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基于多Agent技术的飞机协同飞行建模与仿真

叶博嘉 胡明华 田勇

叶博嘉, 胡明华, 田勇. 基于多Agent技术的飞机协同飞行建模与仿真[J]. 交通运输工程学报, 2013, 13(6): 90-98.
引用本文: 叶博嘉, 胡明华, 田勇. 基于多Agent技术的飞机协同飞行建模与仿真[J]. 交通运输工程学报, 2013, 13(6): 90-98.
YE Bo-jia, HU Ming-hua, TIAN Yong. Modeling and simulation of collaborative flight based on multi-agent technique[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 90-98.
Citation: YE Bo-jia, HU Ming-hua, TIAN Yong. Modeling and simulation of collaborative flight based on multi-agent technique[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 90-98.

基于多Agent技术的飞机协同飞行建模与仿真

基金项目: 

国家自然科学基金项目 61104159

详细信息
    作者简介:

    叶博嘉(1983-), 男, 江苏南京人, 南京航空航天大学工学博士研究生, 从事空中交通管理研究

    胡明华(1962-), 男, 湖南益阳人, 南京航空航天大学教授

  • 中图分类号: V355.2

Modeling and simulation of collaborative flight based on multi-agent technique

More Information
  • 摘要: 应用多Agent建模与仿真技术, 研究了飞机Agent在空中走廊中的飞行风险。根据空中走廊内飞机Agent的飞行目标、主要功能和内部结构, 分析了飞机Agent的推理规则和协同状态, 提出了协同飞行的交互结构, 利用混合式仿真方法进行仿真试验。仿真结果表明: 当大型飞机的最大、最小巡航速度分别为880、620km·h-1, 中型飞机的最大、最小巡航速度分别为790、525km·h-1, 且2种机型加速度的最大值、最小值均分别为0.608、-0.780m·s-2时, 空中走廊中飞机的飞行状态可以划分为4种典型工况; 第1种工况下, 飞机的速度始终为745.17km·h-1, 总飞行时间为708s;第2种工况下, 飞机根据前方飞机调整自身飞行速度, 飞机初始速度为658km·h-1, 最大速度为778km·h-1, 总飞行时间为648s;第3种工况下, 飞机为避免飞行冲突变更空中走廊中的飞行线路, 总飞行时间为744s;第4种工况下, 飞机因安全问题脱离空中走廊, 总飞行时间为66s。提出的模型可满足实际要求。

     

