The 7th IFAC Symposium on Intelligent Autonomous Vehicles 2010

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Sampling-Based Threat Assessment Algorithms for Intersection Collisions Involving Errant Drivers

Georges Aoude
Massachusetts Institute of Technology
United States

Brandon Luders
Massachusetts Institute of Technology
United States

Jonathan How
Massachusetts Institute of Technology
United States

Tom Pilutti
Ford Research and Advanced Engr
United States

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 modified application of rapidly-exploring random trees. A novelty in RRT-Reach is the use of a dual exploration-pursuit mode, which allows for efficient approximation of the errant reachability set for some fixed 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.

 

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