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Certifiability Analysis of Machine Learning Systems for Low-Risk Automotive Applications

Authors :
Vasudevan, Vinod
Abdullatif, Amr
Kabir, Sohag
Campean, Felician
Source :
Computer; September 2024, Vol. 57 Issue: 9 p45-56, 12p
Publication Year :
2024

Abstract

We analyze the existing safety standard, ISO 26262, for automotive applications, determining the certifiability of machine learning (ML) approaches used in low-risk automotive applications. This can help assuring the security and safety of ML-based autonomous driving systems, gaining the trust of regulators, certification agencies, and stakeholders.

Details

Language :
English
ISSN :
00189162 and 15580814
Volume :
57
Issue :
9
Database :
Supplemental Index
Journal :
Computer
Publication Type :
Periodical
Accession number :
ejs67340605
Full Text :
https://doi.org/10.1109/MC.2024.3401402