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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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Attribution-Noncommercial-Share Alike 3.0 Unported http://creativecommons.org/licenses/by-nc-sa/3.0/
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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.
Date issued
2010-09
URI
http://hdl.handle.net/1721.1/60041
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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

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