Devising strategies for aircraft arrival processes via distance-based queuing models

Abstract

Accommodating highly-frequented air traffic at an airport, managing aircraft arrivals is one of the most important functions in the operation. This paper introduces distance-based queuing models, which enable us to present aircraft arrival processes in accordance with the distance at the destination airport, and estimates bottlenecks and delay time in the current and future arrival traffic flows. Strategies to optimize aircraft arrival processes are discussed based on the proposed models applying for two case study airports, Tokyo International Airport and Singapore Changi International Airport. Stochastic parameters in the models are identified using large volume of flight plan and track data-sets, including actual radar data and ADS-B data. Analyzing different features of arrival process at the case study airports provides insights into arrival control strategies and contributes to establish systematic approaches for designing arrival management for long-range traffic flows.