Computer Science ›› 2020, Vol. 47 ›› Issue (2): 306-312.doi: 10.11896/jsjkx.181202400

• Information Security • Previous Articles     Next Articles

Optimization of Aircraft Taxiing Strategy Based on Multi-agent

ZHANG Hong-ying1,SHEN Rong-miao1,LUO Qian2   

  1. (College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China)1;
    (The Second Research Institute of Civil Aviation Administration of China,Chengdu 610041,China)2
  • Received:2018-12-24 Online:2020-02-15 Published:2020-03-18
  • About author:ZHANG Hong-ying,born in 1978,Ph.D,professor,postgraduate supervisor.Her main research interests include airport intelligence and automation technology.
  • Supported by:
    This work was supported by the Key Projects of the Civil Aviation Joint Fund of the National Natural Science Foundation of China (U1533203).

Abstract: The rapid development of civil aviation has led to the shortage of capacity in many airports.In order to alleviate the current situation of large airports,the problem of aircraft taxiing strategy optimization was studied.Taxiing path optimization is the optimal management of the distance between the runway and the gate of the arriving and departing flights according to the airport resource information and the ground operation management system during a specific time period.Through in-depth analysis the structure of the airport ground network,comprehensive consideration of factors such as taxiing conflict and ground operation rules,a multi-agent taxiing strategy optimization method is proposed to improve the utilization rate of airport resources.The aircraft taxiing strategy optimization model is established,based on the concept of ground network link structure.Combined with the basic theory of multi-agent,the selection probability function of runway exit and the multi-agent path optimization algorithm are designed to seek the optimal taxiing path of aircraft.The aircraft taxiing strategy experiment is carried out,based on the actualsituation of a large domestic airport.The results show that the optimization effect of multi-agent taxiing strategy is more signifi-cant compared with the previous algorithms.Set the speed at the runway entrance and the minimum interval distance of the aircraft at the same intersection.the aircraft can effectively adjust the original taxiing path and shorten the taxiing time on the airport scene through the interaction of the runway exit selection and the interactive negotiation among agents.The total taxiing distance of the aircraft,the density and the average waiting time of the aircraft on the taxiway are significantly better than the contrast optimization algorithm,and the taxiway resource allocation is more reasonable compared with the shortest path algorithm.And the average waiting time of aircraft at the node is reduced by 8.26%.Alleviate the current situation of airport traffic congestion and improve the operating efficiency of scene,which is of great significance for reducing aircraft delay and airport operation safety.

Key words: Large airport, Multi-agent, Network model, Probability function, Taxiing path optimization

CLC Number: 

  • TP391.9
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