WG 5: Mobility and Intelligent Transport Systems
Transport modes on land, in water and in the air are reaching higher and higher degrees of automation. Vehicles, roadway and rail systems are well networked. When used intelligently, cars equipped with AI-based assistance systems can increase traffic safety, optimise traffic flows and reduce pollutant emissions. Automated trains can run on rail routes more efficiently. Self-learning systems make the entire mobility system more resilient. But new challenges have to be met in this new digital world, such as the configuration of a proper man-machine interface and the safety use of AI-applications.
Topics and Organisation of the Working Group
The working group compiles design options for intelligent mobility systems. This includes technological solutions and infrastructures, security and safety-related questions, as well as legal requirements.
Members of the Working Group
- Univ.-Prof. Dr.-Ing. Albert Albers
- Karlsruhe Institute of Technology (KIT) - IPEK
- Maria Anhalt
- Continental AG
- Claus Bahlmann
- Siemens Mobility GmbH
- Prof. Dr.-Ing. Fabian Behrendt
- Fraunhofer Institute
- Dr. Astrid Elbe
- Intel Germany
- Prof. Dr.-Ing. Stefanos Fasoulas
- University of Stuttgart
- Dr. Tim Gutheit
- Infineon Technologies AG
- Prof. Dr.-Ing. Axel Hahn
- OFFIS - Institute for Information Technology
- Dr. -Ing. Sören Kerner
- Fraunhofer Institute for Material Flow and Logistics
- Hans Kolß
- FlixMobility GmbH
- Igor Neiva Camargo
- Continental Automotive GmbH
- Dr.-Ing. Ilja Radusch
- Fraunhofer FOKUS / Daimler Center for Automotive IT Innovations
- Dr. Felix Rudolf
- PSI AG
- Dr. Peter Schlicht
- Volkswagen AG
- Dr. Anatoly Sherman
- SICK AG
- Prof. Dr.-Ing. Philipp Slusallek
- German Research Center for Artificial Intelligence (DFKI)
- Prof. Dr.-Ing. J. Marius Zöllner
- Karlsruhe Institute of Technology (KIT)
We have received written consent from the listed persons for the publication of their data in accordance with the DSGVO. This list of members is an excerpt and will be completed continuously.
Key Questions for the Working Group
- How does our mobility structure change when it comes to self-learning systems?
- Which characteristics are necessary to have the most beneficial usage for individual users and the society as a whole?
- How do infrastructure and systems structures within the mobility sector have to be further developed to adequately integrate self-learning systems?
- What is the most optimal relation between individual and local intelligence towards central control?
- How can self-learning systems be secured and tested in the mobility sector?
- Which knowledge representation is necessary (e.g. for knowledge exchange or control)?
Results and Contributions of the Working Group
- On the Way to Intelligent Mobility
- Year of publication: 2019
- A safer, more flexible and more economical way to get from A to B by road, rail or water – Artificial Intelligence (AI) can play an important part in achieving this vision. Indeed, AI-based assistance systems help make transport systems more intelligent and futureproof. This is made possible by the interplay of sensors, cameras and intelligent infrastructures and platforms that capture, manage and share traffic data. Increasingly sophisticated Machine Learning (ML) processes are being used to process captured data and derive operations to be executed either by people or by the systems themselves.
- Contact: Birgit Obermeier / Linda Treugut
Coordination of the Working Group at the Managing Office: Rebecca Ebner