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Multiagent Traffic Management: An Improved Intersection Control Mechanism.
Kurt
Dresner and Peter Stone.
In The Fourth International Joint Conference
on Autonomous Agents and Multiagent Systems, ACM Press, New York, NY, July 2005.
Some
Extended
version citable as University of Texas at Austin AI lab technical
report number UT-AI-TR-04-315
AAMAS-2005
[PDF]143.5kB [postscript]216.7kB
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.
@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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