Impact of Uncertainty on the Prediction of Airspace Complexity of Congested Sectors

The ability of traffic controllers to separate aircraft determines the capacity of the region of airspace under their control, referred to as a sector. Complexity metrics, specifically dynamic density, is used as an estimate for controller workload. The prediction of dynamic density is required for the development of efficient strategic air traffic flow plans. This paper explores the influence of trajectory errors and unexpected aircraft on the prediction of dynamic density. A worst-case analysis is used to describe the conditions under which forecast uncertainty may lead to excessive complexity. Although the approach has general applicability, it is described using one complexity metric. Depending on the sector and the complexity function, when a sector is highly congested, the method identifies aircraft entering the sector at certain locations, boundaries, and altitudes, whose errors in prediction impact the increase in workload significantly. Results based on the analysis of 72 days of traffic data in ...