Sampling-Based Threat Assessment Algorithms for Intersection Collisions Involving Errant Drivers
Author(s)
Aoude, Georges; How, Jonathan P.; Luders, Brandon Douglas; Pilutti, Tom E.
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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.
Date issued
2010-09Department
Massachusetts Institute of Technology. Department of Aeronautics and AstronauticsJournal
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