SAFE-CAR-ML: Semantic Change Description for Vehicle Development with ML-Based Automatic Classification

SCALE, in collaboration with the Fraunhofer Institute SCAI and industry partners Audi, VW, and Porsche, is working on SAFECAR-ML – a research project aimed at automating documentation processes in vehicle development. The project seeks to enhance efficiency and transparency in the product development process through the use of machine learning (ML).

The focus lies on developing innovative methods to simplify the documentation of changes to virtual vehicle models, particularly in the context of crash tests. These tests, predominantly conducted virtually, require extensive documentation of simulated changes. SAFECAR-ML leverages AI-based methods to semantically analyze free-text descriptions, harmonize the extracted data, and derive actionable recommendations.

The Fraunhofer Institute SCAI contributes its expertise in algorithm development and machine learning to the project, supporting efficient data processing and modeling.

The project is funded by the German Federal Ministry of Education and Research (BMBF) under the “KI4KMU” initiative (Research, Development, and Use of AI Methods in SMEs).

The results of SAFECAR-ML are not only valuable for the automotive industry but are also transferable to other sectors. With this, SCALE is making a significant contribution to the digital transformation of product development.