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

Safe AI Engineering Midterm Event at IAA TRANSPORTATION

On 16 September 2026, the Safe AI Engineering Midterm Event took place at IAA TRANSPORTATION in Hanover, bringing together researchers, engineers and industry experts to discuss one of the key challenges for future mobility: the integration of safe AI into real-world transportation systems.

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.

Facts & Figures

Project Budget

34,5 Mio. €

Consortium Lead

Dr. Torsten Stiehm

Luxoft GmbH

Dr.-Ing. Sven Hallerbach

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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