@COMMENT This file was generated by bib2html.pl <http://www.cs.cmu.edu/~pfr/misc_software/index.html#bib2html> version 0.90
@COMMENT written by Patrick Riley <http://www.cs.cmu.edu/~pfr>
@COMMENT This file came from Peter Stone's publication pages at
@COMMENT http://www.cs.utexas.edu/~pstone/papers
@InProceedings{AAAIWS10-au,
	author = {Tsz-Chiu Au and Peter Stone},
	booktitle = {AAAI 2010 Workshop on Bridging The Gap Between Task And Motion Planning (BTAMP)},
	title = {Motion Planning Algorithms for Autonomous Intersection Management},
	year = 2010,
	abstract = {
		The impressive results of the 2007 DARPA Urban Challenge showed
		that fully autonomous vehicles are technologically feasible with current
		intelligent vehicle hardware.  It is natural to ask how current
		transportation infrastructure can be improved when most vehicles are
		driven autonomously in the future.  Dresner and Stone proposed a new
		intersection control mechanism called Autonomous Intersection Management
		(AIM) and showed in simulation that intersection control can be made
		more efficient than the traditional control mechanisms such as traffic
		signals and stop signs.  In this paper, we extend the study by examining
		the relationship between the precision of cars' motion controllers and
		the efficiency of the intersection controller.  We propose a
		planning-based motion controller that can reduce the chance that
		autonomous vehicles stop before intersections, and show that this
		controller can increase the efficiency of the intersection control
		mechanism.
	},
}