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Multi-layer Point Merge System for dynamically controlling arrivals on parallel runways

机译:多层点合并系统,用于动态控制平行跑道上的到达

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In order to efficiently and robustly land more aircraft on two parallel runways, search the conflict-free and less-delay reroute for arrival aircraft, we plan to control arrival aircraft with a novel trajectory operation model named Multi-layer Point Merge System (ML-PM). In this paper, firstly the notional example of ML-PM system is introduced, the characteristics of its horizontal and vertical profiles are described. Secondly, according to the availabilities on two parallel runways, the positions of aircraft on sequencing legs, a trajectory reroute model is built. After that, the geometric relations for conflict detection in merging zones are analyzed in details. Furthermore, two tests with runway re-assignment on and off are compared to study the performances of proposed ML-PM system, the numerical results have shown that: 1) both tests could generate conflict-free trajectories, 2) average delay, average landing interval, and makes-pan could be reduced by runway re-assignment. The relative improvement for average delay is 36.36%, for make-span and average landing interval is 1.35% and 1.36% respectively. However, the average flight time, flight distance, fuel consumption and CO2 emission will increase due to runway re-assignment, the relative increases are 13.49%, 1.11%, 13.49% and 13.49%, respectively. After that, a detailed study about the runway assignment is done, the changes of different indicators are analyzed. Finally, the conclusion is made, ML-PM system shows a very positive ability to dynamically control arrival flows to land on parallel runways.
机译:为了有效地,稳健地将更多飞机降落在两条平行跑道上,搜索到达飞机的无冲突且延误较少的路线,我们计划使用一种名为多层点合并系统(ML-下午)。在本文中,首先介绍了ML-PM系统的概念示例,并描述了其水平和垂直轮廓的特征。其次,根据两条平行跑道上的空缺情况,确定飞机在排序腿上的位置,建立了航迹改航模型。之后,详细分析了合并区域冲突检测的几何关系。此外,比较了两个跑道重新分配的试验,以研究拟议的ML-PM系统的性能,数值结果表明:1)两种试验均可以产生无冲突的轨迹,2)平均延迟,平均着陆间隔,并且可以通过重新分配跑道来减少制造跨度。平均延误的相对改善为36.36%,制造跨度和平均降落间隔分别为1.35%和1.36%。然而,由于重新分配跑道,平均飞行时间,飞行距离,燃油消耗和CO2排放将增加,相对增加分别为13.49%,1.11%,13.49%和13.49%。之后,对跑道分配进行了详细的研究,分析了不同指标的变化。最后,得出的结论是,ML-PM系统显示出非常积极的能力来动态控制降落在平行跑道上的到达流。

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