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.
DepartmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
IFAC Symposium on Intelligent Autonomous Vehicles
Aoude, et al. "Sampling-based assessment algorithms for intersection collisions involving errant drivers," IFAC Symposium on Intelligent Autonomous Vehicles, 2010.
Author's final manuscript