City2.e 2.0

City2.e 2.0

  • Duration:

City2.e 2.0 is supposed to contribute to the turnaround in energy and traffic policy. The project's main objective is a practical demonstration of an intelligent parking space monitoring and control -- including electrical car charging facilities. One first part is the development of a prototype of a holistic parking detection which is followed by a practical real-world test. Another part is the development of a system architecture for a monitoring and control of detected parking spaces. The developed solution is supposed to be integrated in the Berlin traffic information system for demonstration purposes.

The DFKI develops an adaptive prediction solution using machine learning methods to give estimations of future parking area occupation. Thereby, an improvement of planning, routing, and usage of parking spaces and charging stations could be realized.


Siemens AG (Gesamtprojektkoordination), Senatsverwaltung für Stadtentwicklung und Umwelt (Berlin), VMZ Berlin Betreibergesellschaft mbH, Institut für Klimaschutz, Energie und Mobilität - Recht, Ökonomie und Politik e.V. (IKEM)




Roadside parking is a challenge for an automatic occupancy detection but also for traffic management, planning, and predictability.

Publications about the project

Tim Tiedemann; Thomas Vögele; Mario Michael Krell; Jan Hendrik Metzen; Frank Kirchner

In: Papers from the 2015 AAAI Workshop. Workshop on AI for Transportation (WAIT-2015), January 25-26, Austin, USA, AAAI Press, 1/2015.

To the publication

Tim Tiedemann; Thomas Vögele

In: Internationales Verkehrswesen, Vol. 67, Pages 84-85, DVV Media Group GmbH, 2015.

To the publication

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz