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Systems Engineering and Architecting for Intelligent Autonomous Systems
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics. (Embedded control systems)ORCID iD: 0000-0002-8629-0402
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics. (Embedded control systems)ORCID iD: 0000-0002-4300-885X
2017 (English)In: Automated Driving: Safer and More Efficient Future Driving / [ed] Watzenig, Daniel, Horn, Martin, Springer, 2017, 313-351 p.Chapter in book (Refereed)
Abstract [en]

This chapter provides an overview of architecture and systems engineeringfor autonomous driving system, through a set of complementaryperspectives. For practitioners, a short term perspective uses the state of theart to dene a three layered functional architecture for autonomous driving,consisting of a vehicle platform, a cognitive driving intelligence, and o-board supervisory and monitoring services. The architecture is placed withina broader context of model based systems engineering (MBSE), for which wedene four classes of models: Concept of Operations, Logical Architecture,Application Software Components, and Platform Components. These classesaid an immediate or subsequent MBSE methodology for concrete projects.Also for concrete projects, we propose an implementation setup and technologiesthat combine simulation and implementation for rapid testing of autonomousdriving functionality in physical and virtual environments. Futureevolution of autonomous driving systems is explored with a long term perspectivelooking at stronger concepts of autonomy like machine consciousnessand self-awareness. Contrasting these concepts with current engineering practicesshows that scaling to more complex systems may require incorporatingelements of so-called constructivist architectures. The impact of autonomy onsystems engineering is expected to be mainly around testing and verication,while implementations shall continue experiencing an in ux of technologiesfrom non-automotive domains.

Place, publisher, year, edition, pages
Springer, 2017. 313-351 p.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-198054DOI: 10.1007/978-3-319-31895-0_13ISBN: 978-3-319-31895-0 (print)OAI: oai:DiVA.org:kth-198054DiVA: diva2:1055137
Note

QC 20161212

Available from: 2016-12-11 Created: 2016-12-11 Last updated: 2016-12-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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More styles
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Output format
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