Peter Stone's Selected Publications

Classified by TopicClassified by Publication TypeSorted by DateSorted by First Author Last NameClassified by Funding Source


Evasion Planning for Autonomous Vehicles at Intersections

Evasion Planning for Autonomous Vehicles at Intersections.
Tsz-Chiu Au, Chien-Liang Fok, Sriram Vishwanath, Christine Julien, and Peter Stone.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2012.

Download

[PDF]1.3MB  [postscript]18.7MB  

Abstract

Autonomous intersection management (AIM) is a new intersection control protocol that exploits the capabilities of autonomous vehicles to control traffic at intersections in a way better than traffic signals and stop signs. A key assumption of this protocol is that vehicles can always follow their trajectories. But mechanical failures can occur in real life, causing vehicles to deviate from their trajectories. A previous approach for handling mechanical failure was to prevent vehicles from entering the intersection after the failure. However, this approach cannot prevent collisions among vehicles already in the intersection or too close to stop because (1) the lack of coordination among vehicles can cause collisions during the execution of evasive actions; and (2) the intersection may not have enough room for evasive actions. In this paper, we propose a preemptive approach that pre-computes evasion plans for several common types of mechanical failures before vehicles enter an intersection. This preemptive approach is necessary because there are situations in which vehicles cannot evade without pre-allocation of space for evasion. We present a modified AIM protocol and demonstrate the effectiveness of evasion plan execution on a miniature autonomous intersection testbed.

BibTeX Entry

@InProceedings{IROS12-chiu,
  author = {Tsz-Chiu Au and Chien-Liang Fok and Sriram Vishwanath and Christine Julien and Peter Stone},
  title = {Evasion Planning for Autonomous Vehicles at Intersections},
  booktitle = {Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems},
  month = {October},
  year = {2012},
  abstract = {
Autonomous intersection management (AIM) is a new intersection control protocol that exploits the capabilities of autonomous vehicles to control traffic at intersections in a way better than traffic signals and stop signs.  A key assumption of this protocol is that vehicles can always follow their trajectories.  But mechanical failures can occur in real life, causing vehicles to deviate from their trajectories. A previous approach for handling mechanical failure was to prevent vehicles from entering the intersection after the failure.  However, this approach cannot prevent collisions among vehicles already in the intersection or too close to stop because (1) the lack of coordination  among vehicles can cause collisions during the execution of evasive actions; and (2) the intersection may not have enough room for evasive actions.  In this paper, we propose a preemptive approach that pre-computes evasion plans for several common types of mechanical failures before vehicles enter an intersection.  This preemptive approach is necessary because there are situations in which vehicles cannot evade without pre-allocation of space for evasion.  We present a modified AIM protocol and demonstrate the effectiveness of evasion plan execution on a miniature autonomous intersection testbed.},
}

Generated by bib2html.pl (written by Patrick Riley ) on Tue Nov 19, 2024 10:24:44