The SOTIF Meta-Algorithm: Quantitative Analyses of the Safety of Autonomous Behaviors

This paper introduces a meta-algorithm for achieving Safety Of The Intended Functionality (SOTIF) in complex systems by integrating quantitative Fault Tree Analysis (qFTA), structured generation of UL 4600 Safety Performance Indicators (SPIs), and statistical hypothesis testing of SPIs in simulation and reality. The meta-algorithm can be used for specific autonomy stacks and Operational Design Domains (ODDs) to make practical the risk analyses in the automotive standard ISO 21448. By using the SOTIF Meta Algorithm, operators will make more informed deployment decisions for autonomous systems.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/issrew63542.2024.00077
Citations
2
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.69
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article

The SOTIF Meta-Algorithm: Quantitative Analyses of the Safety of Autonomous Behaviors

Neil Carlson, Carmen Cârlan, Michael Wagner, Chris Dwyer et al.
2 citations
EEG and Brain-Computer Interfaces
0.69
article

The SOTIF Meta-Algorithm: Quantitative Analyses of the Safety of Autonomous Behaviors

Neil Carlson, Carmen Cârlan, Michael Wagner, Chris Dwyer, Manoja Hirannaiah
article en
2 citations

Abstract

This paper introduces a meta-algorithm for achieving Safety Of The Intended Functionality (SOTIF) in complex systems by integrating quantitative Fault Tree Analysis (qFTA), structured generation of UL 4600 Safety Performance Indicators (SPIs), and statistical hypothesis testing of SPIs in simulation and reality. The meta-algorithm can be used for specific autonomy stacks and Operational Design Domains (ODDs) to make practical the risk analyses in the automotive standard ISO 21448. By using the SOTIF Meta Algorithm, operators will make more informed deployment decisions for autonomous systems.

Edge Case Research (United States) (US)
Openalex Percentile: Top 29%
EEG and Brain-Computer Interfaces
0.69
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The SOTIF Meta-Algorithm: Quantitative Analyses of the Safety of Autonomous Behaviors — Neil Carlson, Carmen Cârlan, et al. · (2024) | TGRS Research Map | TGRS