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Kurt Dresner and Peter Stone. Multiagent Traffic Management: A Protocol for Defining Intersection Control Policies. Technical Report UT-AI-TR-04-315, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2004.
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Traffic congestion is one of the leading causes of lost productivityand decreased standard of living in urban settings. Recent advancesin artificial intelligence suggest vehicle navigation by autonomousagents will be possible in the near future. In a previous paper,we proposed a reservation-based system for alleviating traffic congestion,specifically at intersections. This paper extends our prototype implementationin several ways with the aim of making it more implementable in thereal world. In particular, we add the ability of vehicles to turn,enable them to accelerate while in the intersection, improve theefficiency and sensor model of the driver agents, and augment theirinteraction capabilities with a detailed protocol such that the vehiclesdo not need to know anything about the intersection control policy.The use of this protocol limits the interaction of the driver agentand the intersection manager to the extent that it is a reasonableapproximation of reliable wireless communication. Finally, we describehow different intersection control policies can be expressed withthis protocol and limited exchange of information. All improvementsare fully implemented and tested, and we present detailed empiricalresults validating their effectiveness.
@TECHREPORT{TR-aim-protocol-04-315,
author = {Kurt Dresner and Peter Stone},
title = {Multiagent Traffic Management: A Protocol for Defining Intersection Control Policies},
institution = {The University of Texas at Austin, Department of Computer Sciences, AI Laboratory},
year = {2004},
number = {UT-AI-TR-04-315},
month = {December},
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 a previous paper,
we proposed a reservation-based system for alleviating traffic congestion,
specifically at intersections. This paper extends our prototype implementation
in several ways with the aim of making it more implementable in the
real world. In particular, we add the ability of vehicles to turn,
enable them to accelerate while in the intersection, improve the
efficiency and sensor model of the driver agents, and 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 improvements
are fully implemented and tested, and we present detailed empirical
results validating their effectiveness.},
bib2html_rescat = {Autonomous Intersection Management},
bib2html_pubtype = {Tech Report}
}
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