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Planning for Improving Throughput in Autonomous Intersection Management Tsz-Chiu Au, Michael Quinlan, Nicu Stiurca, Jesse Zhu, Peter Stone
 

Summary: Planning for Improving Throughput in Autonomous Intersection Management
Tsz-Chiu Au, Michael Quinlan, Nicu Stiurca, Jesse Zhu, Peter Stone
Department of Computer Science
The University of Texas at Austin
1 University Station C0500
Austin, Texas 78712-1188
{chiu,mquinlan,jzhu,nstiurca,pstone}@cs.utexas.edu
Abstract
The impressive results of the 2007 DARPA Urban
Challenge showed that fully autonomous vehicles are
technologically feasible with current intelligent vehi-
cle hardware. It is natural to ask how current trans-
portation infrastructure can be improved when most ve-
hicles are driven autonomously in the future. Dres-
ner and Stone proposed a new intersection control
mechanism called Autonomous Intersection Manage-
ment (AIM) and showed in simulation that intersec-
tion control can be made more efficient than the tra-
ditional control mechanisms such as traffic signals and
stop signs. In this paper, we extend the study to the real

  

Source: Au, Tsz-Chiu - Department of Computer Sciences, University of Texas at Austin

 

Collections: Computer Technologies and Information Sciences