Abstract

International audience; 4D Trajectory optimization in dense terminal control area is one of the most challenging problems in air traffic management research. In order to efficiently and robustly land more aircraft at Beijing Capital International Airport (BCIA), one of the busiest airport in the world, a novel trajectory operation model is proposed, i.e. Multi-layer Point Merge (ML-PM) based Autonomous Arrival Management System. This paper aims at the evaluation of its potential operational benefits in terms of flight efficiency and runway throughput. Horizontal and Vertical profiles of ML-PM route network are introduced, the objective and constraints of this optimizing mathematical model are analyzed, especially the speed change profile and the conflict detection mode for merging zone. Then a case study is made by simulating arrival flows under three different operational modes: baseline, traditional point merge, and the ML-PM. Finally, the results show that rational arrival sequence and conflict-free trajectories are generated in ML-PM system, the benefits gained are very positive. Comparing with baseline and the traditional point merge system, ML-PM system shows good performance on flight time, fuel consumption, CO2 emission. The saving of fuel with ML-PM system is expected around 26838 Yuan per hour at BCIA compared with baseline scenario by numerical simulation. Furthermore, more flexible sequence position shift and continuous descent are possible in ML-PM system, and it is capable to handle the high-density operation environment.


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The different versions of the original document can be found in:

https://hal-enac.archives-ouvertes.fr/hal-01355018/document,
https://hal-enac.archives-ouvertes.fr/hal-01355018/file/ICRAT16_template_final_version__2016_06_20.pdf
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Published on 01/01/2016

Volume 2016, 2016
Licence: CC BY-NC-SA license

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