Welcome Your New AI Teammate: On Safety Analysis by Leashing Large Language Models

DevOps is a necessity in many industries, including the development of Autonomous Vehicles. In those settings, there are iterative activities that reduce the speed of SafetyOps cycles. One of these activities is "Hazard Analysis & Risk Assessment" (HARA), which is an essential step to...

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Bibliographic Details
Published in:arXiv.org 2024-03
Main Authors: Nouri, Ali, Cabrero-Daniel, Beatriz, Törner, Fredrik, Sivencrona, Hȧkan, Berger, Christian
Format: Article
Language:English
Subjects:
Hazard assessment
Iterative methods
Large language models
Requirements specifications
Risk analysis
Risk assessment
Safety
Online Access:Get full text
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Summary:DevOps is a necessity in many industries, including the development of Autonomous Vehicles. In those settings, there are iterative activities that reduce the speed of SafetyOps cycles. One of these activities is "Hazard Analysis & Risk Assessment" (HARA), which is an essential step to start the safety requirements specification. As a potential approach to increase the speed of this step in SafetyOps, we have delved into the capabilities of Large Language Models (LLMs). Our objective is to systematically assess their potential for application in the field of safety engineering. To that end, we propose a framework to support a higher degree of automation of HARA with LLMs. Despite our endeavors to automate as much of the process as possible, expert review remains crucial to ensure the validity and correctness of the analysis results, with necessary modifications made accordingly.
ISSN:2331-8422
DOI:10.48550/arxiv.2403.09565