Towards Benchmarking of Functional Safety in the Automotive Industry
Paper i proceeding, 2013

Functional safety is becoming increasingly important in the automo- tive industry to deal with the growing reliance on the electrical and/or electronic (E/E) systems and the associated complexities. The introduction of ISO 26262, a new standard for functional safety in road vehicles, has made it even more important to adopt a systematic approach of evaluating functional safety. How- ever, standard assessment methods of benchmarking functional safety of automotive systems are not available as of today. This is where the BeSafe (Benchmarking of Functional Safety) project comes into the picture. BeSafe project aims to lay the foundation for benchmarking functional safety of auto- motive E/E systems. In this paper, we present a brief overview of the project along with the benchmark targets that we have identified as relevant for the automotive industry, assuming three abstraction layers (model, software, hard- ware). We then define and discuss a set of benchmark measures. Next, we pro- pose a benchmark framework encompassing fault/error models, methods and the required tool support. This paper primarily focuses on functional safety benchmarking from the Safety Element out of Context (SEooC) viewpoint. Fi- nally, we present some preliminary results and highlight potential future works.

Fault Tolerance

Safety Element out of Context (SEooC).


Fault Injection


Functional Safety


Mafijul Islam

Volvo Group

Behrooz Sangchoolie

Chalmers, Data- och informationsteknik, Datorteknik

Fatemeh Ayatolahi

Chalmers, Data- och informationsteknik, Datorteknik

Daniel Skarin

Chalmers, Data- och informationsteknik, Nätverk och system

Jonny Vinter

Chalmers, Data- och informationsteknik, Datorteknik

Fredrik Törner

Volvo Cars

Mattias Nyberg

Scania CV AB

Emilia Villani

Chalmers, Data- och informationsteknik, Datorteknik

Johan Haraldsson

Volvo Group

Patrik Isaksson

Volvo Group

Johan Karlsson

Chalmers, Data- och informationsteknik, Datorteknik

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 7869 111 - 125
978-364238788-3 (ISBN)



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