Systems Engineering and Electronics ›› 2021, Vol. 43 ›› Issue (3): 722-730.doi: 10.12305/j.issn.1001-506X.2021.03.16

• Systems Engineering • Previous Articles     Next Articles

Modelling for airport gate operation process based on relational spatio-temporal network

Zhiwei XING1(), Hong'en LIU1(), Biao LI1,2(), Qian LUO3(), Tao WEN3(), Zhaoxin CHEN3()   

  1. 1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
    2. College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
    3. The Second Research Institute of Civil Aviation Administration of China, Chengdu 610041, China
  • Received:2020-04-12 Online:2021-03-01 Published:2021-03-16

Abstract:

In order to improve the efficiency of the airport gate operation, this paper analyzes and describes the gate operation process accurately. Based on the analysis of the operation process of the airport inbound and outbound flights, the gate operation process is abstracted as a relational spatio-temporal network, the logical relationship between the flight and the gate is described qualitatively. The gate operation information is discribed quantitatively by using the flight time window, gate location and other characteristic parameters. A quantitative description model of airport gate operation process based on relational spatio-temporal network is proposed. The proposed model is verified by the actual gate operation data of a large domestic airport hub. The results show that, the relational spatio-temporal network model conforms to the power-law distribution, 58.62% of the average node error is 0.172 4 h, the average node degree distribution is 0.666 7, and the average clustering coefficient is 0.807 5. The nodes with higher node degree distribution and clustering coefficient are the key nodes, corresponding to the key flights with greater influence. Compared with the existing models, the macro and micro feature parameters of the situation information can improve the accuracy of scene description and effectively adapt to the change of data scale.

Key words: air transportation, gate operation process, network model, information association, data driving

CLC Number: 

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