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摘要: 提出了空域和流量协同管理概念, 综合利用地面等待、动态航路、条件航路等多种管理手段, 建立了以最小运行成本为目标的数学模型, 同时在模型中引入了动态航路、条件航路的开放成本, 以更好地体现流量与容量之间相互协同优化关系, 最后通过实例对模型进行了验证。计算结果表明: 利用空域和流量协同运行管理模型制定的优化策略后, 总的航班运行成本比优化前减少了8 205美元, 成本波动幅度大大减小, 因此, 该协同管理策略可缩短航班延误时间, 降低航空公司的成本。Abstract: A theoretics of collaborative management for airspace and traffic flow was proposed, several management resorts were used such as ground holding, dynamic route and conditional route, and a methematical model was set up whose objective was based on the minimum cost of operation. The costs of opening conditional route and dynamic route were introduced in the model to reflect the relationship between traffic flow and capacity, and the model was tested by an example. Experimental result shows that the general flight cost decreases by 8 205 dollars, and its amplitude becomes flat after using collaborative management strategy for airspace and traffic flow, so the strategy can cut down delays, and reduce the expense of airline company. 1 tab, 4 figs, 10 refs.
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Key words:
- air traffic flow /
- airspace /
- collaborative management /
- dynamic route /
- conditional route
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表 1 优化前与优化后的结果对比
Table 1. Comparison before and after optimizations
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[1] EUROCONTROL. Guidance document for the implementation of the concept of the flexible use of airspace[R]. Brussels: European Organisation for the Safety of Air Navigation, 2003. [2] EUROCONTROL. Air traffic flow and capacity management evolution plan for the ECAC states[R]. Brussels: European Organisation for the Safety of Air Navigation, 2004. [3] ZHANG Xue-jun, ZHOU Yan, LIU Bo, et al. The air traffic flow management with dynamic capacity and co-evolutionary genetic algorithm[C]∥ University of Washington. Intelligent Transportation Systems Conference. Washington DC: Concentration Banking Info, 2007: 580-585. [4] ALIPIO J, CASTRO P, KAING H, et al. Dynamic airspace super sectors(DASS)as high-density highways in the sky for a new US air traffic management system[C]∥ George Mason University. Digital Avionics Systems Conference. Fairfax: AIAA/IEEE, 2003: 1-10. [5] HALL W D. Dynamic collaborative decisionmaking in air traffic flow management[D]. Cambridge: Massachusetts Institute of Technology, 1998. [6] 张全, 胡明华. 基于协同空域的飞行流量管理[C]∥全国智能运输系统协调指导小组. 第四届全国智能交通年会. 北京: 人民交通出版社, 2008: 469-474.ZHANG Quan, HU Ming-hua. Air traffic flow management based on collaborative airspaces[C]∥ Coordination Steering Group of ITS. 4th China Annual Conference on ITS. Beijing: China Communications Press, 2008: 469-474. (in Chinese) [7] 窦荣, 胡明华, 王艳军. 基于飞行需求的航路动态管理[J]. 航空计算技术, 2008, 38(6): 25-27, 31. https://www.cnki.com.cn/Article/CJFDTOTAL-HKJJ200806008.htmDOU Rong, HU Ming-hua, WANG Yan-jun. Demand based dynamic air route management[J]. Aeronautical Computing Technique, 2008, 38(6): 25-27, 31. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HKJJ200806008.htm [8] EUROCONTROL. Air traffic flow and capacity management strategy[R]. Brussels: European Organisation for the Safety of Air Navigation, 2004. [9] MA Zheng-ping, CUI De-guang, CHENG Peng. Dynamic network flow model for short-term air traffic flow management[J]. IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, 2004, 34(3): 351-358. doi: 10.1109/TSMCA.2003.822969 [10] 徐肖豪, 李雄. 航班地面等待模型中的延误成本分析与仿真[J]. 南京航空航天大学学报, 2006, 38(1): 115-120. https://www.cnki.com.cn/Article/CJFDTOTAL-NJHK200601022.htmXU Xiao-hao, LI Xiong. Cost analysis of flight delays and simulation in ground-holding model[J]. Journal of Nanjing University of Aeronautics and Astronautics, 2006, 38(1): 115-120. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-NJHK200601022.htm -
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