Research Projects


Artificial intelligence for selective real-time recording of scenario and maneuver data during the testing of highly automated vehicles

Start: 01/2021

End: 12/2023

To prove the safe function of highly automated vehicles, firmly defined scenario catalogs are used for maneuver-related evidence according to the current state of the art, as well as real-time data comprising several million driving kilometers for statistical verification.

To develop new vehicles with a 4/5 automation level, achieving a selective acquisition of relevant and critical driving situations, significant environmental data as well as raw data of the vehicle sensor system while driving are indispensable. This data is needed to validate, improve and reproduce the decisions made by artificial intelligence (AI), with the aim of thus achieving the necessary test coverage for future functionalities.

Within the KIsSME project, AI-based algorithms will be applied to enable on-board systems to recognize relevant and critical scenarios in real time and to selectively acquire raw data and scenario descriptions for this purpose. The AI-based algorithms will enable an inherent learning capability that continuously improves the recognition of critical situations and the associated relevant data to increase the information density of the data used for testing when developing level 4/5 automated systems, while simultaneously significantly reducing the associated data volume required as well as the effort needed to ensure data protection.


Marc Zofka

Department Manager
Division: Intelligent Systems and Production Engineering

Research focus

Applied Artificial Intelligence

In this research focus, the FZI prioritizes the topics of Artificial Intelligence (AI) as well as human and AI engineering. In addition, the FZI deals with questions on dedicated AI hardware and predictive AI.

Intelligent Transportation Systems and Logistics

Intelligent solutions for the transportation of people and goods represent a focus topic of FZI’s application research. Particular attention is paid to public transport, the application of artificial intelligence, the further development of driving functions and their safeguarding, and open source & open data.

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