Latest revision as of 18:56, 28 January 2021

Abstract

This paper presents a new approach for automated merging multiple aircraft flows in a busy Terminal Maneuvering Area (TMA). This work is motivated by the current overloaded airspace in the Beijing Capital international airport, the highlighted delay in the China air transportation and the need of more efficient methods to help air traffic controllers. Present research consists of a new approach to optimize a set of aircraft planned to land at a given airport based on multi-agents technique, which is automated generating comprehensive sequencing plan and conflicts-free trajectories.The architecture of the system is based on a Point Merge (PM) route structure to enable expediting or delaying aircraft while staying on lateral navigation mode.The whole system is designed by two main models to manage the process of arriving flows: Sequencing leg and Link. And then, 4 kinds of agents are designed to support the implementation of this automated system: aircraft agent, flow manager agent, conflict detection and resolution agent and 4D trajectory planning agent. We consider the 4D trajectory-based operation situation in TMA and apply different wake turbulence constraint in these two models. Finally, aconclusion is made and future work is outlined. Refereed/Peer-reviewed

Original document

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• http://dx.doi.org/10.1016/j.proeng.2014.12.531 under the license http://creativecommons.org/licenses/by-nc-nd/4.0

• http://dx.doi.org/10.1016/j.proeng.2014.12.531 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/

• https://doi.org/10.1016/j.proeng.2014.12.531

• https://hdl.handle.net/11541.2/135053 under the license Copyright 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0

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http://dx.doi.org/10.1016/j.proeng.2014.12.531 under the license https://www.elsevier.com/tdm/userlicense/1.0/

• https://www.sciencedirect.com/science/article/pii/S1877705814036455,

https://academic.microsoft.com/#/detail/1963502022