NDLI: Provisioning of predictable embedded software in the vehicle industry: the Rubus approach

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Provisioning of predictable embedded software in the vehicle industry: the Rubus approach

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Provisioning of predictable embedded software in the vehicle industry: the Rubus approach

Content Provider	ACM Digital Library
Author	Lawson, Harold "Bud" Mubeen, Saad Lundbäck, Kurt-Lennart Gålnander, Mattias Lundbäck, John
Abstract	Providing computer-based services for vehicular systems has evolved to the point where majority of functions are realised by software. However, the need to provide safety in critical functions such as braking and engine control requires an approach that can guarantee reliable operation of the functions. At the same time, there are a variety of vehicle functions that are less critical. The main challenge for the vehicle manufacturers is to provide both types of functions in an economic and reliable manner. To meet this challenge, this paper considers the Rubus tool chain for model- and component-based development of vehicle software and a well-proven (in the industrial use for over twenty years) and certified (according to ISO 26262) real-time operating system for its execution. The paper provides an overview of the Rubus approach and driving concepts as well as the research results that are used in providing its tool chain. Moreover, the paper presents a success story of a unique academic-industrial collaboration in the vehicle domain that has resulted in sustained development of the tool chain. The collaborators form a clear value chain from academia, through tool developer, to the end users of the technology. The paper also highlights the perspectives of the collaborators and discusses the challenges faced, experiences gained and lessons learned from several technology transfer projects.
Starting Page	3
Ending Page	9
Page Count	7
File Format	PDF
ISBN	9781538627976
DOI	10.1109/SER-IP.2017..1
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-05-20
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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