Research Projects


Needs, wants and behaviour of „Drivers“ and automated vehicles users today and into the future

Start: 05/2019

End: 10/2022

Vehicles operate in an increasingly networked, cooperative, and automated manner. As a result, human-machine interaction (HMI) is becoming increasingly complex in an environment characterized by information and data exchange and increasing automation, imposing new demands on road users.

The aim of the Drive2theFuture project is to prepare drivers and travelers for networked, cooperative, and automated means of transportation, thereby increasing their acceptance. At the same time, the project helps technology manufacturers understand and meet the needs and desires of people. Drive2theFuture tests different use cases, HMI concepts and training and compares them for different transportation carriers as well as user types. In this way, a sustainable market introduction of the application can be simulated, regulated, and optimized.

Within this EU project, the FZI is researching machine learning methods for the interaction between automated and non-automated vehicles, pedestrians and cyclists. For this purpose, the Test Area Autonomous Driving Baden-Württemberg (TAF BW) with its infrastructure sensors –along with a virtual copy of it – will be used to study the interactions in a virtual reality environment.


Marc Zofka

Department Manager
Division: Intelligent Systems and Production Engineering

Research focus

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.

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.

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