Abstract
This paper proposes data-driven queuing models and solutions to reduce arrival time delays originating from aircraft arrival processing bottlenecks at Tokyo International Airport. A data-driven analysis was conducted using two years of radar tracks and flight plans from 2016 and 2017. This analysis helps not only to understand the bottlenecks and operational strategies of air traffic controllers, but also to develop mathematical models to predict arrival delays resulting from increased, future aircraft traffic. The queue-based modeling approach suggests that one potential solution is to expand the realization of time-based operations, efficiently shifting from traffic flow control to time-based arrival management. Furthermore, the proposed approach estimates the most effective range of transition points, which is a key requirement for designing extended arrival management systems while offering automation support to air traffic controllers.
Highlights
Global air traffic passenger demand is expected to increase 250% in the 20 years [1].To accommodate such air traffic growth, the air traffic management system strives to provide the airports and the sectors the traffic capacities needed to ensure arrival traffic punctuality, while having ecologically and economically friendly flights
A significant aircraft delay increase is projected in the airspace between the circles of radii 30 and 50 nautical miles (NM) radius if the current service levels are maintained under future increases in arrival traffic volume
To address the first question, our G/G/c queuing model for arrival traffic, with model parameters derived by analyzing actual flight data, yielded the following preliminary results: decreasing inter-arrival time is one of the most powerful solutions for reducing arrival delay times occurring in airspace bottleneck areas, i = 3 and i = 4
Summary
Global air traffic passenger demand is expected to increase 250% in the 20 years [1]. To analyze bottlenecks that future arrival traffic flow may bring, mathematical models are useful to predict causes and provide solutions for reducing arrival delay times In this light, we apply queue-based modeling for arrivals at a single airport and discuss new procedures and technologies that support air traffic controllers in handling arrival traffic at congested airports. The present paper proposes a queue-based modeling approach to estimating flight arrival delays and the impact of decreasing flight separation in the context of E-AMAN. In this context, aircraft delay time is estimated by means of the proposed queue-based approach.
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