Volume 41 Issue 6
Dec.  2023
Turn off MathJax
Article Contents
Article Navigation >  Journal of Transport Information and Safety  > 2023  >  41(6): 142-151
JIANG Wei, LI Yinfeng. An Entropy Weighting-improved TOPSIS Method for Sector Complexity Evaluation[J]. Journal of Transport Information and Safety, 2023, 41(6): 142-151. doi: 10.3963/j.jssn.1674-4861.2023.06.016
Citation: JIANG Wei, LI Yinfeng. An Entropy Weighting-improved TOPSIS Method for Sector Complexity Evaluation[J]. Journal of Transport Information and Safety, 2023, 41(6): 142-151. doi: 10.3963/j.jssn.1674-4861.2023.06.016
shu

An Entropy Weighting-improved TOPSIS Method for Sector Complexity Evaluation

doi: 10.3963/j.jssn.1674-4861.2023.06.016

  • School of Emergency Management and Safety Engineering, North China University of Science and Technology, Tangshan 063210, China

  • Received Date: 2023-08-23
    Available Online: 2024-04-03
    Abstract
  • Sector complexity evaluation is the key and foundation for airspace planning and airspace resource allocation strategy. To solve the problems of multi-factor coupling and the issue of simplicity and subjectivity of existing evaluation methods, a sector complexity evaluation method based on entropy weight improvement-TOPSIS method is proposed. According to the operation characteristics of airspace sector, eight specific quantitative indicators are developed from three aspects of airspace static structure, traffic operation state and dynamic restriction, including route structure, aircraft potential conflict and bad weather, to establish a multidimensional evaluation index system that comprehensively reflects the complexity of airspace sector. A Gaussian distribution outlier detection method is used to eliminate the influence of extreme outliers on the evaluation. Combined with objective weight calculation of entropy weight method, a sector complexity evaluation method is proposed based on entropy weighting improved TOPSIS method, which is closer to the actual operation of the sector and conforms to the subjective cognition. This study takes Beijing regional sectors as an example for verification analysis, based on the standard of balanced sector complexity, the sector complexity is evaluated and analyzed from two scenarios: horizontal comparison between multiple sectors and comparison of single sector at different time periods, and compared with the expert evaluation results. The results show that the complexity of the two scenarios is unbalanced, indicating that the current allocation of airspace resources in Beijing area is unbalanced in both time and space. According to the evaluation results, airspace structure adjustment and traffic flow optimization can be carried out. Compared with the evaluation results of expert experience, the evaluation results of this method agree with the subjective cognition of experts as high as 80%, which verifies the feasibility, accuracy and effectiveness of this method. This method outperforms the expert evaluation method with the advantages of quantification, strong objectivity and convenient calculation.

     

    • FullText(HTML)
  • loading
    • References(21)
  • [1]
    PUECHMOREL S, DELAHAYA D. New trends in air traffic complexity[C]. 2009 ENRI Internation-al Workshop on ATM/ CNS (EIWAC), Tokyo, Japan: Electronic Navigation Research Institute, 2009.
    [2]
    PRANDINI M, PUTTA V, HU J. A probabilistic measure of air traffic complexity in 3D airspace[J]. International Journal of Adaptive Control and Signal Processing, 2010, 24(10): 813-829. doi: 10.1002/acs.1192
    [3]
    HONG Y, KIM Y, LEE K. Conflict management in air traffic control using complexity map[J]. Journal of Aircraft, 2015, 52 (5): 1524-1534. doi: 10.2514/1.C032987
    [4]
    WANG L L. Research on the classification of air route intersections in the airspace of China[J]. Transportation Research Board, 2019, 2673(2): 243-251. doi: 10.1177/0361198118825452
    [5]
    HILBURN B. Cognitive complexity in air traffic control: a literature review[J]. Center for Human Performance Research, 2004(4): 1-80.
    [6]
    KOPARDEKAR P, SCHWARTZ A, MAGYARITS S, et al. Airspace complexity measurement: an air traffic control simulation analysis[J]. International Journal of Industrial Engineering, 2009, 16(1): 61-70.
    [7]
    XIAO M M, ZHANG J, CAI K Q, et al. ATCEM: a synthetic model for evaluating air traffic complexity[J]. Journal of Advanced Transportation, 2016, 50(3): 315-325. doi: 10.1002/atr.1321
    [8]
    LI B Y, DU W B, ZHANG Y, et al. A deep unsupervised learning approach for airspace complexity evaluation[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 11739-11751. doi: 10.1109/TITS.2021.3106779
    [9]
    张进, 胡明华, 张晨. 空中交通管理中的复杂性研究[J]. 航空学报, 2009, 30(11): 2132-2142. https://www.cnki.com.cn/Article/CJFDTOTAL-HKXB200911020.htm

