Research On The Stochastic Evolution Of Aircraft Ground Traffic Flow In Airport

In recent years,with the rapid socio-economic development,the number of flights and passenger traffic have increased significantly.The high-density flight operations have brought huge operational pressure to the hub airport.A series of traffic problems have been developed in the airport ground traffic,and the research on the key technology of the airport real-time situation awareness system in the big data environment has become a new trend in the research and development of the airport ground traffic.How to meet the conditions of the airport,measuring the aircraft operation congestion conditions with the objective of recognizing and recognizing the ground traffic flow status,so as to adjust the management in time,relieve the operating pressure of the airport traffic,and optimize the complex state of the airport traffic,and effectively improve the airport capacity and operation efficiency.This paper relies on the National Natural Science Foundation of China,and based on the theory of spatio-temporal evolution,studies the moderated probability model of airport ground aircraft.The ground traffic flow characteristics of the airport are analyzed from five aspects including aircraft speed,flow,density,milestone time interval,and aircraft interarrival time,and the airport traffic status is determined by the index of detention,saturation and maximum traffic volume.Taking the aircraft arrival time as an indirect metric,the self-organizing neural network method is used to identify the airport ground traffic flow status and the thresholds for dividing the various states are obtained.The data mining technology(Data Mining,DM)was used to process and analyze the airport operational indicators and related basic data,and the statistical distribution characteristics of the airport operating parameters were obtained.Then the correlation between airport operational indexes was obtained,and the stochastic evolution mechanism of the aircraft ground traffic flow was further summarized and analyzed.Based on the classical space-time evolution idea,considering the macro-impact and micro-impact of the aircraft interarrival time distribution on the operation of the airport,the influence factors such as the aircraft interarrival time distribution,acceleration/deceleration status,aircraft type,traffic environment,safety wake interval,speed difference,the pilot’s self reaction and the controller instruction are studied and analyzed.Then a moderated probability model based on the aircraft interarrival time and its improved model were constructed.Taking a domestic hub airport as an example,this paper simulates the moderated probability model formula by assuming the parameters and conditions of the airport,and then uses the fuzzy logic toolbox(Fuzzy Logic)in Matlab software to simulate the improved model.The simulation results are obtained and analyzed,then verify the effectiveness of the model.The research results can provide theoretical support for the airport operations management department to deeply analyze the operational rule s of aircraft ground traffic flow,and lay the foundation for identifying and predicting the operational status of ground traffic flow at the airport.