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Daniel Watzenig

TU Graz and Virtual Vehicle Research Center

University Professor and Head of Department

 

Ein Bild, das Mann, Person, Schlips, Wand enthält.

Automatisch generierte Beschreibung

 

 

Daniel Watzenig was born in Austria. He received his Master’s degree in electrical engineering and the doctoral degree in technical science from Graz University of Technology, Graz, Austria, in 2002 and 2006, respectively. In 2009 he received the venia docendi (habilitation) for Electrical Measurement and Signal Processing.

Since 2017 he is a Full Professor of Automated Driving at the Institute of Automation and Control, Graz University of Technology, Austria.

In addition, he is Divisional Director and Scientific Head of the Automotive Electronics and Software Department of the Virtual Vehicle Research Center in Graz. Since 2015, he is Vice President of the ARTEMIS Industry Association (European Research Association on Embedded Control Systems).

His research interests focus on sense & control of automated vehicles, signal processing, sensor fusion, uncertainty estimation and quantification, robust optimization, non-invasive measurement techniques, and sampling methods. In 2005 he was a visiting researcher at the University of Auckland, New Zealand, working on multi-sensor arrays and statistical signal processing. In 2011 he was visiting researcher and guest lecturer at the Federal University of Rio de Janeiro. He is IEEE Senior Member of the IEEE Control Systems, Signal Processing and Instrumentation & Measurement Societies.

He is author or co-author of over 170 peer-reviewed papers, book chapters, patents, and articles. In 2016, he published the book “Automated Driving - safer and more efficient future driving” describing the state-of-the-art of this emerging technology[1]. He is the Austrian representative (appointed by the Austrian Federal Ministry BMVIT) of Electrified, Connected, and Automated Vehicles within the International Energy Agency (IEA). Since 2016 he is the Chair of the Task Force on “Methods and Tools for Virtual Development and Validation” of the European Automotive Research Partners Association (EARPA). He is member of the editorial board of the Journal Inverse Problems in Science and Engineering and Editor-in-Chief of the SAE Int. Journal on Connected and Automated Vehicles (SAE JCAV).

 

Kurzbeschreibung der Keynote

The motivation for implementing the next generation vehicles and smart mobility is versatile and should consider environmental, safety, social, and economic aspects. Automated driving offers an excellent solution to meet the main challenges in road traffic due to its capability to increase traffic safety, improve traffic efficiency and comfort, and significantly reduce emissions. Over the last two decades, automated driving has been a challenging research topic. However, despite tremendous improvements in sensor technology, pattern recognition techniques, robust signal processing, control system design, computational power, distributed control, communication bandwidth, vehicle-to-X , and other system technology areas, market introduction of a fully automated vehicle that is capable of unsupervised driving in an unstructured environment still remains a long-term goal. Advanced driver assistance systems (ADAS) and automated driver functions are highly advanced technological systems requiring an exceptionally high level of robustness and safety in order to be accepted by the end-user.

 

This talk will give an overview of the state-of-the-art as well as midterm and long-term research challenges required to introduce automated vehicles. It will be explored how to assure dependability (safety, security, reliability) by fail-aware and fail-operational approaches and by simultaneously reducing the number of required vehicle road driving tests for highly and fully automated driving systems.

 

Session 6

 

Session 6 - Innovation Labs

Stage:

13.11.2019 - 13.30 bis 15.00 Uhr

German/ Keynote

 

Titel: Automated driving - technical challenges and opportunities

 

 

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[1] D. Watzenig and M. Horn, Automated driving- safer and more efficient future driving, Springer, ISBN 978-3-319-31893-6, 2016 (See springer.com for details)