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Time Pattern Recognition of Traffic Flow in Terminal Area Based on Community Division

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Abstract

In order to extract the time pattern of traffic flow fluctuation in terminal area and realize the macroscopic description of traffic flow in terminal area. A time pattern recognition method of traffic flow in terminal area is proposed. Firstly, the traffic flow in the terminal area is counted, the time scale is determined according to the characteristics of data distribution, and the flow time series is established. Secondly, time series are mapped into complex networks by using visibility graph. Finally, time series segmentation and time pattern recognition are realized by community division of complex networks. Based on the experimental data of 4998 arrival flights within a week in a terminal area, the time series is established and the experiment is carried out. Experimental results show that with transformation of time series into complex networks, the dynamic segmentation of time series can be realized by community division, and the accurate identification of different fluctuation modes of time series can be realized while maintaining the dynamic segmentation of time series.

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Data Availability

Raw data were generated at the Automatic Dependent Surveillance-Broadcast equipment. Derived data supporting the findings of this study are available from the corresponding author upon request.

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Acknowledgements

This work was supported by the Fundamental Research Funds for the Central Universities and CAUC special fund under Grant 3122022105.

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Authors and Affiliations

  1. College of Air Traffic Management, Civil Aviation University of China, Tianjin, 300300, China

    Zhaoyue Zhang & Ying Yang

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  1. Zhaoyue Zhang
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  2. Ying Yang
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Correspondence to Zhaoyue Zhang.

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Zhang, Z., Yang, Y. Time Pattern Recognition of Traffic Flow in Terminal Area Based on Community Division. Mobile Netw Appl 27, 2543–2552 (2022). https://doi.org/10.1007/s11036-022-02079-2

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