Data-Driven Analysis of Final Separation Between Successive Landing Aircraft

被引:0
|
作者
Gu, Yushi [1 ]
Zhang, Junfeng [1 ]
Zhou, Ming [1 ]
Wang, Bin [2 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Dept Air Traff, Nanjing, Jiangsu, Peoples R China
[2] Civil Aviat Adm China, Dept Air Traff Control, Cent & Southern Reg Air Traff Management Bur, Guangzhou, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
aviation; airfield and airspace capacity and delay; advanced analytics and data science; air traffic control; terminal airspace; KERNEL DENSITY-ESTIMATION;
D O I
10.1177/03611981221082559
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In recent years, with the development of air traffic in China, airspace resources cannot keep up with the growth of traffic demand. Therefore, enhancement of runway capacity by reducing wake turbulence separation has become a research hotspot in the air traffic management field. As there are gaps between theory and practice, many scholars are doing practical operation-based evaluations, focusing on the final separations (intervals) between two successive aircraft. However, few studies have considered the impact of different controllers and the evolution of separations over time. This paper is dedicated to analyzing the final separations between leading and trailing aircraft based on the aircraft trajectories. This study carries out the final separation analysis from static and dynamic perspectives, considering the final separations under different traffic pressures, by different controllers, and in the different segregated and mixed operations. Guangzhou Baiyun International Airport (ZGGG) is taken as an experimental case. The results indicate that the final separation buffer decreases over time. Moreover, under the same high traffic pressures, the final separations could be used to compare the effectiveness of different controllers.
引用
收藏
页码:786 / 798
页数:13
相关论文
共 50 条
  • [1] Data-Driven Modeling of Aircraft Midair Separation Violation
    Stover, Oliver
    Mahadevan, Sankaran
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (09) : 15005 - 15014
  • [2] Data-Driven Pilot Behavior Modeling Applied to an Aircraft Offset Landing Task
    Turetta, Felipe M. S.
    Hultmann Ayala, Helon Vicente
    Trabasso, Luis G.
    Coelho, Leandro S.
    Alfredson, Jens
    ADVANCES IN HUMAN ASPECTS OF TRANSPORTATION, 2018, 597 : 117 - 127
  • [3] Data-Driven Robust Model Predictive Control of Tiltwing Vertical Takeoff and Landing Aircraft
    Doff-Sotta, Martin
    Cannon, Mark
    Bacic, Marko
    JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2025, 48 (01) : 203 - 211
  • [4] Analyze Potential of Dynamic Aircraft Wake Separation via Data-driven Aircraft Wake Region Detection
    Chu, Nana
    Kam, K.
    Ng, H.
    Liu, Ye
    AIAA AVIATION FORUM AND ASCEND 2024, 2024,
  • [5] Efficient multidisciplinary modeling of aircraft undercarriage landing gear using data-driven Naïve Bayes and finite element analysis
    Al-Haddad, Luttfi A.
    Mahdi, Nibras M.
    MULTISCALE AND MULTIDISCIPLINARY MODELING EXPERIMENTS AND DESIGN, 2024, 7 (04) : 3187 - 3199
  • [6] Data-Driven Surface Traversability Analysis for Mars 2020 Landing Site Selection
    Ono, Masahiro
    Rothrock, Brandon
    Almeida, Eduardo
    Ansar, Adnan
    Otero, Richard
    Huertas, Andres
    Heverly, Matthew
    2016 IEEE AEROSPACE CONFERENCE, 2016,
  • [7] A data-driven analysis of short and long laminar separation bubbles
    Dellacasagrande, M.
    Lengani, D.
    Simoni, D.
    Yarusevych, S.
    JOURNAL OF FLUID MECHANICS, 2023, 976
  • [8] Forecasting Risk of Service Failures Between Successive Rail Inspections: A Data-Driven Approach
    Faeze Ghofrani
    Naresh Kumar Chava
    Qing He
    Journal of Big Data Analytics in Transportation, 2020, 2 (1): : 17 - 31
  • [9] Data-Driven Long-Landing Event Detection and Interpretability Analysis in Civil Aviation
    Yang, Xiong
    Ren, Jin
    Li, Junchen
    Zhang, Haigang
    Yang, Jinfeng
    IEEE ACCESS, 2022, 10 : 64257 - 64269
  • [10] Data-Driven Aircraft Estimated Time of Arrival Prediction
    Kern, Christian Strottmann
    de Medeiros, Ivo Paixao
    Yoneyama, Takashi
    2015 9TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON), 2015, : 727 - 733