# A Study on the Normalized Delineation of Airspace Sectors Based on Flight Conflict Dynamics
## 1 Introduction  
After the COVID-19 epidemic, the civil aviation transportation industry has rapidly recovered and entered a new strong development phase; the airspace operation environment is becoming more and more complex, the air traffic flow continues to increase, and the problems arising from various aspects, such as air transportation efficiency and flight safety, are becoming more and more serious. In order to sort out the air traffic, we usually divide the airport area into multiple sectors, which are commanded and deployed by multiple controllers. However, the number of aircraft in different sectors may vary greatly at the same time, which leads to a very heavy load on the busy controllers in some sectors and poses safety risks. The scientific and reasonable division of airport sectors can effectively solve this problem and ensure flight safety, which makes sector optimization a hot research topic in the industry [1]. At present, the research on airspace sector-delineation technology at home and abroad mainly adopts mathematical modeling methods, such as graph theory and clustering and intelligent optimization algorithms. [PERSON] et al. establish Voronoi polygons by taking randomly generated points in the two-dimensional airspace as the clustering centers or nodes, and determine the sector-delineation scheme by adopting genetic algorithms with the goal of balancing the control loads in each polygon [2]. On the basis of this, [PERSON] proposed a sector-delineation method based on controller workload by dividing the airspace into grids according to flight safety intervals and flight route requirements [3]. [PERSON] and analyzed an algorithm for the optimal sector delineation of airspace with the goal of balancing dynamic density, and clustered the spatial positions of the recorded aircraft based on the nature of the metrics and the location of the airspace boundaries [4]. [PERSON] combined the tree search algorithm with neural network to explore the division method of airspace block combination on the basis of airspace segmentation [5]. [PERSON] applied the theory of the variable precision rough set to derive the optimal number of sectors in various cases, and then derived the final optimal combination of sectors, which proved the practicability of this method [6]. [PERSON] et al. use Voronoi diagram and a particle-swarm optimization algorithm to balance the workload of each waypoint, and establish a sector-combination optimization model [7]. [PERSON] et al. propose a sector-delineation method based on the workload of control [8]. [PERSON] et al. design a sector-delineation and optimization algorithm based on the genetic algorithm for 3D airspace [9]. [PERSON] analyzes the complexity factors of the airspace using principal component analysis, and selects a sector-delineation algorithm suitable for the structural characteristics of the airspace through a comprehensive description and comparison of different intelligent algorithms to select sector-delineation algorithms suitable for the structural characteristics of the airspace for different airspaces [10]. [PERSON] proposes a method based on historical trajectory radar data, extracting navigational information, and realizing the sector delineation of terminal airspace through data mining [11]. Most current sector delineation mainly focuses on the three aspects of reducing air traffic complexity, equalizing controller load, and improving airspace capacity. The current airspace sector-delineation research mainly focuses on modeling the target airspace based on known airspace information in order to achieve the balance of sector control load and air traffic safety. When considering the sector-delineation method, it is proposed to introduce the Voronoi diagram for sector delineation, which is a widely used spatial topology, firstly proposed by the Dutch meteorologist [PERSON], and a spatial partitioning technique that regularly divides the plane [12; 13].