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Model for Estimating Urban Mobility Based on the Records of User Activities in Public Mobile Networks

Author

Listed:
  • Krešimir Vidović

    (Ericsson Nikola Tesla, Krapinska 45, 10000 Zagreb, Croatia)

  • Marko Šoštarić

    (Department of Transport Planning, Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Sadko Mandžuka

    (Department of Intelligent Transport Systems, Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Goran Kos

    (Institute for tourism, Vrhovec 4, 10000 Zagreb, Croatia)

Abstract

Urban mobility of a population is usually estimated within procedures that focus on specific domains, using limited datasets, indicators, and indices related to the targeted subsets of the urban population. This paper proposes a new approach to urban mobility estimation, based on the telecommunication activities within the public mobile telecommunication networks. The urban mobility indicators in this research are generated from a database of mobile phone users call data records and are integrated into the urban mobility index of the population based on the model defined through the adaptive neuro-fuzzy inference system (ANFIS). The following has been considered in the process: an initial fuzzy inference system, model learning, model quality control, limitations, errors, and deficiencies. The model is practically applied in the programming environment, on a set of real word data. The research results prove the following hypothesis set in this paper: the urban mobility of inhabitants in a specific timeframe, can be described with an urban mobility index based on the data on the recorded telecommunication activities of the public mobile communication network users.

Suggested Citation

  • Krešimir Vidović & Marko Šoštarić & Sadko Mandžuka & Goran Kos, 2020. "Model for Estimating Urban Mobility Based on the Records of User Activities in Public Mobile Networks," Sustainability, MDPI, vol. 12(3), pages 1-27, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:838-:d:312226
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    References listed on IDEAS

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    1. Morfoulaki, Maria & Tyrinopoulos, Yannis & Aifadopoulou, Georgia, 2007. "Estimation of Satisfied Customers in Public Transport Systems: A New Methodological Approach," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 46(1).
    2. Jean-Pierre Nicolas & Pascal Pochet & Hélène Poimboeuf, 2003. "Towards Sustainable Mobility Indicators: Application to the Lyons Conurbation," Post-Print halshs-00068232, HAL.
    3. Nicolas, J. -P. & Pochet, P. & Poimboeuf, H., 2003. "Towards sustainable mobility indicators: application to the Lyons conurbation," Transport Policy, Elsevier, vol. 10(3), pages 197-208, July.
    4. Frei, Fernando, 2006. "Sampling mobility index: Case study in Assis--Brazil," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(9), pages 792-799, November.
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    1. Marcele Elisa Fontana & Natallya de Almeida Levino & José Leão & Patrícia Guarnieri & Emerson Philipe Sinesio, 2023. "Risk Analysis of Transport Requalification Projects in the Urban Mobility Problem Caused by a Mining Disaster," Logistics, MDPI, vol. 7(3), pages 1-17, September.
    2. Marko Šoštarić & Krešimir Vidović & Marijan Jakovljević & Orsat Lale, 2021. "Data-Driven Methodology for Sustainable Urban Mobility Assessment and Improvement," Sustainability, MDPI, vol. 13(13), pages 1-22, June.

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