Impact of uncertainty on the prediction of airspace complexity of congested sectors

Abstract

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 long-term air traffic plans. This paper explores the influence of trajectory errors on the prediction of dynamic density and uses a worst-case analysis to describe the conditions under which forecast errors may lead to excessive complexity. Although the approach has general applicability, it is described using one definition of complexity. 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 contribute significantly to the increase in workload. If these errors cannot be reduced, it may be necessary to limit the traffic approaching the sector from these altitudes and boundaries.