City2.e 2.0

Smart Parking Solutions

City2.e 2.0 is supposed to contribute to the turnaround in energy and traffic policy. The main objective is a practical demonstration of an intelligent parking space monitoring and control - including electrical car charging facilities. Main parts are a prototype of a holistic parking detection, a practical real-world test, and a system architecture for monitoring and control of detected parking spaces. The developed solution is to be integrated in the Berlin traffic information system. 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.

Duration: 01.01.2014 till 31.08.2016
Donee: German Research Center for Artificial Intelligence GmbH
Sponsor: Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection
Grant number: Supported by the Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (grant no. 16EM2051-5).
Partner: Siemens AG, Senatsverwaltung für Stadtentwicklung und Umwelt Berlin (SenStadtUm Berlin), Verkehrsmanagementzentrale Berlin (VMZ), Institut für Klimaschutz, Energie und Mobilität (IKEM)
Application Field: Electric Mobility



Concept of a Data Thread Based Parking Space Occupancy Prediction in a Berlin Pilot Region
Tim Tiedemann, Thomas Vögele, Mario Michael Krell, Jan Hendrik Metzen, Frank Kirchner
In Papers from the 2015 AAAI Workshop, (WAIT-2015), 25.1.-26.1.2015, Austin, AAAI Press, Jan/2015.
Wissen, wann ein Parkplatz frei wird
Tim Tiedemann, Thomas Vögele
In Internationales Verkehrswesen, DVV Media Group GmbH, volume 67, pages 84-85, 2015.

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