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An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition

Author

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  • Elisa Frutos-Bernal

    (Department of Statistics, Universidad de Salamanca, 37007 Salamanca, Spain)

  • Ángel Martín del Rey

    (Department of Applied Mathematics, Institute of Fundamental Physics and Mathematics, Universidad de Salamanca, 37008 Salamanca, Spain)

  • Irene Mariñas-Collado

    (Department of Statistics and Operation Research and Mathematics Didactics, Universidad de Oviedo, 33007 Oviedo, Spain)

  • María Teresa Santos-Martín

    (Department of Statistics, Institute of Fundamental Physics and Mathematics, Universidad de Salamanca, 37008 Salamanca, Spain)

Abstract

In recent years, a growing number of large, densely populated cities have emerged, which need urban traffic planning and therefore knowledge of mobility patterns. Knowledge of space-time distribution of passengers in cities is necessary for effective urban traffic planning and restructuring, especially in large cities. In this paper, the inbound ridership in the Barcelona metro is modelled into a three-way tensor so that each element contains the number of passenger in the i th station at the j th time on the k th day. Tucker3 decomposition is used to discover spatial clusters, temporal patterns, and the relationships between them. The results indicate that travel patterns differ between weekdays and weekends; in addition, rush and off-peak hours of each day have been identified, and a classification of stations has been obtained.

Suggested Citation

  • Elisa Frutos-Bernal & Ángel Martín del Rey & Irene Mariñas-Collado & María Teresa Santos-Martín, 2022. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1122-:d:784358
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    References listed on IDEAS

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    Cited by:

    1. Irene Mariñas-Collado & Ana E. Sipols & M. Teresa Santos-Martín & Elisa Frutos-Bernal, 2022. "Clustering and Forecasting Urban Bus Passenger Demand with a Combination of Time Series Models," Mathematics, MDPI, vol. 10(15), pages 1-16, July.

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