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An Analysis of ISO 26262: Machine Learning and Safety in Automotive Software
Technical Paper
2018-01-1075
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Machine learning (ML) plays an ever-increasing role in advanced automotive functionality for driver assistance and autonomous operation; however, its adequacy from the perspective of safety certification remains controversial. In this paper, we analyze the impacts that the use of ML within software has on the ISO 26262 safety lifecycle and ask what could be done to address them. We then provide a set of recommendations on how to adapt the standard to better accommodate ML.
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Citation
Salay, R., Queiroz, R., and Czarnecki, K., "An Analysis of ISO 26262: Machine Learning and Safety in Automotive Software," SAE Technical Paper 2018-01-1075, 2018, https://doi.org/10.4271/2018-01-1075.Also In
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