    ZHANG J, HU M H, ZHANG C. Complexity research in air traffic management[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(11): 2132-2142. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HKXB200911020.htm
    [10]
    GIANAZZA D. Forecasting workload and airspace configuration with neural networks and tree search methods[J]. Artificial Intelligence, 2010, 174(7): 530-549.
    [11]
    SURAKITBANHARN C, WEI P, LANDRY S, et al. Evaluation of stream air traffic operations by adapting dynamic density complexity measure[C]. 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Indianapolis, Indiana: American Institute of Aeronautics and Astronautics, 2012.
    [12]
    王红勇, 赵嶷飞, 王飞, 等. 空中交通管制扇区复杂度评估研究[J]. 交通运输系统工程与信息, 2013, 13(6): 147-153. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201306023.htm

    WANG H Y, ZHAO B F, WANG F, et al. Research on complexity evaluation of air traffic control sector[J]. Journal of Transportation Systems Engineering and Information Technology, 2013, 13(6): 147-153. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201306023.htm
    [13]
    ZHU X, CAO X B, CAI K Q. Measuring air traffic complexity based on small samples[J]. Chinese Journal of Aeronautics, 2017, 30(4): 1493-1505. doi: 10.1016/j.cja.2017.04.018
    [14]
    贾铧霏. 基于复杂度分析的扇区划分研究[D]. 天津: 中国民航大学, 2017.

    JIA H F. Research on sector division based on complexity analysis[D]. Tianjin: Civil Aviation University of China, 2017. (in Chinese)
    [15]
    王莉莉, 胡亚坤. 空中航路交叉点的复杂度分析[J]. 计算机仿真, 2019, 36(8): 51-56. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJZ201908011.htm

    WANG L L, HU Y K. Complexity analysis of air route intersection[J]. Computer Simulation, 2019, 36(8): 51-56. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSJZ201908011.htm
    [16]
    郝恩蕾. 基于管制工作复杂性的终端区改航策略研究[D]. 南京: 南京航空航天大学, 2017.

    HAO E L. Research on terminal area rerouting strategy based on the complexity of control work[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2017. (in Chinese)
    [17]
    王莉莉, 张兆宁. 空域规划与管理[M]. 北京: 科学出版社, 2019.

    WANG L L, ZHANG Z N. Airspace planning and management[M]. Beijing: Science Press, 2019. (in Chinese)
    [18]
    XIAO S M, LI Y F, SHANG R R, et al. Threshold analysis method for aircraft avoiding convective weather[J]. Journal of Mechanical Engineering, Automation and Control Systems, 2022, 3(1): 35-46. doi: 10.21595/jmeacs.2022.22575
    [19]
    卿原, 张洪海, 张启钱, 等. 基于TOPSIS-GRA的空管航班正常管理绩效评价[J]. 航空计算技术, 2019, 49(6): 33-37. https://www.cnki.com.cn/Article/CJFDTOTAL-HKJJ201906008.htm

    QING Y, ZHANG H H, ZHANG Q Q, et al. Performance evaluation of air traffic control flight normal management based on TOPSIS-GRA[J]. Aviation Computing Technology, 2019, 49(6): 33-37. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HKJJ201906008.htm
    [20]
    CHEN Z Y, SHEN D, REN Y J, et al. Airspace operation effectiveness evaluation based on q-rung orthopair probabilistic hesitant fuzzy GRA and TOPSIS[J]. Symmetry, 2022, 14 (2): 242-263. doi: 10.3390/sym14020242
    [21]
    冯芝梅, 郭明洋, 贺玉龙, 等. 基于组合赋权-改进TOPSIS法的城市慢行三网融合评价方法[J]. 交通信息与安全, 2023, 41(4): 163-172. doi: 10.3963/j.jssn.1674-4861.2023.04.017?viewType=HTML

    FENG Z M, GUO M Y, HE Y L, et al. A combined weighting-improved TOPSIS method for evaluating integration of urban greenway-waterfront road-municipal non-motorized transport network[J]. Journal of Transport Information and Safety, 2023, 41(4): 163-172. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2023.04.017?viewType=HTML
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(9)  / Tables(6)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (226) PDF downloads(10) Cited by()
    Proportional views
    Related

    Copyright Editorial Office of Transport Information and Safety鄂ICP备05003336号-2

    Address：No. 1178，Heping Avenue, Wuchang, Wuhan, CHINA (430063)

    Tel：027-86580355 Email：jtjsj@vip.163.com

    Supported by: Beijing Renhe Information Technology Co. Ltd  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return