Sampling-Based Threat Assessment Algorithms for Intersection Collisions Involving Errant Drivers
Name
Aoude.pdf
Description
Main article
Size
818.3 KB
Format
Adobe PDF
Checksum (MD5)
d071fdcdc917e15f2161451c6a0cf6db
Author(s)
Aoude, Georges
How, Jonathan P.
Luders, Brandon Douglas
Pilutti, Tom E.
Date Issued
September 2010
Journal
IFAC Symposium on Intelligent Autonomous Vehicles
Citation
Aoude, et al. "Sampling-based assessment algorithms for intersection collisions involving errant drivers," IFAC Symposium on Intelligent Autonomous Vehicles, 2010.
Version
Author's final manuscript
Abstract
This paper considers the decision-making problem for a vehicle crossing a road
intersection in the presence of other, potentially errant, drivers. This problem is considered in
a game-theoretic framework, where the errant drivers are assumed to be capable of causing
intentional collisions. Our approach is to simulate the possible behaviors of errant drivers using
RRT-Reach, a modi ed application of rapidly-exploring random trees. A novelty in RRT-Reach
is the use of a dual exploration-pursuit mode, which allows for e cient approximation of the
errant reachability set for some xed time horizon. Through simulation and experimental results
with a small autonomous vehicle, we demonstrate that this threat assessment algorithm can be
used in real-time to minimize the risk of collision.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Attribution-Noncommercial-Share Alike 3.0 Unported
Persistent DSpace Link
DOI of Published Version
http://iav2010.unile.it/CMSystem/modules/request.php?module=oc_program&action=summary.php&id=150
