柔性空域结构中CDO轨迹的多目标优化

Wenbo Li, Lei Yang, Yutong Chen, Haoran Zhang, Zheng Zhao
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引用次数: 0

摘要

连续下降操作(CDO)可以通过使到达的飞机在巡航高度保持更长的时间,然后以接近怠速推力连续下降,没有水平飞行段,从而显著减少燃油消耗和噪音影响。设计简洁、高效、灵活的到达路线,实现高水平自动化生成无冲突、经济的轨迹,是高密度交通场景下全面实现CDO的基石。在本研究中,受点合并(PM)的启发,我们设计了终端区的倒皇冠形到达空域(ICSAA)及其操作流程,以提供全方位的CDO。为了高效生成即将到来飞机的备选无冲突最优轨迹,建立了采用精英策略非支配排序遗传算法求解的多目标轨迹优化模型(NSGA-Ⅱ)。在单架飞机和高度复杂的多架飞机场景下,实现了最小油耗和行程时间的最优化解决方案。结果验证了该算法的有效性和可接受的计算成本(在极高密度场景下小于5min)。此外,公务员制度协协似乎是一个很有前途的结构,由于其业务灵活性和能力,可以促进CDO的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Objective Optimization of CDO Trajectory in a Flexible Airspace Structure
Continuous Descent Operations (CDO) can significantly reduce fuel burn and noise impact by keeping arriving aircraft at their cruise altitude for longer and then having a continuous descent at near-idle thrust with no level-flight segments. Designing concise, efficient and flexible arrival routes for high-level automation in generating conflict-free and economical trajectories, is a cornerstone for fully achieving CDO in high-density traffic scenarios. In this research, inspired by the Point Merge (PM), we design the Inverted Crown-Shaped Arrival Airspace (ICSAA) and its operational procedures in the terminal area to deliver Omni-directional CDO. In order to generate alternative optimal conflict-free trajectories for upcoming aircraft in an efficient manner, we established a multi-objective trajectory optimization model solved by Non-dominated Sorting Genetic Algorithm with Elitist Strategy (NSGA-Ⅱ). The Parote solutions of minimal fuel consumption and trip time were achieved in single aircraft and highly complex multi-aircraft scenarios. Results validated the effectiveness and acceptable computational cost (less than 5min in extremely high-density scenarios) of proposed algorithm. In addition, ICSAA seems to be a promising structure that could promote the application of CDO for its operational flexibility and capacity.
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