| 基于空中交通密度的进场航班动态协同排序方法 |
| |
| 引用本文： | 刘继新,江灏,董欣放,兰思洁,王浩哲. 基于空中交通密度的进场航班动态协同排序方法[J]. 航空学报, 2020, 41(7): 323717-323717. DOI: 10.7527/S1000-6893.2020.23717 |
| |
| 作者姓名： | 刘继新 江灏 董欣放 兰思洁 王浩哲 |
| |
| 作者单位： | 1. 南京航空航天大学 民航学院, 南京 211106;2. 国家空管飞行流量管理技术重点实验室, 南京 211106;3. 中国民用航空华北地区空中交通管理局天津分局, 天津 300300 |
| |
| 摘 要： | 为适应协同决策（CDM）需要,考虑空管、航空公司和机场的诉求,对进场航班动态协同排序问题进行了系统的研究。设计了一种进场航班动态排序方法,提出了一种时隙交换方法,建立了基于空中交通密度的进场航班协同排序模型,设计了精英保留的遗传算法和带精英策略的快速非支配排序遗传算法以求解所建模型,寻求进场航班动态协同排序的最优解。仿真结果表明,较基于滚动时域控制（RHC）方法,动态协同方法所得结果与排序开始时间无关,所需排序次数平均减少26.4%,且排序效率更高。较先到先服务（FCFS）方法,动态协同方法在高密度条件下各排序阶段最后一个进场航班的落地时间平均提前199.8 s;中密度条件下各排序阶段航班延误总时间平均减少29.9%,航班延误均衡性平均提高34.4%;低密度条件在航班正常率及航班延误公平性得到保证的前提下,满足时隙交换规则的排序阶段均增加了1种进场航班排序模式。所提方法可对进场航班进行优化排序,显著提高跑道容量,有效提升航班延误均衡性和航班延误公平性,契合协同决策理念,可实现三方协同排序。
|
| 关 键 词： | 空中交通管制 协同决策 进场排序 时隙交换 多目标优化 遗传算法 |
| 收稿时间： | 2019-12-08 |
| 修稿时间： | 2020-02-07 |
Dynamic collaborative sequencing method for arrival flights based on air traffic density |
| |
| LIU Jixin,JIANG Hao,DONG Xinfang,LAN Sijie,WANG Haozhe. Dynamic collaborative sequencing method for arrival flights based on air traffic density[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(7): 323717-323717. DOI: 10.7527/S1000-6893.2020.23717 |
| |
| Authors: | LIU Jixin JIANG Hao DONG Xinfang LAN Sijie WANG Haozhe |
| |
| Affiliation: | 1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;2. National Key Laboratory of Air Traffic Flow Management, Nanjing 211106, China;3. Air Traffic Management Bureau of Tianjin Civil Aviation Administration, Tianjin 300300, China |
| |
| Abstract: | To meet the needs of Collaborative Decision Making (CDM), dynamic collaborative sequencing of arrival flights is systematically studied, considering the demands of air traffic control units, airlines and airports. A dynamic sequencing method for arrival flights is designed, a slot exchange method is proposed, and a collaborative sequencing model based on air traffic density is built. A genetic algorithm with the elitist reservation and a fast non-dominated sorting genetic algorithm with the elitist strategy are designed to achieve the optimal solution of dynamic collaborative sequencing of arrival flights. Compared with those of the Receding Horizon Control (RHC) method, the results of the dynamic collaborative method are independent of the start time of sequencing with the required sequencing times reduced by 26.4% on average, leading to higher sequencing efficiency. Compared with that of the First Come First Service (FCFS) method, under the condition of high density, the landing time of the last arrival flight in each sequencing stage is 199.8 s ahead of schedule on average with the dynamic collaboration method; under the condition of medium density, the total flight delay of each sequencing stage is reduced by 29.9% on average, while the flight delay equilibrium is increased by 34.4% on average; under the condition of low density, with the premise that the punctuality rate of arrival flights and the fairness of flight delays are guaranteed, one sequencing mode of arrival flights is added if the sequencing stage satisfies the slot exchange rules. The proposed method can optimize the sequencing of arrival flights, significantly enhancing the runway capacity and effectively improving the flight delay equilibrium and fairness. In line with the concept of collaborative decision making, this method can achieve collaborative sequencing of ATC, airlines and airports. |
| |
| Keywords: | air traffic control collaborative decision making arrival sequencing slot exchange multi-objective optimization genetic algorithm |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《航空学报》浏览原始摘要信息 |
|
点击此处可从《航空学报》下载全文 |
|
