Arrival Management Decisions by Visualising 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 sequence managers in planning inbound flights to optimize capacity, flight efficiency, and predictability. All AMANs are based on predictions of an aircraft\u27s arrival time. Due to various disturbances the error of these predictions grows larger with the prediction horizon. Air Traffic Controllers 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 paper proposes and tests an enhancement based on the probability density function of the expected arrival time, allowing controllers to include uncertainty in the decision making process