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.

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In Proceedings of IROS 2010-IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), October 2010.

@InProceedings{IROS10-quinlan, title={Bringing Simulation to Life: A Mixed Reality Autonomous Intersection}, author={Michael Quinlan and Tsz-Chiu Au and Jesse Zhu and Nicolae Stiurca and Peter Stone}, booktitle={Proceedings of IROS 2010-IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)}, month={October}, url="http://www.cs.utexas.edu/users/ai-lab?IROS10-quinlan", year={2010} }