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pro vyhledávání: '"Sivencrona, Hȧkan"'
Changes and updates in the requirement artifacts, which can be frequent in the automotive domain, are a challenge for SafetyOps. Large Language Models (LLMs), with their impressive natural language understanding and generating capabilities, can play
Externí odkaz:
http://arxiv.org/abs/2403.16289
DevOps is a necessity in many industries, including the development of Autonomous Vehicles. In those settings, there are iterative activities that reduce the speed of SafetyOps cycles. One of these activities is "Hazard Analysis & Risk Assessment" (H
Externí odkaz:
http://arxiv.org/abs/2403.09565
Autor:
Habibullah, Khan Mohammad, Heyn, Hans-Martin, Gay, Gregory, Horkoff, Jennifer, Knauss, Eric, Borg, Markus, Knauss, Alessia, Sivencrona, Håkan, Li, Polly Jing
Background: Driving automation systems (DAS), including autonomous driving and advanced driver assistance, are an important safety-critical domain. DAS often incorporate perceptions systems that use machine learning (ML) to analyze the vehicle enviro
Externí odkaz:
http://arxiv.org/abs/2302.12155
Akademický článek
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Publikováno v:
In Safety Science November 2017 99 Part B:166-177
Publikováno v:
SAE Transactions, 2007 Jan 01. 116, 573-578.
Externí odkaz:
https://www.jstor.org/stable/44719927
Publikováno v:
SAE Transactions, 2007 Jan 01. 116, 422-429.
Externí odkaz:
https://www.jstor.org/stable/44719909
Publikováno v:
SAE Transactions, 2003 Jan 01. 112, 62-67.
Externí odkaz:
https://www.jstor.org/stable/44699652
Autor:
Sivencrona, Håkan, Johansson, Lars-Åke
Publikováno v:
SAE Transactions, 2001 Jan 01. 110, 670-674.
Externí odkaz:
https://www.jstor.org/stable/44718387