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Automatic Decomposition and Allocation of Safety Integrity Levels Using a Penalty-Based Genetic Algorithm

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Recent Trends in Applied Artificial Intelligence (IEA/AIE 2013)

Abstract

Automotive Safety Integrity Levels (ASILs) are used in the new automotive functional safety standard, ISO 26262, as a key part of managing safety requirements throughout a top-down design process. The ASIL decomposition concept, outlined in the standard, allows the safety requirements to be divided between multiple components of the system whilst still meeting the ASILs initially allocated to system-level hazards. Existing exhaustive automatic decomposition techniques drastically reduce the effort of performing such tasks manually. However, the combinatorial nature of the problem leaves such exhaustive techniques with a scalability issue. To overcome this problem, we have developed a new technique that uses a penalty-based genetic algorithm to efficiently explore the search space and identify optimum assignments of ASILs to the system components. The technique has been applied to a hybrid braking system to evaluate its effectiveness.

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Parker, D., Walker, M., Azevedo, L.S., Papadopoulos, Y., Araújo, R.E. (2013). Automatic Decomposition and Allocation of Safety Integrity Levels Using a Penalty-Based Genetic Algorithm. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_46

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  • DOI: https://doi.org/10.1007/978-3-642-38577-3_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38576-6

  • Online ISBN: 978-3-642-38577-3

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