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Failure safety analysis of artificial intelligence systems for smart / autonomous vehicles
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Pourdanesh, Faranak, Dinh, Truong Quang, Tagliabo, Fulvio and Whiffin, Phill (2022) Failure safety analysis of artificial intelligence systems for smart / autonomous vehicles. In: 2021 24th International Conference on Mechatronics Technology (ICMT), Singapore, 18-22 Dec 2021. Published in: Proceedings of the 2021 24th International Conference on Mechatronics Technology (ICMT) pp. 1-6. ISBN 9781665424592. doi:10.1109/ICMT53429.2021.9687283
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Official URL: http://dx.doi.org/10.1109/ICMT53429.2021.9687283
Abstract
Up to now failures in artificial intelligence systems, specifically machine learning algorithms which are their software components, are considered as systematic failures. The goal of this paper is to introduce a new concept of quantitative failure analysis for machine learning algorithms which can be used in smart/autonomous vehicles to guarantee sufficiently low risk of residual errors in this application. Firstly, a coincidence in evaluating impacts of unpredictable behaviours of machine learning algorithms and hardware components is introduced in order to statistically estimate failure rate based on a given number of data points. Next, a metric utilising this randomic failure rate is proposed to assess functional safety of smart and/or autonomous vehicles and evaluate their safeness according to ISO 26262:2018, and ISO/PAS 21448.
| Item Type: | Conference Item (Paper) | ||||||
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||
| Journal or Publication Title: | Proceedings of the 2021 24th International Conference on Mechatronics Technology (ICMT) | ||||||
| Publisher: | IEEE | ||||||
| ISBN: | 9781665424592 | ||||||
| Book Title: | 2021 24th International Conference on Mechatronics Technology (ICMT) | ||||||
| Official Date: | 1 February 2022 | ||||||
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| Page Range: | pp. 1-6 | ||||||
| DOI: | 10.1109/ICMT53429.2021.9687283 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Copyright Holders: | IEEE | ||||||
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| Conference Paper Type: | Paper | ||||||
| Title of Event: | 2021 24th International Conference on Mechatronics Technology (ICMT) | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Singapore | ||||||
| Date(s) of Event: | 18-22 Dec 2021 |
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