The Audi Autonomous Driving Cup

The Audi Autonomous Driving Cup is an interdisciplinary competition focusing on students of computer science, electrical engineering and similar sciences. The students develop automated driving functionalities on miniature vehicles facing similar challenges as on full-size cars. The miniature vehicles as well as the basic driving functionalities are delivered by Audi, giving a perfect basis for developing higher level perception and planning algorithms.

The interdisciplinary character as well as the development of industry-related topics is the perfect reason to support this competition by the FZI. The idea of developing real­-world applications on small­-scale vehicles is highly integrated into several projects. Over the years, a supporting infrastructure has been built up including several small­-scale environment objects of different qualities and quantities and a full­-featured intuitive simulation for efficient prototype testing.

And the next big ideas are at the ready...


Team AlpaKa 2018

Team AlpaKa 2018 Team AlpaKa, supported by the FZI, is one of the ten teams participating in the fourth Audi Autonomous Driving Cup 2018. The students Simon Roesler, Maximilian Zipfl, Shuxiao Ding, Mark Timon Hüneberg und Yimeng Zhu are highly motivated to face the challenges of autonomous driving.

Team KADABRA 2017

Team KADABRA, supported by the FZI, was one of the ten teams that participated in the third Audi Autonomous Driving Cup 2017. The students Robin Andlauer, Kolja Esders, Nico Kuhn, Fabian Dürr and Kai Braun unfortunately could not defend the second place of the years before. Team KADABRA built up on the experiences of the teams KAtana and KACADU. The software architecture was altered from a monolith towards a modularized micro-architecture. An enhanced robust road perception was achieved by means of Fully Convolutional Neural Networks. The necessary training data was generated in simulations which allows for automated labelling. Furthermore, a new method to detect and track cars and pedestrians was implemented by incorporating the YOLO real-time object detection system.

Team KACADU 2016

Team KACADU, supported by the FZI, was one of the ten teams that participated in the second Audi Autonomous Driving Cup 2016. The students Vitali Kaiser, Jan­-Markus Gomer, Micha Pfeiffer, Peter Zimmer und David Zimmerer were able to defend the second place from 2015.

Team KACADU built up on the experiences of team KAtana. The modular road environment was enlarged by a few high quality modules and large flexible redefinable carpets. The idea of the robust hierarchical road layout perception was kept up and completely reimplemented in a more performant grid­-based solution. In a parallel lab course, students from KIT laid the basis for the miniature vehicle simulation.

Read more (in German)

Publication

Details about the robust environment perception were presented in a paper on Intelligent Transportation Systems from the 2016 IEEE International Conference on 1­4 November 2016.

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The source code is available for download at GitHub: https://github.com/fzi-forschungszentrum-informatik/aadc2016

Team KAtana 2015

Team KAtana, supported by the FZI, was one of the ten teams that participated in the first Audi Autonomous Driving Cup 2015. The students Raphael Frisch, Christoph Rist, Nilan Marktanner, Philipp Hertweck, Sascha Ibrahimpasic made it into the finals and reached the second place.

Team KAtana was the FZI's first team to participate in the cup. They faced several challenges and laid the basis for future teams. The first physical road modules were created and a first implementation of the robust hierarchical road layout perception was used in the cup. Furthermore, the necessity of a supporting simulation was identified.

Read more (in German)

The source code is available for download at GitHub: https://github.com/KAtana-Karlsruhe/AADC_2015_KAtana

Miniature Vehicle Simulation

For the Audi Autonomous Driving Cup, the FZI has developed a simulation based on the Gazebo robot simulation. It consists of

  • an intuitive world editor, including models for road tiles and traffic signs,
  • a physical and visual vehicle model of the miniature vehicles, including all actuators and sensors
  • logic models for elementary simulation of other traffic participants

Publication

Details about the simulation are presented in a paper at 2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR).


Contact

Dipl.-Math. techn. Florian Kuhnt

Research Scientist

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Career

Florian Kuhnt studierte bis 2012 Technomathematik am Karlsruher Institut für Technologie (KIT). Seine Schwerpunkte liegen in den Gebieten Kognitive Systeme und Robotik.

Seine Diplomarbeit mit dem Titel „Probabilistische Kollisionsprädiktion für Segway-Transporter“ führte er in der Abteilung Technisch Kognitive Systeme (TKS) am Forschungszentrum Informatik (FZI) durch.

Seit Juni 2012 ist er wissenschaftlicher Mitarbeiter in der Abteilung TKS. Er ist im Bereich der Hinderniserkennung und -bewertung, sowie der Situationsanalyse und -interpretation tätig.

Publications

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Contact

Phone: +49 721 9654-364
Fax: +49 721 9654-365
E-Mail: kuhnt@dont-want-spam.fzi.de

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M.Sc. Tobias Fleck

Wissenschaftlicher Mitarbeiter

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Career

Tobias Fleck studierte bis 2016 Informatik am Karlsruher Institut für Technologie (KIT). Während seines Masterstudiums beschäftigte er sich mit Kognitiven Systemen, insbesondere probabilistische Schätz- und Modellierungsmethoden bildeten seine Schwerpunkte.

Seine Masterarbeit "Trajectory Estimation and Prediction in the Context of Autonomous Driving" führte er in der Abteilung Technisch Kognitive Systeme (TKS) durch.

Seit Februar 2017 ist Tobias Fleck als wissenschaftlicher Mitarbeiter am Forschungszentrum Informatik (FZI) in der Abteilung TKS tätig.

Publications

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Contact

Phone: +49 721 9654-216
E-Mail: Tobias.Fleck@dont-want-spam.fzi.de

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