Preprint Article Version 1 This version is not peer-reviewed

A Method Framework for Automatic Airspace Reconfiguration-Monte Carlo Method for Eliminating Irregular Sector Shapes Generated by Region Growth Method

Version 1 : Received: 23 July 2019 / Approved: 25 July 2019 / Online: 25 July 2019 (10:22:38 CEST)

How to cite: Ye, Z.; Kong, F.; Zhang, B.; Gao, W.; Mao, J. A Method Framework for Automatic Airspace Reconfiguration-Monte Carlo Method for Eliminating Irregular Sector Shapes Generated by Region Growth Method. Preprints 2019, 2019070287 (doi: 10.20944/preprints201907.0287.v1). Ye, Z.; Kong, F.; Zhang, B.; Gao, W.; Mao, J. A Method Framework for Automatic Airspace Reconfiguration-Monte Carlo Method for Eliminating Irregular Sector Shapes Generated by Region Growth Method. Preprints 2019, 2019070287 (doi: 10.20944/preprints201907.0287.v1).

Abstract

With the growth of air traffic demand in busy airspace, there is an urgent need for airspace sectorization to increase air traffic throughput and ease the pressure on controllers. The purpose of this paper is to develop a method framework that can perform airspace sectorization automatically, reasonably, which can be used as an advisory tool for controllers as an automatic system, especially for eliminating irregular sector shapes generated by simulated annealing algorithm (SAA) based on region growth method. Two graph cutting method, dynamic Monte Carlo method by changing location of flexible vertices (MC-CLFV) and Monte Carlo method by radius changing (MC-RC) were developed to eliminating irregular sector shapes generated by SAA in post-processing. The experimental results show that the proposed method framework of AS can automatically and reasonably generate sector design schemes that meet the design criteria. Our methodology framework and software can provide assistant design and analysis tools for airspace planners to design airspace, improve the reliability and efficiency of airspace design, and reduce the burden of airspace planners. In addition, this lays the foundation for reconstructing airspace with more intelligent method.

Subject Areas

Airspace Reconfiguration; irregular boundary smoothing; dynamic Monte Carlo method by changing location of flexible vertices; Monte Carlo method by radius changing; Voronoi diagram; graph cutting; multi-objective optimization

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