Air traffic management;
Sequence of arrival flights;
Point merge;
Closely spaced parallel runway;
Paired approach;
Genetic algorithm;
AIRCRAFT;
D O I:
10.1016/j.jtte.2023.09.001
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
The paired approach is a kind of efficiency approach to closely spaced parallel runways (CSPRs), and the point merge system has the powerful interval management function, which is effective to realize the converge of traffic flows from different approach directions. In order to improve the operation efficiency of the airport terminal area, a model of paired approach sequencing based on point merge is proposed to investigate the problem of increasing the operation capacity of the closely spaced parallel runways. Taking the minimum average flight delay time as the objective, the flight distance on sequencing legs, wake turbulence separation and paired approach safety separation as constraints, the genetic algorithm is used to optimize the paired approach sequencing of arrival flights. Taking the closely parallel runways of Shanghai Hongqiao International Airport run south as an example, the point merge program is designed and the effect of model was analyzed. The results show that after optimization, the average delay time and average landing time are reduced by 40.6% and 51.8% respectively, the capacity of the closely spaced parallel runways are 1.1 times higher than the actual, the flight uptime rate can reach 100%. It is concluded that the proposed model is feasible, which can effectively reduce delay times and alleviate congestion in terminal areas. (c) 2023 Periodical Offices of Chang'an University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
机构:
Univ Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
Univ Calif San Francisco, Dept Biochem & Biophys, San Francisco, CA 94158 USAUniv Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
Arigovindan, Muthuvel
Shaevitz, Joshua
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机构:
Princeton Univ, Dept Phys, Princeton, NJ 08544 USA
Princeton Univ, Lewis Sigler Inst Integrat Genom, Princeton, NJ 08544 USAUniv Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
Shaevitz, Joshua
McGowan, John
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
Univ Calif San Francisco, Dept Biochem & Biophys, San Francisco, CA 94158 USAUniv Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
McGowan, John
Sedat, John W.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
Univ Calif San Francisco, Dept Biochem & Biophys, San Francisco, CA 94158 USAUniv Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
Sedat, John W.
Agard, David A.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA
Univ Calif San Francisco, Dept Biochem & Biophys, San Francisco, CA 94158 USA
Princeton Univ, Howard Hughes Med Inst, Princeton, NJ 08544 USAUniv Calif San Francisco, Keck Adv Microscopy Ctr, San Francisco, CA 94158 USA