Static sectorization approach to dynamic airspace configuration using approximate dynamic programming

Abstract

The National Airspace System (NAS) is an important and a vast resource. Efficient management of airspace capacity is important to ensure safe and systematic operation of the NAS eventually resulting in maximum benefit to the stakeholders. Dynamic Airspace Configuration (DAC) is one of the NextGen Concept of Operations (ConOps) that aims at efficient allocation of airspace as a capacity management technique.This paper is a proof of concept for the Approximate Dynamic Programming (ADP) approach to Dynamic Airspace Configuration (DAC) by static sectorization. The objective of this paper is to address the issue of static sectorization by partitioning airspace based on controller workload i.e. airspace is partitioned such that the controller workload is balanced between adjacent sectors. Several algorithms exist that address the issue of static restructuring of the airspace to meet capacity requirements on a daily basis. The intent of this paper is to benchmark the results of our methodology with the state-of-the-art algorithms and lay a foundation for future work in dynamic resectorization.

Cognitive dynamic airspace management

“…[38,118,106,123,67,101] ) are generally referred to the airspace sectorization problem. Over the years, the problem has been modelled as a graph partitioning problem consisting of air tra c flows [38,17,109,80,77,24,98], a combinatorial problem of elementary building blocks [21,123,26,39,76,18,58,74,67] and a continuous black-box problem with the use of computational geometry [106,119,107]. The use of Voronoi Diagram as a computational geometry tool in the airspace sectorization problem posed as a continuous black-box problem is shown to be e↵ective in previous studies [106,107].…”

“…• Bottom-up Approach [21,123,26,48,39,76,18,58,74,67,101]: Combination of elementary shapes or blocks to form sectors…”

“…The bottom-up approach for airspace sectorization is primarily based on the combination of simple polygon mesh and is mostly modelled as a combinatorial problem [123,26,21,58,74,67]. Further, the combination of various elementary sectors (from some existing sectorization) is optimised based on varying tra c flows in [101,48,39,18].…”

“…(a)Re-entry (b)Overload Last but not least, there is a safety consideration on Table 2.1, which is important for the feasibility of airspace sector shapes in the real world. In previous works, papers that considered the minimum distance from areas of potential conflicts to sector boundaries are taken as a constraint [38,123,109,37,77,98,58,74]. The use of constraint is appropriate because if the solution does not satisfy the safety consideration, the sectors are highly likely to be unsafe for implementation in the real world.…”

“…Studies have shown that changing sector boundaries a↵ects the ATCs performance [62]. Following this, measurements for changes in the reconfiguration of sector shapes were proposed in [18,74,105,24]. In particular, the general concept of sector similarity was proposed in [105] to measure how di↵erent the sectors are.…”