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A Context-Aware, Confidence-Disclosing and Fail-Operational Dynamic Risk Assessment Architecture

: Feth, Patrik; Adler, Rasmus; Schneider, Daniel

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Erstellt am: 8.3.2019

Institute of Electrical and Electronics Engineers -IEEE-:
14th European Dependable Computing Conference, EDCC 2018 : Iaşi, Romania, 10-14 September 2018
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-8060-5
ISBN: 978-1-5386-8061-2
European Dependable Computing Conference (EDCC) <14, 2018, Iasi>
European Commission EC
H2020-ECSEL-2017-2 - RIA; 783119; SECREDAS
Cyber Security for Cross Domain Reliable Dependable Automated Systems
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IESE ()
risk management; vehicle dynamic; measurement; safety; computer architecture; resilience

Future automotive systems will be highly automated and they will cooperate to optimize important system qualities and performance. Established safety assurance approaches and standards have been designed with manually controlled stand-alone systems in mind and are thus not fit to ensure safety of this next generation of systems. We argue that, given frequent dynamic changes and unknown contexts, systems need to be enabled to dynamically assess and manage their risks. In doing so, systems become resilient from a safety perspective, i.e. they are able to maintain a state of acceptable risk even when facing changes. This work presents a Dynamic Risk Assessment architecture that implements the concepts of context-awareness, confidence-disclosure and fail-operational. In particular, we demonstrate the utilization of these concepts for the calculation of automotive collision risk metrics, which are at the heart of our architecture.