Research On Xi'an Terminal Sector Dynamic Optimization Base On Controller Workload

With the rapid development of aviation in recent years,air traffic flow rapid growth,resulting in the contradiction between the airspace resources and the increasing of air traffic flow.As the transition space between the airport and the route,the terminal area is the most complex in the air traffic,which is the choke point to limit the whole space capacity.Owing to the terminal sector is unreasonable or the original sector can't adapt to the current air traffic flow,On the one hand,it leads to imbalanced control load among sectors,which causes a short board effect and severely restricts the capacity of the entire terminal area;On the other hand,there is a lack of rationality in the combination of sectors,reducing utilization of airspace and work efficiency.Therefore,the dynamic optimization of the sector in the terminal area makes the load of the sector controllers relatively balanced and the sector combination more scientific and reasonable.It is significant for improving the capacity of the entire terminal area and utilization of the airspace,and ensuring flight safety.The paper takes Xi'an terminal area as an example,firstly,introducing the basic theory of sector partitioning and Voronoi diagram.Secondly,considering the influence of space complexity on the controller load,and constructing the computational model,combined with the DOROTASK method,proposes a method of controller load quantification based on the dynamic weighting of space complexity,and explaining the steps and methods of genetic algorithms in sector optimization.Finally,based on present situation of the Xi'an terminal area,analysised the traffic flow in the terminal area of Xi'an and the control tasks of the controllers in order to quantify the controller load.According to the principle of the control load balance,achieved the optimization and combination of sectors in the Xi'an terminal area by using the genetic algorithm tool in MATLAB.Comparing the fore and aft changes in capacity and controller load,the optimization effect was verified.