IDEAS home Printed from https://ideas.repec.org/h/spr/eurchp/978-3-031-62719-4_12.html
   My bibliography  Save this book chapter

Data-Driven Public Transport Routes and Timetables Based on Anonymized Telecom Data

In: Eurasian Business and Economics Perspectives

Author

Listed:
  • Nikolay Netov

    (St. Kliment Ohridski Sofia University)

  • Radoslav Rizov

    (St. Kliment Ohridski Sofia University)

Abstract

Human activities, including daily urban commuting, usually demonstrate a mix of sustainable and changing behavioral patterns. The development and continuous update of optimal routes and schedules for public transport is a key element in satisfying the transport demands of dwellers. The data available demonstrates a perceived private car dominance over public transport use in Bulgaria. The limited capabilities of cities to develop and introduce optimal routes and schedules of public transport services based on citizens’ actual demands and needs is considered a major shortcoming. The aim of the article is to validate an approach for public transport optimization based on anonymous and statistically aggregated mobile phone positioning data. Our results, which focus exclusively on this novel kind of data, supplement earlier studies on the use of Seasonal ARIMA models in short-term passenger demand forecasting. This allowed us to make a statistical assessment and forecast potential future passenger flow for our chosen routes at different time ranges of the day. Data-driven public transport routes and timetables would make public transport more attractive and useful. Reducing the share of private car trips will improve the air quality and will help lower the level of noise pollution and CO2 emissions in our cities.

Suggested Citation

  • Nikolay Netov & Radoslav Rizov, 2024. "Data-Driven Public Transport Routes and Timetables Based on Anonymized Telecom Data," Eurasian Studies in Business and Economics, in: Mehmet Huseyin Bilgin & Hakan Danis & Ender Demir & Sofia Vale (ed.), Eurasian Business and Economics Perspectives, pages 219-231, Springer.
  • Handle: RePEc:spr:eurchp:978-3-031-62719-4_12
    DOI: 10.1007/978-3-031-62719-4_12
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eurchp:978-3-031-62719-4_12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.