why?
Abstract (arXiv)
The development of new assessment methods for the performance of automated vehicles is essential to enable the deployment of automated driving technologies, due to the complex operational domain of automated vehicles. One contributing method is scenario-based assessment in which test cases are derived from real-world road traffic scenarios obtained from driving data. Given the complexity of the reality that is being modeled in these scenarios, it is a challenge to define a structure for capturing these scenarios. An intensional definition that provides a set of characteristics that are deemed to be both necessary and sufficient to qualify as a scenario assures that the scenarios constructed are both complete and intercomparable. In this article, we develop a comprehensive and operable definition of the notion of scenario while considering existing definitions in the literature. This is achieved by proposing an object-oriented framework in which scenarios and their building blocks are defined as classes of objects having attributes, methods, and relationships with other objects. The object-oriented approach promotes clarity, modularity, reusability, and encapsulation of the objects. We provide definitions and justifications of each of the terms. Furthermore, the framework is used to translate the terms in a coding language that is publicly available.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jan 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 2; 2023: 1.
4 papers.
- 2021Towards Traffic Scene Description: The Semantic Scene Graphcited by 12
- 2022Using Ontologies for the Formalization and Recognition of Criticality for Automated Drivingcited by 12
- 2022Scenario-based Evaluation of Prediction Models for Automated Vehiclescited by 4
- 2023Bridging Data-Driven and Knowledge-Driven Approaches for Safety-Critical Scenario Generation in Automated Vehicle Validationcited by 3
- 2023Bridging Data-Driven and Knowledge-Driven Approaches for Safety-Critical Scenario Generation in Automated Vehicle Validation18 Nov 2023
- 2022Scenario-based Evaluation of Prediction Models for Automated Vehicles11 Oct 2022
- 2022Using Ontologies for the Formalization and Recognition of Criticality for Automated Driving3 May 2022
- 2021Towards Traffic Scene Description: The Semantic Scene Graph19 Nov 2021