Automated generation of consistent models using qualitative abstractions and exploration strategies

Automatically synthesizing consistent models is a key prerequisite for many testing scenarios in autonomous driving to ensure a designated coverage of critical corner cases. An inconsistent model is irrelevant as a test case (e.g., false positive); thus, each synthetic model needs to simultaneously...

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Detalles Bibliográficos
Autores principales: Babikian, Aren A., Semeráth, Oszkár, Li, Anqi, Marussy, Kristóf, Varró, Dániel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Special Section Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525443/
https://www.ncbi.nlm.nih.gov/pubmed/36196213
http://dx.doi.org/10.1007/s10270-021-00918-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525443/
https://www.ncbi.nlm.nih.gov/pubmed/36196213
http://dx.doi.org/10.1007/s10270-021-00918-6

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