• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 27 Issue 3
May  2014
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Article Contents
WANG Chao, HAN Bangcun, WANG Fei. Identification of Prevalent Air Traffic Flow in Terminal Airspace Based on Trajectory Spectral Clustering[J]. Journal of Southwest Jiaotong University, 2014, 27(3): 546-552. doi: 10.3969/j.issn.0258-2724.2014.03.027
Citation: WANG Chao, HAN Bangcun, WANG Fei. Identification of Prevalent Air Traffic Flow in Terminal Airspace Based on Trajectory Spectral Clustering[J]. Journal of Southwest Jiaotong University, 2014, 27(3): 546-552. doi: 10.3969/j.issn.0258-2724.2014.03.027

Identification of Prevalent Air Traffic Flow in Terminal Airspace Based on Trajectory Spectral Clustering

doi: 10.3969/j.issn.0258-2724.2014.03.027
  • Received Date: 15 Jul 2013
  • Publish Date: 25 Jun 2014
  • In order to improve the adaptability of terminal airspace and standard arrival/departure routes to real air traffic flows and their spatial distribution, a method for detection of main air traffic flows in massive flight trajectories was addressed. After analysis of the spatial characteristics of trajectories, a trajectory similarity model based on 3D grids was proposed. Flight trajectories were partitioned with spectral clustering algorithm, and an identification method for prevalent air traffic flow and outlier trajectories was proposed through kernel density estimation of trajectories in one cluster. Experiments were carried out from trajectories recorded by air traffic control radar to identify prevalent traffic flows. The results show that 1 476 trajectories were divided into 5 clusters, and 5 prevalent traffic flows were identified; in addition, the identification results were not affected by outliers.

     

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  • 袁冠, 夏士雄, 张磊, 等. 基于结构相似度的轨迹聚类算法[J]. 通信学报, 2011, 32(9): 103-110. YUAN Guan, XIA Shixiong, ZHANG Lei, et al. Trajectory clustering algorithm based on structural similarity[J]. Journal on Communications, 2011, 32(9): 103-110.
    陈继东, 孟小峰, 赖彩凤. 基于道路网络的对象聚类[J]. 软件学报, 2007, 18(2): 332-454. CHEN Jidong, MENG Xiaofeng, LAI Caifeng. Clustering objects in a road network[J]. Journal of Software, 2007, 18(2): 332-454.
    龚玺, 裴韬, 孙嘉, 等. 时空轨迹聚类方法研究进展[J]. 地理科学进展, 2011, 30(5): 522-534. GONG Xi, PEI Tao, SUN Jia, et al. Review of the research progresses in trajectory clustering methods[J]. Progress in Geography, 2011, 30(5): 522-534.
    王超, 徐肖豪, 王飞. 基于航迹聚类的终端区进场程序管制适用性分析[J]. 南京航空航天大学学报, 2013, 45(1): 130-139. WANG Chao, XU Xiaohao, WANG Fei. ATC serviceability analysis of terminal arrival procedures using trajectory clustering[J]. Journal of Nanjing University of Aeronautics and Astronautics, 2013, 45(1): 130-139.
    PERNG C S, WANG H, ZHANG S R, et al. Landmarks: a new model for similarity-based pattern querying in time series databases[C]//Proceedings of the 16th International Conference on Data Engineering,[S.l.]: IEEE, 2000: 33-42.
    CHEN L, ZSU M T, ORIA V. Robust and fast similarity search for moving object trajectories[C]//Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data. New York: ACM, 2005: 491-502.
    REHM F. Clustering of flight tracks[C]//6th AIAA Infotech @ Aerospace 2010. Atlanta: AIAA, 2010: AIAA-2010-3412.
    GARIEL M, SRIVASTAVA A, FERON E. Trajectory clustering and an application to airspace monitoring[J]. Intelligent Transportation Systems, 2011, 12(4): 1511-1524.
    赵恩来, 郝文宇, 赵飞, 等. 改进的基于密度的航迹聚类算法[J]. 计算机工程, 2011, 37(9): 270-272. ZHAO Enlai, HAO Wenyu, ZHAO Fei, et al. Improved track clustering algorithm based on density[J]. Computer Engineering, 2011, 37(9): 270-272.
    KLEIN J, BITTIHN P, LEDOCHOWITSCH P, et al. Grid-based spectral fiber clustering[C]//Medical Imaging. International Society for Optics and Photonics. San Diego: SPIE, 2007: 65091E-1-65091E-10.
    NG A Y, JORDAN M I, WEISS Y. On spectral clustering: analysis and an algorithm[C]//Proceedings of Advances in Neural Information Processing Systems. Cambridge: MIT Press, 2001: 849-856.
    Von LUXBURG U. A tutorial on spectral clustering[J]. Statistics and Computing, 2007, 17(4): 395-416.
    孔万增, 孙志海, 杨灿, 等. 基于本征间隙与正交特征向量的自动谱聚类[J]. 电子学报, 2010, 38(8): 1880-1885. KONG Wanzeng, SUN Zhihai, YANG Can, et al. Automatic spectral clustering based on eigengap and orthogonal[J]. Chinese Journal of Electronics, 2010, 38(8): 1880-1885.
    BELKIN M, NIYOGI P. Laplacian eigenmaps for dimensionality reduction and data representation[J]. Neural Computation, 2003, 15(6): 1373-1396.
    LEDL T. Kernel density estimation: theory and application in discriminant analysis[J]. Austrian Journal of Statistics, 2004, 33(3): 267-279.
    SILÜERMAN B W. Density estimation for statistics and data analysis[M]. London: Chapman and Hall, 1986: 45-48.
    HINNERBURG A, KEIM D A. An efficient approach to clustering in large multimedia database with noise[C]//Proceedings of the 4th International Conference on Knowledge Discovery and Data Mining.: AAAI Press, 1998: 58-65.
    NIKUNJ O. Flight tracks, Northern California Tracon[DB/OL].[2013-03-01]. https:[C]//c3.nasa.gov/dashlink/resources/132.
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