Development of air-traffic simulation model

Abstract

According to several studies, the amount of airspace traffic is increasing very rapidly in recent years. Therefore, there is a rising need to assist the Airspace Traffic Controllers in monitoring the traffic flow. Though many solutions have been proposed, there has not been any application product that is recognized as the absolute solution for this problem. One possible solution is Cognitive Decision making Architecture for Dynamic Airspace Sectorization (CDAS for short), suggested by C.Wong in December 2016. The idea of this model is to generate 3D sector shapes that aim to minimize the conflicting workload between airspace traffic controllers, as well as changing the sector shapes as least as possible over time. In terms of efficiency, the model shows a competitive edge over many other existing solutions, such as split-and-merge method for sectors with heavy traffic. For the research phase of this model is almost completed using Matlab, it is important to apply this model and make it an official application product. Therefore, the aim of this project is to implement a CDAS system in Python language with desirable result and execution speed.