AI-based extraction of requirements from regulations for automotive engineering

Abstract

Automotive engineering requires compliance with regulations for certification. In specifications, regulations are referenced, which need to be analyzed manually to elicit requirements. This process is time-consuming and leads to high costs. The aim of this research is to evaluate artificial intelligence (AI) models in terms of extracting requirements automatically from regulations. Relevant AI models are identified in a systematic literature analysis and evaluated using success criteria. The most promising AI models are implemented in a pipeline for requirements extraction. The performance of these AI models is assessed in a comparative study using automotive regulations. The results show which AI models are best suited for this task.

Introducing a multipliable BOM-based automatic definition of information retrieval in plant engineering

“…Existing literature approaches, such as Gräßler et al (2023), Luttmer et al (2023) as well as our own research (Layer et al, 2023b) demonstrate the possibilities of automating and streamlining this process.…”