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Bringing Simulation to Life: A Mixed Reality Autonomous Intersection.
Michael
Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter
Stone.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
2010.
Video available at http://www.cs.utexas.edu/~aim/video/MixedReality.wmv
Fully autonomous vehicles are technologically feasible with the current generation of hardware, as demonstrated by recent robot car competitions. Dresner and Stone proposed a new intersection control protocol called Autonomous Intersection Management (AIM) and showed that with autonomous vehicles it is possible to make intersection control much more efficient than the traditional control mechanisms such as traffic signals and stop signs. The protocol, however, has only been tested in simulation and has not been evaluated with real autonomous vehicles. To realistically test the protocol, we implemented a mixed reality platform on which an autonomous vehicle can interact with multiple virtual vehicles in a simulation at a real intersection in real time. From this platform we validated realistic parameters for our autonomous vehicle to safely traverse an intersection in AIM. We present several techniques to improve efficiency and show that the AIM protocol can still outperform traffic signals and stop signs even if the cars are not as precisely controllable as has been assumed in previous studies.
@InProceedings{IROS10-quinlan,
author = "Michael Quinlan and Tsz-Chiu Au and Jesse Zhu and Nicolae Stiurca and Peter Stone",
title = "Bringing Simulation to Life: A Mixed Reality Autonomous Intersection",
booktitle = "Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)",
location = "Taipei, Taiwan",
month = "October",
year = "2010",
abstract = {
Fully autonomous vehicles are technologically feasible with the
current generation of hardware, as demonstrated by recent robot car
competitions. Dresner and Stone proposed a new intersection control
protocol called \emph{Autonomous Intersection Management} (AIM) and
showed that with autonomous vehicles it is possible to make intersection
control much more efficient than the traditional control mechanisms such
as traffic signals and stop signs. The protocol, however, has only been
tested in simulation and has not been evaluated with real autonomous
vehicles. To realistically test the protocol, we implemented a mixed
reality platform on which an autonomous vehicle can interact with
multiple virtual vehicles in a simulation at a real intersection in real
time. From this platform we validated realistic parameters for our
autonomous vehicle to safely traverse an intersection in AIM. We
present several techniques to improve efficiency and show that the AIM
protocol can still outperform traffic signals and stop signs even if the
cars are not as precisely controllable as has been assumed in previous
studies.
},
wwwnote={Video available at <a href="http://www.cs.utexas.edu/~aim/video/MixedReality.wmv">http://www.cs.utexas.edu/~aim/video/MixedReality.wmv</a>},
}
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