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Collision avoidance systems, whether for manned or unmanned aircraft, must reliably prevent collision while minimizing alerts. Deciding what action to execute at a particular instant may be framed as a multiple-objective optimization problem has explored methods of efficiently computing the that can be solved offline by computers. Prior work optimal collision avoidance logic from a probabilistic model of aircraft behavior and a cost function. One potential concern with using a probabilistic model to construct the logic is that the model may not adequately represent the real world. Inaccuracies in the model could lead to vulnerabilities in the system when deployed. This paper evaluates the robustness of collision avoidance optimization to modeling errors.