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Context-aware and ethics-first crowd mobility portraits over massive smart card data

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Abstract

Smart card data have received increasing interest from transport researchers for travel behavior investigation. However, the utility of smart card data has arguably yet to be exploited in the spatio-temporal context of interpreting the essential properties of passenger groups. Before building socially responsible data models, considering ethics issues of what is right, just and fair is able to minimize negative impacts of technology. This work demonstrates a multi-phase methodology to illustrate the essential properties of passenger groups with crowd mobility portraits that are presented by several words in combination with visualized maps. In particular, we propose an efficient ranking algorithm to figure out trajectories mostly contributing to the city-wide mobility patterns and construct time-varying land functions to textualize trajectories and obtain interpretable crowd mobility portraits. Experiments show that our method outperforms the state-of-the-art methods with an accuracy improvement of 8%. Case studies of real-world data also confirm the effectiveness of crowd mobility portraits.

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Acknowledgements

This research/project is supported by the National Research Foundation, Singapore under its Strategic Capability Research Centres Funding Initiative. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore. This work was also supported by the Key Research and Development Program of Hunan Province (no. 2021GK5014, 2019SK2161).

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Authors and Affiliations

  1. Institute for AI Moral Decision-Making, Hunan Normal University, Yuelu Street, Changsha, 410081, Hunan, China

    Liqiang Peng

  2. College of Information Science and Engineering, Hunan Normal University, Yuelu Street, Changsha, 410081, Hunan, China

    Qiang Li

  3. School of Computing, National University of Singapore, 21 Lower Kent Ridge Rd, Singapore, 119077, Singapore

    Fei Wang

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  1. Liqiang Peng
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Correspondence to Qiang Li.

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Peng, L., Li, Q. & Wang, F. Context-aware and ethics-first crowd mobility portraits over massive smart card data. Multimedia Systems 29, 499–510 (2023). https://doi.org/10.1007/s00530-022-00967-x

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