AI engineering as an enabler for a well-founded
safety argumentation throughout the entire
life cycle of an AI function.

AI engineering as an enabler for a well-founded safety argumentation throughout the entire life cycle of an AI function.

For greater safety in automated driving

The Safe AI Engineering research project is an important step towards a generally accepted and practical safety certification for AI functions that can be used for homologation and is therefore approval-relevant.

The aim is to develop a holistic methodology for validating safety-critical AI functions in automated driving – from planning, development, testing, application, and monitoring to continuous improvement. The research project focuses on increasing safety and better integration of AI features.

Safety Rope

As with a safety rope, a reliable safety argument is characterized by the consistent interweaving of various aspects. These aspects – represented by the sub-aspects of the project – are woven together into a robust structure through a process known as orchestration, which, similar to a braiding machine, twists the threads into a safe rope.

In this way, Safe AI Engineering creates the basis for an AI engineering method that forms the foundation for a generally accepted and practical proof of safety to establish safety-critical AI-System into the market.

For greater safety in automated driving

The Safe AI Engineering research project is an important step towards a generally accepted and practical safety certification for AI functions that can be used for homologation and is therefore approval-relevant.

The aim is to develop a holistic methodology for validating safety-critical AI functions in automated driving – from planning, development, testing, application, and monitoring to continuous improvement. The research project focuses on increasing safety and better integration of AI features.

Safety Rope

As with a safety rope, a reliable safety argument is characterized by the consistent interweaving of various aspects. These aspects – represented by the sub-aspects of the project – are woven together into a robust structure through a process known as orchestration, which, similar to a braiding machine, twists the threads into a secure rope.

In this way, Safe AI Engineering creates the basis for an AI engineering method that forms the foundation for a generally accepted, practical verification of safety-critical AI in the market.

Latest news about the project

Use Case 1 Demonstration in Bietigheim-Bissingen

At the end of November, the Safe AI Engineering project reached an important milestone: the demonstration of Use Case 1 at the AVL Tech Center in Bietigheim-Bissingen. With a mix of exciting presentations, simulations, and demonstrations, the initial results were presented, the work on safety argumentation was introduced, insights and problems were shared and their solutions discussed.

Safe AI Engineering at the AVF Conference in Berlin

On December 2-3, 2025 more than 250 experts from academia, industry, and politics gathered at the Harnack House in Berlin for the conference Research and Technology for Autonomous Driving. The project was presented at the networking event for projects initiated and developed as part of the VDA lead Initiative on autonomous and connected driving and which are funded by the Federal Ministry for Economic Affairs and Energy.

Facts & Figures

Project Budget

34,5 Mio. €

Consortium Lead

Dr. Ulrich Wurstbauer

Luxoft GmbH

Prof. Dr. Frank Köster

DLR

Consortium

23 Partners

OEMs, suppliers, technology providers, research institutions, external partners

Funding

17,2 Mio. €

Duration

36 Months

March 2025 – February 2028

Consortium

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