Supporting arrival management by visualizing uncertainty.

To balance the flow of inbound aircraft and the capacity at airports, more and more Air Navigation Service Providers use Arrival Management (AMAN) systems. These provide decision support to air traffic controllers in planning inbound flights to optimize capacity, flight efficiency, and predictability. All AMANs are based on predictions of an aircraft’s arrival time. Due to various disturbances the error of these predictions grows larger with the prediction horizon. Planners will therefore not be able to effectively use the support at a certain horizon due to the lack of confidence in the provided information. This project proposes and tests enhancements to controller interfaces based on the probability density function of the expected arrival time, allowing planners to include uncertainty in the decision-making process.