Characteristics of Air Traffic Flow in Terminal Airspace: A Multiplex Recurrence Network Analysis

• Published in: IEEE transactions on intelligent transportation systems 2024-10, Vol.25 (10), p.14803-14815
• Main Authors: Jiang, Furong, Zhang, Zhaoning
• Format: Article
• Language: English
• Subjects: Air traffic control; Air traffic flow; Airports; Clustering algorithms; density-based spatial clustering of applications with noise (DBSCAN); Fluctuations; multiplex recurrence network (MRN); Multiplexing; terminal airspace; Time series analysis; Trajectory
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2024.3396627

We introduce a novel data analytics framework, using a multiplex recurrence network (MRN) to analyze flight tracking flow fluctuations in multi-airport terminal areas, with a case study on Shanghai's Pudong (PVG) and Hongqiao (SHA) airports. It fills the gap in existing research by focusing on daily traffic flow fluctuations and exploring the operational dynamics within multi-airport systems. The MRN method effectively captures the synchronicity and similarity of traffic flows, offering novel insights into the management of airport terminal areas. Empirical analysis based on actual flight operation data validates the MRN's efficacy, revealing distinct patterns of traffic flow synchronicity across four different scenarios-All Arrivals of PVG and SHA (AllArr), All Departures of PVG and SHA (AllDep), All Arrivals and Departures of PVG (AllPVG), and All Arrivals and Departures of SHA (AllSHA). These findings highlight the potential for enhancing operational efficiency by improving the synchronicity of traffic flows, especially during peak periods. This novel framework for understanding and optimizing air traffic flows in terminal areas offers both academic insights and practical implications for air traffic management, and provides a foundation for targeted interventions to improve the efficiency of airport operations in multi-airport systems.