Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system

Integration of machine learning (ML) components in critical applications introduces novel challenges for software certification and verification. New safety standards and technical guidelines are under development to support the safety of ML-based systems, e.g., ISO 21448 SOTIF for the automotive do...

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Detalles Bibliográficos
Autores principales: Borg, Markus, Henriksson, Jens, Socha, Kasper, Lennartsson, Olof, Sonnsjö Lönegren, Elias, Bui, Thanh, Tomaszewski, Piotr, Sathyamoorthy, Sankar Raman, Brink, Sebastian, Helali Moghadam, Mahshid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975451/
http://dx.doi.org/10.1007/s11219-022-09613-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975451/
http://dx.doi.org/10.1007/s11219-022-09613-1

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