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Goal-oriented possibilistic fuzzy C-Medoid clustering of human mobility patterns—Illustrative application for the Taxicab trips-based enrichment of public transport services

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  • Miklós Mezei
  • Imre Felde
  • György Eigner
  • Gyula Dörgő
  • Tamás Ruppert
  • János Abonyi

Abstract

The discovery of human mobility patterns of cities provides invaluable information for decision-makers who are responsible for redesign of community spaces, traffic, and public transportation systems and building more sustainable cities. The present article proposes a possibilistic fuzzy c-medoid clustering algorithm to study human mobility. The proposed medoid-based clustering approach groups the typical mobility patterns within walking distance to the stations of the public transportation system. The departure times of the clustered trips are also taken into account to obtain recommendations for the scheduling of the designed public transportation lines. The effectiveness of the proposed methodology is revealed in an illustrative case study based on the analysis of the GPS data of Taxicabs recorded during nights over a one-year-long period in Budapest.

Suggested Citation

  • Miklós Mezei & Imre Felde & György Eigner & Gyula Dörgő & Tamás Ruppert & János Abonyi, 2022. "Goal-oriented possibilistic fuzzy C-Medoid clustering of human mobility patterns—Illustrative application for the Taxicab trips-based enrichment of public transport services," PLOS ONE, Public Library of Science, vol. 17(10), pages 1-17, October.
  • Handle: RePEc:plo:pone00:0274779
    DOI: 10.1371/journal.pone.0274779
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    References listed on IDEAS

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    1. André Luiz Lopes Toledo & Emílio Lèbre La Rovere, 2018. "Urban Mobility and Greenhouse Gas Emissions: Status, Public Policies, and Scenarios in a Developing Economy City, Natal, Brazil," Sustainability, MDPI, vol. 10(11), pages 1-24, November.
    2. Jules Muvuna & Tuleen Boutaleb & Slobodan B. Mickovski & Keith Baker & Ghoreyshi Seyed Mohammad & Mario Cools & Wissal Selmi, 2020. "Information Integration in a Smart City System—A Case Study on Air Pollution Removal by Green Infrastructure through a Vehicle Smart Routing System," Sustainability, MDPI, vol. 12(12), pages 1-14, June.
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