Safety Case Templates for Autonomous Systems
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Abstract (arXiv)
This report documents safety assurance argument templates to support the deployment and operation of autonomous systems that include machine learning (ML) components. The document presents example safety argument templates covering: the development of safety requirements, hazard analysis, a safety monitor architecture for an autonomous system including at least one ML element, a component with ML and the adaptation and change of the system over time. The report also presents generic templates for argument defeaters and evidence confidence that can be used to strengthen, review, and adapt the templates as necessary. This report is made available to get feedback on the approach and on the templates. This work was sponsored by the UK Dstl under the R-cloud framework.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 13 of its 34 references that are in the map. First posted on arXiv 29 Jan 2021.
Builds on
13 of 34 references.
References · 13
- 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
- 2016YOLO9000: Better, Faster, Strongercited by 1,429
- 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,361
- 2018Learning Confidence for Out-of-Distribution Detection in Neural Networkscited by 245
- 2017On a Formal Model of Safe and Scalable Self-driving Carscited by 129
- 2015UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Trackingcited by 98
- 2019Requirements Engineering for Machine Learning: Perspectives from Data Scientistscited by 49
- 2020A Safety Framework for Critical Systems Utilising Deep Neural Networkscited by 19
- 2019Assessing the Safety and Reliability of Autonomous Vehicles from Road Testingcited by 15
- 2018AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detectioncited by 14
- 2018Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262cited by 13
- 2019Traffic Light Recognition Using Deep Learning and Prior Maps for Autonomous Carscited by 8
1 more
- 2020Assurance 2.0: A Manifestocited by 6
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Citing papers per year: 2021: 2; 2022: 0; 2023: 0; 2024: 1.
3 papers.