Establishing the Correlation Between Complexity and Performance for Arrival Operations

Junfeng Zhang
Nanjing University of Aeronautics and Astronautics

Tong Xiang
Nanjing University of Aeronautics and Astronautics

Ming Zhou
Nanjing University of Aeronautics and Astronautics

Bin Wang
Central and Southern Regional Air Traffic Management Bureau of the Civil Aviation Administration of China

Abstract

Air traffic complexity indicators play an essential role in measuring operational performance and control-ler workload. However, current studies mainly depend on the manual scoring method to scale performance or workload. This paper focuses on arrival operations and presents a data-driven strategy to establish the correla-tion between complexity and performance to avoid the subjectivity of the currently used manual scoring method. Firstly, we present twenty-six indicators for describing air traffic complexity and two indicators for arrival op-erational performance. Secondly, the clustering method distinguishes peak and off-peak situations for arrival operation. Moreover, clustering results are compared to investigate the correlation between complexity and per-formance initially. Thirdly, the classification method is adopted to determine such correlation further. In addi-tion, we also identify the affecting factors which could influence operational performance. Finally, trajectories of arrival aircraft landing at Guangzhou Baiyun Inter-national Airport (ZGGG) are used for case validation. The results indicate that there is a strong correlation be-tween complexity and performance. The accuracy and precision of classification are approximately 90%. Fur-thermore, the number of aircraft significantly impacts the arrival operational performance within TMA.