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dc.contributor.authorKugele, Stefan
dc.contributor.authorCebotari, Vadim
dc.contributor.authorGleirscher, Mario
dc.contributor.authorHashemi, Morteza
dc.contributor.authorSegler, Christoph
dc.contributor.authorShafaei, Sina
dc.contributor.authorVögel, Hans-Jörg
dc.contributor.authorBauer, Fridolin
dc.contributor.authorKnoll, Alois
dc.contributor.authorMarmsoler, Diego
dc.contributor.authorMichel, Hans-Ulrich
dc.contributor.editorEibl, Maximilian
dc.contributor.editorGaedke, Martin
dc.date.accessioned2017-08-28T23:47:05Z
dc.date.available2017-08-28T23:47:05Z
dc.date.issued2017
dc.identifier.isbn978-3-88579-669-5
dc.identifier.issn1617-5468
dc.description.abstractDuring the last decades, the functional power and complexity of automotive E/E architectures grew radically and is going to grow further. We identified two key factors namely autonomy and intelligence. Both pose research challenges for the next generation E/E architecture. We aim to tackle the design challenges with methods and technologies. We propose in this project statement to use a service-oriented architecture on top of an in-vehicle communication network based on time-sensitive networking. Moreover, a rigor risk analysis and mitigation approach enables synthesis of a safety controller. A learning architecture facilitates a shift towards user centralization by proactively adapting functions according to user profiles. In addition, further functions might need to be learned at run-time.en
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2017
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-275
dc.subjectAutomotive
dc.subjectsafety assurance
dc.subjectservice-oriented architectures
dc.subjectcommunication
dc.subjecttimesensitive network
dc.subjectdeep learning
dc.subjectmachine learning
dc.subjectartificial intelligence
dc.titleResearch Challenges for a Future-Proof E/E Architecture - A Project Statementen
mci.reference.pages1463-1474
mci.conference.sessiontitleASE – 15. Workshop Automotive Software Engineering
mci.conference.locationChemnitz
mci.conference.date25.-29. September 2017
dc.identifier.doi10.18420/in2017_146


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