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pAGe 32 DARpA URBAN CHALLeNGe This system has the following advantages: n Meets tough realtime requirements, even with a nonrealtimecapable PC. n Safety functions can be implemented directly on the reliable AutoBox (emergency stop). n Trajectory planning and trajectory control are not coupled. While there can be no doubt that the challenge has given an enormous boost to the development of selfdriving vehicles, it is actually only a sideshow. TR28’s real goals are a lot higher (http://www.kognimobil.org/), even though achieving them is a long way off. In the future, the vehicles will have to cope without receiving prior information on their environment. A detailed map of the road network like that used by the vehicles in the Urban Challenge might no longer be necessary. A vehicle approaching an intersection would recognize it as such with the aid of its sensors. Data interchange between vehicles is also conceivable. Team Oshkosh Truck, Wisconsin, USA “ We were mainly 3 groups working together – Oshkosh Truck, Wisconsin (headquarters of the Oshkosh company); Teledyne, California; and Parma University in Italy with the Artificial Vision and Intelligent Systems Laboratory (VisLab). We organized weekly teleconferences and many trips to the US to develop and test the system. The teamwork was very successful and well coordinated. We had several critical, very exciting situations. For example, we were still testing the system the night before the race. We – just like everyone else, I believe – had a very tight schedule that did not allow us to include everything we designed and realized. For example, we unfortunately did not use the whole potential of vision (we developed 4 systems and only used 2 of them!) due to lack of testing time. Oshkosh is indeed interested in having these technologies in its vehicles. For Oshkosh and VisLab the Urban Challenge was not just a race and nothing more. We see a wide range of possibilities to implement these technologies on real vehicles as a retrofit. And we already did so: We demonstrated a palletized load system (PLS) vehicle able to reach a destination, unload, and get back autonomously. We did that just after the Grand Challenge, in January 2006.”
“ The whole event was amazing! A wonderful experience, even if our vehicle didn’t make it to the finish line as it did two years ago during the DARPA Grand Challenge. We learned a lot from this and previous experiences: We already have 15 years’ experience in the field of autonomous vehicles, but nevertheless this experience let us improve our systems in terms of robustness and maintenance.” Prof. Alberto Broggi, Team Oshkosh Truck, Parma University, Italy Prof. Alberto Broggi was responsible for Team Oshkosh in the VisLab team. In particular, his group was involved with sensors for the surrounding environment. They used video cameras and a link between vision and laser for this. The Oshkosh truck navigating the city streets. pAGe 33
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Page 49 and 50: A conversation with Dr. Herbert Han
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Page 53 and 54: “ We haven’t wasted our time on
Page 55 and 56: The young scientists Wolfgang Fritz
Page 57 and 58: Interview Dr. Herbert Schütte, Dir
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