Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system

Markus Borg, Jens Henriksson, Kasper Socha, Olof Lennartsson, Elias Sonnsjö Lönegren, Thanh Bui, Piotr Tomaszewski, Sankar Raman Sathyamoorthy, Sebastian Brink, Mahshid Helali Moghadam

Research output: Contribution to journalArticlepeer-review

Abstract

Integration of machine learning (ML) components in critical applications introduces novel challenges for software certification and verification. New safety standards and technical guidelines are under development to support the safety of ML-based systems, e.g., ISO 21448 SOTIF for the automotive domain and the Assurance of Machine Learning for use in Autonomous Systems (AMLAS) framework. SOTIF and AMLAS provide high-level guidance but the details must be chiseled out for each specific case. We initiated a research project with the goal to demonstrate a complete safety case for an ML component in an open automotive system. This paper reports results from an industry-academia collaboration on safety assurance of SMIRK, an ML-based pedestrian automatic emergency braking demonstrator running in an industry-grade simulator. We demonstrate an application of AMLAS on SMIRK for a minimalistic operational design domain, i.e., we share a complete safety case for its integrated ML-based component. Finally, we report lessons learned and provide both SMIRK and the safety case under an open-source license for the research community to reuse.

Original languageEnglish
Pages (from-to)335-403
JournalSoftware Quality Journal
Volume31
Issue number2
Early online date2023
DOIs
Publication statusPublished - 2023

Subject classification (UKÄ)

  • Software Engineering

Free keywords

  • Automotive demonstrator
  • Machine learning safety
  • Safety case
  • Safety standards

Fingerprint

Dive into the research topics of 'Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system'. Together they form a unique fingerprint.

Cite this