The objective of this research is to design and demonstrate an agent-based modeling and analysis tool for evaluating General Aviation (GA) pilot situation awareness under free flight air traffic management (ATM). A computational tool is developed to assess free flight's potential effect on GA operators, by combining an agent-based representation of the overall pilot/vehicle/ATM system with quantitative modelbased metrics of pilot SA. The model's performance is demonstrated in a set of simulation trials designed to measure the pilot agent's ability to recognize and correctly assess protected zone conflicts in free flight ATM, using information available from a hypothetical cockpit display of traffic information. A set of simulations is presented to examine the effect of sensor accuracy and attention allocation on pilot awareness of protected zone conflict hazards posed by intruder aircraft. The results show that reducing sensor accuracy leads to an increase in overall SA error, and that the pilot agent divides its attention over multiple traffic hazards in proportion to each intruder's hazard potential. This attention-sharing varies dynamically as the conflict situation changes, in a manner that is consistent with intuitive expectations.
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