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
  • [31] A model of fake data in data-driven analysis
    Li, Xiaofan
    Whinston, Andrew B.
    JOURNAL OF MACHINE LEARNING RESEARCH, 2020, 21
  • [32] DATA ANALYSIS OF COMMERCIAL AIRCRAFT LANDING ON THE RUNWAY AIRPORTS IN INDONESIA
    Passarella, Rossi
    Nurmaini, Siti
    Rachmatullah, Muhammad Naufal
    Arsalan, Osvari
    Kurniati, Rizki
    Aditya, Aditya
    Afriansyah, Indra Gifari
    Fathan, Rifqi
    Yousnaidi, Rani Silvani
    Veny, Harumi
    SCIENTIFIC JOURNAL OF SILESIAN UNIVERSITY OF TECHNOLOGY-SERIES TRANSPORT, 2023, 120 : 233 - 247
  • [33] Data-Driven Analysis of the Interaction Between Storage Ownership and Market Behavior
    Wu, Zhaoyuan
    Chen, Zili
    Ren, Yi
    Chen, Lin
    Guo, Zun
    Zhou, Ming
    IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2025, 61 (01) : 1735 - 1747
  • [34] Data-driven analysis of influence between radiologists for diagnosis of breast lesions
    Chao Fu
    Dongyue Wang
    Wenjun Chang
    Annals of Operations Research, 2023, 328 : 419 - 449
  • [35] Data-driven analysis of influence between radiologists for diagnosis of breast lesions
    Fu, Chao
    Wang, Dongyue
    Chang, Wenjun
    ANNALS OF OPERATIONS RESEARCH, 2023, 328 (01) : 419 - 449
  • [36] Data-Driven Hazard Avoidance Landing of Parafoil: A Deep Reinforcement Learning Approach
    Park, Junwoo
    Bang, Hyochoong
    JOURNAL OF AEROSPACE INFORMATION SYSTEMS, 2024, 21 (01): : 58 - 74
  • [37] Data-driven Online Motion Analysis
    Huang, Tianyu
    Yang, Jia
    Li, Lijie
    2009 IEEE 10TH INTERNATIONAL CONFERENCE ON COMPUTER-AIDED INDUSTRIAL DESIGN & CONCEPTUAL DESIGN, VOLS 1-3: E-BUSINESS, CREATIVE DESIGN, MANUFACTURING - CAID&CD'2009, 2009, : 1407 - 1411
  • [38] Data-driven Forest Fire analysis
    Gao, Jerry
    Shalini, Kshama
    Gaur, Navit
    Guan, Xuan
    Chen, Sean
    Hong, Jesse
    Mahmoud, Medhat
    2017 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTED, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI), 2017,
  • [39] Data-driven analysis in drug discovery
    Kenakin, Terry
    JOURNAL OF RECEPTORS AND SIGNAL TRANSDUCTION, 2006, 26 (04) : 299 - 327
  • [40] Data-Driven Fault Detection in Aircraft Engines With Noisy Sensor Measurements
    Sarkar, Soumik
    Jin, Xin
    Ray, Asok
    JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME, 2011, 133 (08):