Terminal airspace sector capacity estimation method based on the ATC dynamical model

Abstract

Purpose – Air traffic resources mainly include two parts, namely, air traffic controller (ATC) and physical system resources, such as airspace. Reasonable assessment and effective management of ATC and airspace resources are the premise and foundation of ensuring the safety and efficiency of air traffic management systems. The previous studies focussed on subjective workload control and the statistics of control communication time; they revealed the lack of kinetic universality analyses of controlling actions. Although frequency distribution patterns were generated by controlling the timing sequence, the correlation between the controlling actions and terminal airspace (TMA) sector capacity was not revealed. The paper aims to discuss these issues. Design/methodology/approach – Thus, given the immeasurable complexity of controlling actions and statistical features of the controlling communications, a dynamical model of ATC was built in this study to identify the frequency distribution patterns generated by controlling the timing sequence. With the Directorate of Operational and Analysis Task method, TMA sector capacity was estimated through multiple linear regression analysis. Findings – With data from the Kunming sector, the power exponent was calculated as 2.55, and the mathematical expectation was determined to be 47.21 s. The correlation between controlling actions (workload) and sector capacity was obtained. Finally, the data were integrated in the verification of the model and its feasibility. Originality/value – Airspace capacity is an index to measure the ability of the airspace system to deliver services to meet the air traffic demand. A scientific and accurate forecast of airspace capacity is a foundation of the effective management and rational allocation of the airspace resources. The study is of great significance for the efficient use of airspace resources, controller resources.