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A holistic data-driven framework for developing a complete profile of bus passengers

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  • Chen, Siyuan
  • Liu, Xin
  • Lyu, Cheng
  • Vlacic, Ljubo
  • Tang, Tianli
  • Liu, Zhiyuan

Abstract

User profiles, considered as one of the fundamental inputs of recommendation systems and customized services, can be rationally applied in the public transport domain to represent passengers’ characteristics and behavioral preferences. A user profile of a bus passenger, termed as a bus passenger profile (BPP), is an assortment of labels containing passengers’ travel features. This paper proposes a data-driven framework for developing BPP so as to provide guidance on how to create and estimate user profiles for bus passengers based on smart card data. The proposed method comprises three steps. (i) Data preprocessing aimed at extracting key information and preparing passenger profiling. (ii) A tag system aimed at storing the estimated travel features of passengers. (iii) Knowledge graphs aimed at connecting various BPP with semantic edges for practical application of prior knowledge in downstream tasks. The developed framework is implemented in a case study of the Beijing bus system. Deployment of the developed framework has demonstrated that it can satisfactorily develop BPP, while prior knowledge from the BPP-based knowledge graphs can benefit downstream tasks.

Suggested Citation

  • Chen, Siyuan & Liu, Xin & Lyu, Cheng & Vlacic, Ljubo & Tang, Tianli & Liu, Zhiyuan, 2023. "A holistic data-driven framework for developing a complete profile of bus passengers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:transa:v:173:y:2023:i:c:s096585642300112x
    DOI: 10.1016/j.tra.2023.103692
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    References listed on IDEAS

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    1. Schmid, Basil & Jokubauskaite, Simona & Aschauer, Florian & Peer, Stefanie & Hössinger, Reinhard & Gerike, Regine & Jara-Diaz, Sergio R. & Axhausen, Kay W., 2019. "A pooled RP/SP mode, route and destination choice model to investigate mode and user-type effects in the value of travel time savings," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 262-294.
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    1. Tang, Tianli & Gu, Ziyuan & Yang, Yuanxuan & Sun, Haobo & Chen, Siyuan & Chen, Yuting, 2024. "A data-driven framework for natural feature profile of public transport ridership: Insights from Suzhou and Lianyungang, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).

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