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Automotive safety a...
Automotive safety and machine learning : Initial results from a study on how to adapt the ISO 26262 safety standard
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- Henriksson, Jens, 1991 (author)
- Semcon Sweden AB, Gothenburg, Sweden,Chalmers tekniska högskola,Chalmers University of Technology
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- Borg, Markus (author)
- RISE,SICS,RISE SICS, Lund, Sweden,RISE Research Institutes of Sweden
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- Englund, Cristofer, 1977- (author)
- RISE,Viktoria,RISE Viktoria, Gothenburg, Sweden,Cooperative Systems,RISE Research Institutes of Sweden
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(creator_code:org_t)
- 2018-05-28
- 2018
- English.
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In: 2018 IEEE/ACM 1st International Workshop on Software Engineering for AI in Autonomous Systems (SEFAIAS). - New York, NY : ACM Publications. - 9781450357395 - 9781538662618 ; May 2018, s. 47-49
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Abstract
Subject headings
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- Machine learning (ML) applications generate a continuous stream of success stories from various domains. ML enables many novel applications, also in safety-critical contexts. However, the functional safety standards such as ISO 26262 did not evolve to cover ML. We conduct an exploratory study on which parts of ISO 26262 represent the most critical gaps between safety engineering and ML development. While this paper only reports the first steps toward a larger research endeavor, we report three adaptations that are critically needed to allow ISO 26262 compliant engineering, and related suggestions on how to evolve the standard. © 2018 ACM.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Inbäddad systemteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Embedded Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Software Engineering (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Keyword
- Computing methodologies
- Machine learning
- Software and its engineering
- Software safety
Publication and Content Type
- ref (subject category)
- kon (subject category)
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