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Keynote Lectures

Available Soon
Karl Henrik Johansson, KTH Royal Institute of Technology, Sweden

Technologies Towards Automated Vehicles
Christoph Stiller, Karlsruhe Institute of Technology (KIT), Germany

Available Soon
Rudy R. Negenborn, Delft University of Technology, Netherlands

 

Keynote Lecture

Karl Henrik Johansson
KTH Royal Institute of Technology
Sweden
 

Brief Bio
Available Soon


Abstract
Available Soon



 

 

Technologies Towards Automated Vehicles

Christoph Stiller
Karlsruhe Institute of Technology (KIT)
Germany
 

Brief Bio
Christoph Stiller studied Electrical Engineering in Aachen, Germany and Trondheim, Norway, and received the Diploma degree and the Dr.-Ing. degree (Ph.D.) from Aachen University of Technology in 1988 and 1994, respectively. He worked with INRS-Telecommunications in Montreal, Canada for a post-doctoral year in 1994/1995 and with Robert Bosch GmbH, Germany from 1995 - 2001. In 2001 he became Chaired Professor and Director of the Institute for Measurement and Control Systems at Karlsruhe Institute of Technology, Germany.

Dr. Stiller is Fellow of the IEEE and serves as Chair of the Technical Committee for Self Driving Automobiles. He has been inaugurating Editor-in-Chief of the IEEE Intelligent Transportation Systems Magazine (2009-2011) and has been Associate Editor thereafter. His automated driving team AnnieWAY has been finalist in the Darpa Urban Challenge 2007 as well as first and second winner of the Grand Cooperative Driving Challenge in 2011 and 2016, respectively. He has served is several positions for the IEEE Intelligent Transportation Systems Society including being its President 2012-2013.


Abstract
Vehicle automation is among the most fascinating trends in automotive electronics and a huge challenge to the Intelligent Transportation Systems community. This talk with discuss the state-of-the-art and a potential evolution of automated vehicles. We discuss lessons learned from the autonomous Bertha Benz memorial tour from Mannheim to Pforzheim.

We investigate probabilistic and deep learning approaches to perception and planning methods for automated vehicles and elaborate on the potential and cooperative driving. Beyond the fascinating progress that we have witnessed in the past decades, the remaining challenges for achieving full autonomy for self-driving cars still require substantial research. Reliable perception, provable behavioral safety and safety validation are prominent examples for these. Furthermore, fail-safe requirement lead to novel vehicle architectures. Technical supervision and teleoperation may lower the hurdles for deployment. Last, not least, a societal consensus on an acceptable risk level is required and compliance with this consensus must be tracked in empirical safety analysis.



 

 

Keynote Lecture

Rudy R. Negenborn
Delft University of Technology
Netherlands
 

Brief Bio
Available Soon


Abstract
Available Soon



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