Peter Stone's Selected Publications

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Multiagent Traffic Management: An Improved Intersection Control Mechanism

Kurt Dresner and Peter Stone. Multiagent Traffic Management: An Improved Intersection Control Mechanism. In The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, ACM Press, New York, NY, July 2005.
Some videos referenced in the paper. The main project page
Extended version citable as University of Texas at Austin AI lab technical report number UT-AI-TR-04-315
AAMAS-2005

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Abstract

Traffic congestion is one of the leading causes of lost productivity and decreased standard of living in urban settings. Recent advances in artificial intelligence suggest vehicle navigation by autonomous agents will be possible in the near future. In previous work, a reservation-based system for alleviating traffic congestion, specifically at intersections was proposed. This paper extends that prototype implementation in several ways with the aim of making it more implementable in the real world. In particular, we 1) add the ability of vehicles to turn, 2) enable them to accelerate while in the intersection, and 3) augment their interaction capabilities with a detailed protocol such that the vehicles do not need to know anything about the intersection control policy. The use of this protocol limits the interaction of the driver agent and the intersection manager to the extent that it is a reasonable approximation of reliable wireless communication. Finally, we describe how different intersection control policies can be expressed with this protocol and limited exchange of information. All three improvements are fully implemented and tested, and we present detailed empirical results validating their effectiveness.

BibTeX Entry

@InProceedings{AAMAS05-intersection,
        author="Kurt Dresner and Peter Stone",
        title="Multiagent Traffic Management: An Improved Intersection Control Mechanism",
        booktitle="The Fourth International Joint Conference on Autonomous Agents and  Multiagent Systems",
       editor="Frank Dignum and Virginia Dignum and Sven Koenig and Sarit Kraus and Munindar P.~Singh and Michael Wooldridge",
      publisher="{ACM Press}",
      address="New York, NY",
       month="July",year="2005",
       abstract={
                 Traffic congestion is one of the leading causes of
                 lost productivity and decreased standard of living in
                 urban settings.  Recent advances in artificial
                 intelligence suggest vehicle navigation by autonomous
                 agents will be possible in the near future.  In
                 previous work, a reservation-based system for
                 alleviating traffic congestion, specifically at
                 intersections was proposed.  This paper extends that
                 prototype implementation in several ways with the aim
                 of making it more implementable in the real world.
                 In particular, we 1) add the ability of vehicles to
                 turn, 2) enable them to accelerate while in the
                 intersection, and 3) augment their interaction
                 capabilities with a detailed protocol such that the
                 vehicles do not need to know anything about the
                 intersection control policy.  The use of this
                 protocol limits the interaction of the driver agent
                 and the intersection manager to the extent that it is
                 a reasonable approximation of reliable wireless
                 communication.  Finally, we describe how different
                 intersection control policies can be expressed with
                 this protocol and limited exchange of information.
                 All three improvements are fully implemented and
                 tested, and we present detailed empirical results
                 validating their effectiveness.
       },
       wwwnote={Some <a
href="http://www.cs.utexas.edu/users/kdresner/papers/2005aamas/">videos</a> referenced in the paper.  The <a href="http://www.cs.utexas.edu/~aim/">main project page</a><br>
<a href="http://www.cs.utexas.edu/research/publications/ncstrl/ncstrl2html.cgi?what=AI%20Abstracts&when=2004#UTEXAS.CS//AI04-315">Extended version</a> citable as <a href="http://www.cs.utexas.edu/research/publications/"> University of Texas at Austin AI lab technical report</a> number UT-AI-TR-04-315<br>
       <a href="http://www.aamas2005.nl/">AAMAS-2005</a>},
}       

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