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A Novel Approach to Taxi-GPS-Trace-Aware Bus Network Planning

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2021)

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Abstract

Taxi GPS traces are rich with information regarding the human mobility pattern in metropolitans. In this paper, we aimed at fully exploiting the Taxi GPS traces and addressing the bus network planning problem. Specifically, the proposed framework comprises a method for determining candidate bus stations by utilizing passenger pick-up and drop-off records, a bio-inspired method for yielding bus routes and further for generating the final bus network. To prove the effectiveness of our framework, we conduct simulative studies as well based on a real-world taxi GPS data-set and show that our proposed framework considerably outperforms traditional ones.

Liangyao Tang and Peng Chen contribute equally to this work and thus are co-first authors of this paper.

This work is supported by China Scholarship Council Science and Technology Program of Sichuan Province under Grant 2020YFG0326, Talent Program of Xihua University under Grant Z202047, the Chongqing grand research and development project under Grant cstc2019jscx-fxyd0385.

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Authors and Affiliations

  1. School of Computers, Chongqing University, Chongqing, 400030, China

    Liangyao Tang, Ruilong Yang, Yunni Xia & Hong Xie

  2. School of Computer and Software Engineering, Xihua University, Chengdu, 610039, China

    Peng Chen

  3. Mashang Consumer Finance Co., Ltd. (MSCF), Chongqing, 40022, China

    Ning Jiang

  4. Institute of Software Application Technology, Guangzhou and Chinese Academy of Sciences, Guangzhou, 511458, China

    Yin Li

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  1. Liangyao Tang
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  2. Peng Chen
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  4. Yunni Xia
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  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. Xi’an Jiaotong-Liverpool University, Suzhou, China

    Xinheng Wang

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Tang, L. et al. (2021). A Novel Approach to Taxi-GPS-Trace-Aware Bus Network Planning. In: Gao, H., Wang, X. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-030-92635-9_30

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  • DOI: https://doi.org/10.1007/978-3-030-92635-9_30

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  • Print ISBN: 978-3-030-92634-2

  • Online ISBN: 978-3-030-92635-9

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