# Guidance on the Safety Assurance of Autonomous Systems in Complex Environments (SACE)

arXiv: https://arxiv.org/abs/2208.00853 · HTML: https://mlsanity.com/paper/2208.00853/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Aug 2022.

## Built on by (most cited first, 8 of 8)

- [SafeLLM: Domain-Specific Safety Monitoring for Large Language Models: A Case Study of Offshore Wind Maintenance](https://mlsanity.com/paper/2410.10852/) (2024)
- [ASTRID -- An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems](https://mlsanity.com/paper/2501.08208/) (2025)
- [Safety Analysis of Autonomous Railway Systems: An Introduction to the SACRED Methodology](https://mlsanity.com/paper/2403.12114/) (2024)
- [MATRIX: Multi-Agent simulaTion fRamework for safe Interactions and conteXtual clinical conversational evaluation](https://mlsanity.com/paper/2508.19163/) (2025)
- [Out-of-Distribution Detection for Safety Assurance of AI and Autonomous Systems](https://mlsanity.com/paper/2510.21254/) (2025)
- [Assessing Trustworthiness of Autonomous Systems](https://mlsanity.com/paper/2305.03411/) (2023)
- [AI Assurance in UK Defence: Challenges in Operationalising JSP 936](https://mlsanity.com/paper/2606.09414/) (2026)
- [A Local Agentic AI Framework to Generate Edge Case Scenarios for Safety Assurance](https://mlsanity.com/paper/2610.13479/) (2026)

## Abstract (arXiv)

Autonomous systems (AS) are systems that have the capability to take decisions free from direct human control. AS are increasingly being considered for adoption for applications where their behaviour may cause harm, such as when used for autonomous driving, medical applications or in domestic environments. For such applications, being able to ensure and demonstrate (assure) the safety of the operation of the AS is crucial for their adoption. This can be particularly challenging where AS operate in complex and changing real-world environments. Establishing justified confidence in the safety of AS requires the creation of a compelling safety case. This document introduces a methodology for the Safety Assurance of Autonomous Systems in Complex Environments (SACE). SACE comprises a set of safety case patterns and a process for (1) systematically integrating safety assurance into the development of the AS and (2) for generating the evidence base for explicitly justifying the acceptable safety of the AS.