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

First overall consortium meeting of the Safe AI Engineering project at Bosch in Renningen

From September 23 to 24, 2025, the first major project meeting of the Safe AI Engineering Consortium took place at the Bosch Research Campus in Renningen. More than 80 experts from the consortium came together to present the results of the various subprojects to date, exchange ideas on the status of Use Case 1, discuss the project, and plan the next steps.
Gruppenbild Konsortium Safe AI Engineering

Kick-off of the new Safe AI Engineering research project in Böblingen

Joint kick-off for the Safe AI Engineering research project: All 24 partners met at Luxoft in Böblingen on March 20 and 21, 2025, to plan the next steps together and ensure a successful project launch.

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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