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Inferring the Most Popular Route Based on Ant Colony Optimization with Trajectory Data

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Wireless Sensor Networks (CWSN 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 812))

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Abstract

The development of big data technologies makes it possible to derive valuable information from the history trajectory data. An algorithm is proposed to discover the most popular route from the given source to the given destination in this paper. The region is latticed into regular grids and then the history trajectories are discretized according to the aforementioned grids. Afterwards, the most popular route is determinated by the ant colony optimization method, where the actions of the ants are inspired by the statistics of the history trajectories which lead to the destination or at least near the destination. The grid size and the ant colony parameters are adjustable to fulfil the requirements of the solution precision and the computation complexity. The experiments are performed on the real vehicle trajectory dataset and the results meet our common sense of the popular routes.

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Acknowledgement

This work was supported by National Natural Science Foundation of China (61370191) and the Fundamental Research Funds for the Central Universities (FRFBR-16-024a).

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Authors and Affiliations

  1. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Hong Zhang & Wei Huangfu

  2. Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services, Beijing, 100083, China

    Hong Zhang & Wei Huangfu

  3. China Mobile Group Design Institute Co., Ltd., Beijing, 100080, China

    Xiaoyan Hu

Authors
  1. Hong Zhang
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  2. Wei Huangfu
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  3. Xiaoyan Hu
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Corresponding author

Correspondence to Wei Huangfu .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Jianzhong Li

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Huadong Ma

  3. Tianjin University, Tianjin, Tianjin, China

    Keqiu Li

  4. Chinese Academy of Sciences, Beijing, China

    Li Cui

  5. Chinese Academy of Sciences, Beijing, China

    Limin Sun

  6. Tianjin University, Tianjin, China

    Zenghua Zhao

  7. Tianjin University, Tianjin, China

    Xiaofei Wang

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Zhang, H., Huangfu, W., Hu, X. (2018). Inferring the Most Popular Route Based on Ant Colony Optimization with Trajectory Data. In: Li, J., et al. Wireless Sensor Networks. CWSN 2017. Communications in Computer and Information Science, vol 812. Springer, Singapore. https://doi.org/10.1007/978-981-10-8123-1_27

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  • DOI: https://doi.org/10.1007/978-981-10-8123-1_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8122-4

  • Online ISBN: 978-981-10-8123-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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