Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/146567
Title: | Devising strategies for aircraft arrival processes via distance-based queuing models | Authors: | Itoh, Eri Schultz, Michael Srinivas, Athota Duong, Vu |
Keywords: | Engineering::Aeronautical engineering::Aviation | Issue Date: | 2020 | Source: | Itoh, E., Schultz, M., Srinivas, A., & Duong, V. (2020). Devising strategies for aircraft arrival processes via distance-based queuing models. Proceedings of SESAR Innovation Days 2020, 1-8. | metadata.dc.contributor.conference: | SESAR Innovation Days 2020 | 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. | URI: | https://hdl.handle.net/10356/146567 | Schools: | School of Mechanical and Aerospace Engineering | Research Centres: | Air Traffic Management Research Institute | Rights: | © 2020 SESARJU. All rights reserved. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | ATMRI Conference Papers |
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File | Description | Size | Format | |
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Devising Strategies for Aircraft Arrival Processes via Distance-based Queuing Models.pdf | SESAR Innovation Days 2020 Conference Paper | 321.81 kB | Adobe PDF | ![]() View/Open |
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