Multiagent interactions in urban driving

In Fall 2007, the US Defense Advanced Research Projects Agency (DARPA) held the Urban Challenge, a street race between fully autonomous vehicles. Unlike previous challenges, the Urban Challenge vehicles had to follow the California laws for driving, including properly handling traffic. This article presents the modular algorithms developed largely by undergraduates at The University of Texas at Austin as part of the Austin Robot Technology team. We emphasize the aspects of the system that are relevant to multiagent interactions. Specifically, we discuss how our vehicle tracked and reacted to nearby traffic in order to allow our autonomous vehicle to safely follow and pass, merge into moving traffic, obey intersection precedence, and park.This research is supported in part by NSF CAREER award IIS-0237699 and ONR YIP award N00014-04-1-0545