  • 图  1  空中走廊结构

    Figure  1.  Air corridor structure

    图  2  内部结构

    Figure  2.  Interior structure

    图  3  交互结构

    Figure  3.  Interactive structure

    图  4  不同间隔的关系

    Figure  4.  Relations among different spacing distances

    图  5  算法流程

    Figure  5.  Algorithm flow

    图  6  工况1下的间隔距离

    Figure  6.  Spacing distance under condition 1

    图  7  工况1下的协同状态

    Figure  7.  Collaborative state under condition 1

    图  8  工况2下的飞机加速度

    Figure  8.  Aircraft acceleration under condition 2

    图  9  工况2下的飞机速度

    Figure  9.  Aircraft speed under condition 2

    图  10  工况2下的间隔距离

    Figure  10.  Spacing distance under condition 2

    图  11  工况2下的协同状态

    Figure  11.  Collaborative state under condition 2

    图  12  工况3下的飞机加速度

    Figure  12.  Aircraft acceleration under condition 3

    图  13  工况3下的飞机速度

    Figure  13.  Aircraft speed under condition 3

    图  14  工况3下的间隔距离

    Figure  14.  Spacing distance under condition 3

    图  15  工况3下的协同状态

    Figure  15.  Collaborative state under condition 3

    图  16  工况4下的飞机加速度

    Figure  16.  Aircraft acceleration under condition 4

    图  17  工况4下的飞机速度

    Figure  17.  Aircraft speed under condition 4

    图  18  工况4下的间隔距离

    Figure  18.  Spacing distance under condition 4

    图  19  工况4下的协同状态

    Figure  19.  Collaborative state under condition 4

    表  1  关键参数初始值

    Table  1.   Initial values of key parameters

    下载: 导出CSV
  • [1] Joint Planning and Development Office. Concept of operations for the next generation air transportation system[R]. Washington DC: Federal Aviation Administration, 2007.
    [2] 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]//IEEE. Proceedings of the 2003Systems and Information Engineering Design Symposium. New York: IEEE, 2003: 57-66.
    [3] YOUSEFI A, DONOHUE G. High-volume tube-shape sectors (HTS): a network of high capacity ribbons connecting congested city pairs[C]//IEEE. The 23rd Digital Avionics Systems Conference. New York: IEEE, 2004: 12-21.
    [4] SRIDHAR B, GRABBE S, SHETH K, et al. Initial study of tube networks for flexible airspace utilization[C]//AIAA. 2006AIAA Guidance, Navigation, and Control Conference. Washington DC: AIAA, 2006: 237-252.
    [5] HOFFMAN R, PRETE J. Principles of airspace tube design for dynamic airspace configuration[C]//AIAA. 26th Congress of International Council of the Aeronautical Sciences. Anchorage: AIAA, 2008: 108-139.
    [6] XUE Min, KOPARDEKAR P. High-capacity tube network design using the hough transform[J]. Journal of Guidance, Control and Dynamics, 2009, 32 (3): 788-795. doi: 10.2514/1.40386
    [7] XUE Min, ZELINSKI S J. Complexity analysis of traffic in corridors-in-the-sky[C]//AIAA. 10th AIAA Aviation Technology, Integration and Operations Conference. Fort Worth: AIAA, 2000: 110-122.
    [8] HEXMOOR H, HENG T. Air traffic control agents: landing and collision avoidance[C]//AIAA. International Conference in Artificial Intelligence. Las Vegas: AIAA, 2000: 21-35.
    [9] NITSCHKE G. Cooperating air traffic control agents[J]. Applied Artificial Intelligence, 2001, 15 (2): 209-235. doi: 10.1080/088395101750065778
    [10] CALLANTINE T J. CATS-based air traffic controller agents[R]. Sacramento: NASA Ames Research Center, 2002.
    [11] NGUYEN M, BRIOT J, DROGOUL A. An application of multi-agent coordination techniques in air traffic management[C]//IEEE. 2003IEEE/WIC International Conference in Intelligent Agent Technology. Halifax: IEEE, 2003: 622-625.
    [12] HILL J, ARCHIBALD J, STIRLING W, et al. A multi-agent system architecture for distributed air traffic control[C]//AIAA. 2005AIAA Guidance, Navigation and Control Conference. San Francisco: AIAA, 2005: 1005-1049.
    [13] AGOGINO A, TUMER K. Learning indirect actions in complex domains: action suggestions for air traffic control[J]. Advances in Complex Systems, 2009, 12 (4): 493-512.
    [14] 张洪海. 机场终端区协同流量管理关键技术研究[D]. 南京: 南京航空航天大学, 2009.

    ZHANG Hong-hai. The key technologies of collaborative flow management in airport terminal area[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2009. (in Chinese).
    [15] 黎新华, 张兆宁. 基于Agent的空中交通流量管理系统结构研究[J]. 交通运输工程与信息学报, 2007, 5 (1): 56-61. https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC200701011.htm

    LI Xin-hua, ZHANG Zhao-ning. Research of the structure of air traffic flow management system based on the agent[J]. Journal of Transportation Engineering and Information, 2007, 5 (1): 56-61. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC200701011.htm
    [16] 王万乐. Multi-Agent系统在飞行冲突探测与解脱中的应用[J]. 交通信息与安全, 2009, 27 (3): 9-15. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS200903002.htm

    WANG Wan-le. Application of multi-agent system in flight conflict detection and resolution[J]. Journal of Transport Information and Safety, 2009, 27 (3): 9-15. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS200903002.htm
    [17] 戴玲, 夏学知. 多Agent技术在飞行冲解脱中的应用[J]. 舰船电子工程, 2009, 28 (3): 62-64, 89. https://www.cnki.com.cn/Article/CJFDTOTAL-JCGC200803018.htm

    DAI Ling, XIA Xue-zhi. Application of multi-agent in flight conflict resolution[J]. Ship Electronic Engineering, 2009, 28 (3): 62-64, 89. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JCGC200803018.htm
    [18] 王超, 徐肖豪. 基于Agent的空中交通系统建模与仿真研究[J]. 计算机工程与应用, 2008, 44 (31): 12-14. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG200831004.htm

    WANG Chao, XU Xiao-hao. Researching on air traffic system using agent-based modeling and simulation[J]. Computer Engineering and Applications, 2008, 44 (31): 12-14. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG200831004.htm
    [19] 王飞, 徐肖豪, 张静. 基于Multi-Agent的空中交通协同流量管理[J]. 广西师范大学学报: 自然科学版, 2008, 26 (1): 125-128. https://www.cnki.com.cn/Article/CJFDTOTAL-GXSF200801032.htm

    WANG Fei, XU Xiao-hao, ZHANG Jing. Air traffic flow collaborate management based on multi-agent[J]. Jounal of Guangxi Normal University: Natural Science Edition, 2008, 26 (1): 125-128. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GXSF200801032.htm
    [20] 张钧翔, 胡明华. 基于多Agent的多机场终端区空中交通智能仿真系统设计[J]. 交通运输工程与信息学报, 2009, 7 (2): 90-98. https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC200902019.htm

    ZHANG Jun-xiang, HU Ming-hua. Design of the air traffic intelligent simulation system for the airport with multi-terminal areas based on multi-agents[J]. Journal of Transportation Engineering and Information, 2009, 7 (2): 90-98. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC200902019.htm
    [21] YOUSEFI A, LARD J, TIMMERMAN J. Nextgen flow corridors initial design, procedures, and display functionalities[C]//IEEE. 29th Digital Avionics Systems Conference. Salt Lake City: IEEE, 2010: 201-219.
    [22] YOUSEFI A, ZADEH A N. Dynamic allocation and benefit assessment of nextgen flow corridors[J]. Transportation Research Part C: Emerging Technologies, 2013, 33 (2): 297-310.
    [23] 黄卫芳. 美国区域导航航路划设和实施研究[J]. 空中交通管理, 2011 (2): 8-10, 46.

    HUANG Wei-fang. Studies on US RNAV route alignment and implementation[J]. Air Traffic Management, 2011 (2): 8-10, 46. (in Chinese).
    [24] STROEVE S, BLOM H, BAKKER G. Systemic accident risk assessment in air traffic by Monte Carlo simulation[J]. Safety Science, 2009, 47 (2): 238-249.
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出版历程
  • 收稿日期:  2013-06-18
  • 刊出日期:  2013-12-25

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