Identification and Spatiotemporal Evolution Analysis of Air Traffic Congestion in Terminal Area

被引：0
作者：
Li S.-M. [1 ]
Wang Y.-X. [1 ]
Lei Q.-L. [2 ]
Song S.-N. [1 ]
Wang C. [1 ]
机构：
[1] College of Air Traffic Management, Civil Aviation University of China, Tianjin
[2] Low-altitude Flight Service Center, Zhejiang Provincial General Aviation Industry Development Cooperation, Hangzhou
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2023年 / 23卷 / 06期
基金：
中国国家自然科学基金;
关键词：
air transportation; identification; Kernel density estimation; spatiotemporal evolution; traffic congestion;
D O I：
10.16097/j.cnki.1009-6744.2023.06.013
中图分类号：
学科分类号：
摘要：
The identification of air traffic congestion in terminal areas has traditionally relied on the subjective judgment of air traffic controllers, lacking a scientific foundation to understand the evolution of congestion. This has often led to inaccuracies in congestion assessment. To enhance the accuracy of congestion assessment by controllers, this study proposes a methodology for identifying air traffic congestion based on Kernel density estimation and the traffic flow fundamental diagram, and investigates the spatiotemporal evolution characteristics of air traffic congestion. Considering the characteristics of air traffic control behavior and aircraft trajectories, a parameter identification method is proposed for determining air traffic flow parameters based on the fundamental diagram theory. By combining traffic flow parameter data with air traffic control experiences, a congestion recognition method is developed using Gaussian Kernel density estimation. The effectiveness of the proposed method is demonstrated using data from the Beijing terminal area. The results indicate that the relative speed thresholds for dividing traffic states are 6.5 km · min- 1 and 9.8 km · min-1. In congested states, controllers exhibit more pronounced radar guidance behavior, and flights have longer durations, greater distances, and more turns, reflecting increased traffic complexity. The spatiotemporal analysis of air traffic congestion in the Beijing terminal area reveals a significant imbalance in congestion distribution. Congestion periods are mainly observed around 9:00 am, 2:00 pm, and 7:00 pm, with the central region experiencing the highest levels of congestion. These findings contribute to improving the precision and scientific basis for controllers' understanding of congestion scenarios. © 2023 Science Press. All rights reserved.
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页码：120 / 132
页数：12
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