Daniel Watzenig is CTO at Virtual Vehicle Research and Professor of Autonomous Driving at Graz University of Technology, Austria. His research interests focus on sense & control of cooperative autonomous vehicles, as well as the software stack of autonomous systems. He is the Editor-in-Chief of the SAE Int. Journal on Connected and Automated Vehicles and Distinguished Lecturer at IEEE IMS. Since 2019, Daniel has been an invited guest lecturer at Stanford University, USA, teaching multi-sensor perception and data fusion. He also teaches vehicle autonomy at Tongji University in Shanghai, China.
How does your work align with the mission of PAVE to educate the public on AV technology and its promise?
As a university professor, I am in charge of educating future engineers in both theoretical foundations and emerging technologies such as connected, cooperative, and autonomous vehicles. Undergraduates, graduates, and PhD candidates learn the theoretical, algorithmic, and implementation aspects of main techniques for autonomy in my related courses, problem classes, and hands-on labs. As a researcher, my clear focus is to significantly contribute to research, development, and innovation, making autonomous vehicles more reliable and safer to address currently existing public concerns. A factor of success is a close collaboration between industry, academia, and public authorities.
What are the current barriers you see in public acceptance of automated vehicles?
The major challenge is to make autonomous driving tangible for the end-user and to build public trust through easy access to this exciting technology. This will help to eliminate prejudices, correct false information, remove the fear of autonomy, and ultimately highlight the benefits. Along with public road offers, autonomous racing events play an important role, demonstrating autonomy at high speeds, challenging driving dynamics, and adverse weather conditions. Many breakthrough technologies have been invented in extreme sports! We – for sure – need more outreach activities highlighting and explaining the technology, concepts, applications, and readiness level of AI-powered autonomous vehicles.