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Modeling the Controller's Conflict Detection Task Using Fast Time Simulation

This paper shows how the CATS (Complete Air Traffic Simulator) can model the controlleri¯s conflict detection task using a sliding time window. Because of uncertainties, detection is by far the most time consuming and cognitively challenging aspect of air traffic control. The processes governing detection are distinct from resolution actions. Few conflicts detected lead to a resolution maneuver. Because future aircraft positions are uncertain, controllers detect many more conflicts or "potential conflicts" than actually occur. In this paper, we solve conflicts in a real time context and compare different uncertainty scenarios. We show how uncertainties impact the number of theoretical potential conflicts detected and the increase the number of unnecessary maneuver actions required to keep the traffic safe. When we deal with realistic uncertainty values, the majority of calculation time in CATS is used for calculating maneuvers that will usually not be transmitted to pilots. This observation reveals the true nature of the controlleri¯s workload today.