The Value of Reduced Uncertainty in Air Traffic Flow Management

Abstract

Given the numerous sources of uncertainty inherent in the National Airspace System, plans to alleviate demand-capacity imbalances are sometimes untrustworthy. In addition, differing solutions to demand-capacity imbalances are difficult to compare in terms of their potential quality in the face of weather and schedule uncertainties. In this work, a method for evaluating the robustness of a traffic scheduling solution to various uncertainties is presented. By converting solutions to predicted demands and capacities of sectors and airports together with measures of uncertainty on those predictions, any given plan can be evaluated based on the number of expected capacity violations along with distributions on their severity. With such measures, the most robust of a set of potential plans might be chosen by a traffic manager. As a side-effect of this approach, the value of reduced uncertainties can be measured in terms of reduced expected violations. The value of reduced uncertainty is demonstrated using a deterministic, minimum-delay approach to managing demand-capacity imbalances. When the deterministic solution is measured in terms of expected violations given models of demand and capacity uncertainty, results indicate that if the calculated uncertainty measures are reduced by 50%, then the number of expected violations will decrease by just over 40%.

Real-time flight scheduling for optimal air traffic flow management

“…However, several studies have acknowledged and attempted to quantify the inherent demand uncertainty present in air transportation system. In [69], the authors have identified and quantified both capacity uncertainty due to weather conditions, and the demand uncertainty due to deviations in time. Furthermore, they have proposed a method to measure the expected number of violations (demand exceeding capacity) in a given schedule.…”