Sampling-Based Threat Assessment Algorithms for Intersection Collisions Involving Errant Drivers
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 ap...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
2010
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| Online Access: | http://hdl.handle.net/1721.1/60041 https://orcid.org/0000-0001-8576-1930 |
| Summary: | 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. |
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