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Prediction of Bus Travel Time over Intervals between Pairs of Adjacent Bus Stops Using City Bus Probe Data

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Abstract

Prediction of bus travel time is a crucial tool for passengers. We present methods to predict bus travel time over intervals between pairs of adjacent bus stops using city bus probe data. We apply Gradient Boosting Decision Trees to several kinds of features extracted from the probe data. Experimental results illustrate that adding a combination of features improves the accuracy of travel time prediction over the target interval. In particular, the method using a combination of the travel time over the interval previous to the target one and the number of stops the bus makes before reaching the target interval has better performance than the other methods which use all the other combinations of four features used in this study.

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Notes

  1. https://www.furuno.com/en/its/articles/20171026/

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Acknowledgments

The probe data used in this study were provided by Showa Bus Co. Ltd., Saga, Japan under the Collaboration Research. This work is partly supported by JSPS KAKENHI Grant Numbers JP19KK0257 and JP20H01728.

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Authors and Affiliations

  1. Department Advanced Information Technology, Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan

    Takuya Kawatani, Tsubasa Yamaguchi, Yuta Sato & Ryotaro Maita

  2. Department Advanced Information Technology, Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan

    Tsunenori Mine

Authors
  1. Takuya Kawatani
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  2. Tsubasa Yamaguchi
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  3. Yuta Sato
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  4. Ryotaro Maita
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  5. Tsunenori Mine
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Correspondence to Takuya Kawatani.

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Kawatani, T., Yamaguchi, T., Sato, Y. et al. Prediction of Bus Travel Time over Intervals between Pairs of Adjacent Bus Stops Using City Bus Probe Data. Int. J. ITS Res. 19, 456–467 (2021). https://doi.org/10.1007/s13177-021-00251-8

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  • DOI: https://doi.org/10.1007/s13177-021-00251-8

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