Peter Stone's Selected Publications

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A Multiagent Approach to Autonomous Intersection Management

Kurt Dresner and Peter Stone. A Multiagent Approach to Autonomous Intersection Management. Journal of Artificial Intelligence Research, 31:591–656, March 2008.
Available from journal's webpage.
View this abstract in Romanian courtesy of azoft.
And here's a version in Polish.
And now one in Russian, and one in German.

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Abstract

Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging. We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology---traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.

BibTeX Entry

@Article{JAIR08-dresner,
	author="Kurt Dresner and Peter Stone",
	title="A Multiagent Approach to Autonomous Intersection Management",
	journal = {Journal of Artificial Intelligence Research},
	month = {March},
	year = {2008},
	volume = {31},
	pages = {591--656},
	abstract = {
	Artificial intelligence research is ushering in a new era of
	sophisticated, mass-market transportation technology.  While computers
	can already fly a passenger jet better than a trained human pilot,
	people are still faced with the dangerous yet tedious task of driving
	automobiles. Intelligent Transportation Systems (ITS) is the field that
	focuses on integrating information technology with vehicles and
	transportation infrastructure to make transportation safer, cheaper, and
	more efficient.  Recent advances in ITS point to a
	future in which vehicles themselves handle the vast majority of the
	driving task.  Once autonomous vehicles become popular, autonomous
	interactions amongst \emph{multiple} vehicles will be possible.  Current
	methods of vehicle coordination, which are all designed to work with
	human drivers, will be outdated.  The bottleneck for roadway
	efficiency will no longer be the drivers, but rather the mechanism by
	which those drivers' actions are coordinated. While open-road driving
	is a well-studied and more-or-less-solved problem, urban traffic
	scenarios, especially intersections, are much more challenging.
	We believe current methods for controlling traffic, specifically at
	intersections, will not be able to take advantage of the increased
	sensitivity and precision of autonomous vehicles as compared to human
	drivers. In this article, we suggest an alternative mechanism for
	coordinating the movement of autonomous vehicles through intersections.
	Drivers and intersections in this mechanism are treated as autonomous agents
	in a multiagent system. In this multiagent system, intersections use a new
	reservation-based approach built around a detailed communication protocol,
	which we also present. We demonstrate in simulation that our new mechanism
	has the potential to significantly outperform current intersection control
	technology---traffic lights and stop signs. Because our mechanism can
	emulate a traffic light or stop sign, it subsumes the most popular current
	methods of intersection control. This article also presents two extensions
	to the mechanism. The first extension allows the system to control
	human-driven vehicles in addition to autonomous vehicles. The second gives
	priority to emergency vehicles without significant cost to civilian
	vehicles. The mechanism, including both extensions, is implemented and
	tested in simulation, and we present experimental results that strongly
	attest to the efficacy of this approach.
	},
	wwwnote = {Available from <a
href="http://www.jair.org/papers/paper2502.html">journal's web
page</a>.<br><a
href="http://www.azoft.com/people/seremina/edu/multiagent-rom.html">View this abstract in Romanian</a> courtesy of <a href="http://www.azoft.com/">azoft</a>.<br>And here's a <a href="http://autoersatzteile.de/blog/peter-stone-wybrane-publikacje">version in Polish</a>.<br>And now one in <a href="http://web-meister.ru/science/mnogoagentnyi-podkhod-k-upravleniyu-avtonomnogo-peresecheniya">Russian</a>, and one in <a href="http://led24.de/blog/wieloagentowych-podejscie-do-autonomicznego-zarzadzania-intersection">German</a>.},
}

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