Welcome Your New AI Teammate: On Safety Analysis by Leashing Large Language Models
Paper i proceeding, 2024

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.

Safety

Prompt Engineering

LLM

Autonomous Vehicles

Hazard Analysis Risk Assessment

DevOps

ChatGPT

Large Language Model

Författare

Ali Nouri

Software Engineering 1

Beatriz Cabrero-Daniel

Göteborgs universitet

Fredrik Torner

Volvo Cars

Hakan Sivencrona

Zenseact AB

Christian Berger

Göteborgs universitet

PROCEEDINGS 2024 IEEE/ACM 3RD INTERNATIONAL CONFERENCE ON AI ENGINEERING-SOFTWARE ENGINEERING FOR AI, CAIN 2024

172-177
979-8-4007-0591-5 (ISBN)

IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI (CAIN)
Lisbon, Portugal,

Ämneskategorier

Programvaruteknik

Datorsystem

DOI

10.1145/3644815.3644953

Mer information

Senast uppdaterat

2024-08-15