Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (5): 738-746.doi: 10.23940/ijpe.20.05.p7.738746

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Forecasting Airport Surface Traffic Congestion based on Decision Tree

Zhaoyue Zhanga*(), An Zhanga, Cong Suna,  and Shanmei Lib   

  1. aSchool of Aeronautics, Northwestern Polytechnical University, Xi'an, 710072, China
    bCollege of Air Traffic Management, Civil Aviation University of China, Tianjin, 300300, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: Zhaoyue Zhang
  • Supported by:
    This work was supported by Research Funds for Interdisciplinary Subject, NWPU, and the National Nature Science Foundation of China (No. 71801215) .


To improve the operational efficiency of airport surfaces, this paper studies the air traffic congestion prediction of airport surfaces, demonstrates the limitations of traffic congestion prediction, and proposes a prediction method for airport surface traffic congestion based on decision tree. Firstly, the definition and measurement methods of traffic congestion in airport surfaces are promoted. Then, the key factors affecting traffic congestion are extracted, and a prediction model of traffic congestion is established. Finally, we verify the validity of the model based on actual operation data from Atlanta. The results show that the accuracy of the prediction is 70%.

Key words: air transportation, traffic congestion, decision tree, C4.5 algorithm