Prediction and Analysis of Airport Surface Taxi Time: Classification, Features, and Methodology

Author:

Yin Jianan12ORCID,Zhang Mingwei2,Ma Yuanyuan2,Wu Wei12,Li He2,Chen Ping2

Affiliation:

1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

2. State Key Laboratory of Air Traffic Management System, Nanjing 210007, China

Abstract

Airport arrival and departure movements are characterized by high dynamism, stochasticity, and uncertainty. Therefore, it is of paramount importance to predict and analyze surface taxi time accurately and scientifically. This paper conducts a comprehensive review of existing studies on surface taxi time prediction and analysis. Firstly, the overall research framework of surface taxi time prediction and analysis is categorized from three perspectives: taxi time type, movement type, and modeling method. Then, focusing on the two means of taxi time analytical modeling and simulation modeling, the existing mainstream models and methods are categorized, and the main ideas and scope of application of the various methods are analyzed. Finally, the paper presents the future development direction of surface taxi time prediction prospects. The research results are aimed at providing basic support and methodological guidance for reducing the uncertainty in airport surface operation and enhancing the level of control and decision-making ability of airport surface operation.

Funder

National Natural Science Foundation of China

States Key Laboratory of Air Traffic Management System

Natural Science Foundation of Jiangsu Province

Publisher

MDPI AG

Reference78 articles.

1. Lian, G. (2019). Research on Aircraft Departure Dynamic Pushback Control Method Based on Predicted Taxi-Out Time, Harbin Institute of Technology.

2. Meng, J. (2016). Research on Aircraft Taxi-Out Time Prediction for A-CDM, Civil Aviation University of China.

3. Qian, J. (2019). Research on the Aircraft Pushback Time Decision Based on Machine Learning, Nanjing University of Aeronautics and Astronautics.

4. A new dynamic pushback control method for reducing fuel-burn costs: Using predicted taxi-out time;Lian;Chin. J. Aeronaut.,2019

5. Yin, M. (2018). Research on Optimization Strategy of Arport Surface Operation Based on Taxi Time Prediction, Nanjing University of Aeronautics and Astronautics.

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