Autonomous vehicles must be able to perceive their environment and appropriately react to it. Error-free and reliable environment recognition that can correctly identify and classify all relevant road users is a basic prerequisite for implementing autonomous driving functions. This is especially true for the perception of the environment in complex urban traffic situations where methods of artificial intelligence (AI) are increasingly being used. Such AI function modules based on machine learning are thus becoming a key technology.

One of the greatest challenges for integrating these technologies into highly automated vehicles is ensuring the customary functional safety of previous systems without the driver having to take over the driving task in an emergency. Existing and established safeguarding processes cannot easily be transferred to machine learning methods.

In order to solve this challenge, the KI Absicherung project is working on establishing a stringent and provable safety argumentation for the first time with which AI-based function modules (AI modules) can be secured and validated for highly automated driving.