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Spatiotemporal analysis of trajectory for a new real-time bus routes updated model

  • Deep Learning for Big Data Analytics
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Abstract

With the development of location-based service, the wide range of applications of trajectory data obtained by GPS has made great contributions to the analysis of urban buses information. Affected by the increasing quantity of data, filtering out valid GPS trajectory data to update real-time information of urban buses faces new difficulties. In this study, a prototype model named Real-Time Bus Routes Updated model (RT-BRU) is developed to process and mine the GPS trajectory data collected from each urban bus of each interval. The main purpose of this model is to update real-time information of urban bus routes and provide much more realistic public navigation data with the help of trajectory data and geo-statistical tools. Compared to the regular algorithms and Chinese public navigation map data, the experiment results show that the RT-BRU model proposed here can discover more types of urban bus’s updated routes and play better in perspective of GPS points counts, operation time, calculation results, correct results and accuracy.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China, No. 71503068 by Youlin Zhao; National Philosophy and Social Science Fund Key Grant, No. 16ZDA046; Program for Changjiang Scholars and Innovative Research Team in University (No. IRT_17R35). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Authors and Affiliations

  1. Business School of Hohai University, Nanjing City, 211100, Jiangsu Province, People’s Republic of China

    Youlin Zhao

  2. Business School of Hohai University, Nanjing City, Jiangsu Province, People’s Republic of China

    Yahui Liu

  3. Tianjin Institute of Surveying and Mapping, No. 9 Changling Road, Liqizhuang, Tianjin, 300381, China

    Liang Ge

  4. First Crust Deformation Monitoring and Application Center, China Earthquake Administration, Tianjin, 300180, China

    Ning Wang

Authors
  1. Youlin Zhao
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  2. Yahui Liu
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  3. Liang Ge
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  4. Ning Wang
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Contributions

YLZ and LG conceived and designed the experiments. YLZ, LG, NW and YHL performed the experiments. LG and YLZ analyzed the data. YHL and LG contributed reagents/materials/analysis tools. YLZ, LG, NW and YHL wrote the paper.

Corresponding authors

Correspondence to Youlin Zhao or Liang Ge.

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Zhao, Y., Liu, Y., Ge, L. et al. Spatiotemporal analysis of trajectory for a new real-time bus routes updated model. Neural Comput & Applic 32, 1701–1713 (2020). https://doi.org/10.1007/s00521-019-04244-3

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  • DOI: https://doi.org/10.1007/s00521-019-04244-3

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