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Kurt Dresner and Peter Stone. Turning the Corner: Improved Intersection Control for Autonomous Vehicles. In The 2005 IEEE Intelligent Vehicles Symposium, Las Vegas, NV, USA, June 2005.
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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 (1) add the ability of vehicles toturn, (2) enable them to accelerate while in the intersection, (3)give a better sensor model and communication-efficient heuristicto our driver agent, and (4) augment their interaction capabilitieswith a detailed protocol such that the vehicles do not need to knowanything about the intersection control policy. The use of this protocollimits the interaction of the driver agent and the intersection managerto the extent that it is a reasonable approximation of reliable wirelesscommunication. We then use this protocol to implement a new controlpolicy: the stop sign. All three improvements are fully implementedand tested, and we present detailed empirical results validatingtheir effectiveness.
@INPROCEEDINGS{2005iv-dresner,
author = {Kurt Dresner and Peter Stone},
title = {Turning the Corner: Improved Intersection Control for Autonomous
Vehicles},
booktitle = {The 2005 IEEE Intelligent Vehicles Symposium},
year = {2005},
month = {June},
address = "Las Vegas, NV, USA",
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 (1) add the ability of vehicles to
turn, (2) enable them to accelerate while in the intersection, (3)
give a better sensor model and communication-efficient heuristic
to our driver agent, and (4) 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. We then use this protocol to implement a new control
policy: the stop sign. All three improvements are fully implemented
and tested, and we present detailed empirical results validating
their effectiveness.},
bib2html_rescat = {Autonomous Intersection Management},
bib2html_pubtype = {Symposium}
}
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