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International Conference on Computer Recognition Systems

CORES 2017: Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017 pp 53–62Cite as

Travel Time Prediction for Trams in Warsaw

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 578))

Abstract

The paper presents a comparison between different prediction methods for trams time travels in Warsaw. Predictions are constructed based on historical trams GPS positions. Three different prediction approaches were implemented and compared with the official timetables and real time travels. Obtained results show that the official timetables provides only approximated time travel especially in rush hours. Proposed prediction methods outperform the official schedule in the term of time travel precision and may be used as a more accurate source of travel time for passengers.

The research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688380.

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Author information

Authors and Affiliations

  1. Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662, Warsaw, Poland

    Adam Zychowski, Konstanty Junosza-Szaniawski & Aleksander Kosicki

Authors
  1. Adam Zychowski
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  2. Konstanty Junosza-Szaniawski
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  3. Aleksander Kosicki
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Corresponding author

Correspondence to Adam Zychowski .

Editor information

Editors and Affiliations

  1. Department of Systems and Computer Networks, Wrocław University of Technology, Wrocław, Poland

    Marek Kurzynski

  2. Department of Systems and Computer Networks, Wrocław University of Technology, Wroclaw, Poland

    Michal Wozniak

  3. Department of Systems and Computer Networks, Wrocław University of Technology , Wroclaw, Poland

    Robert Burduk

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Zychowski, A., Junosza-Szaniawski, K., Kosicki, A. (2018). Travel Time Prediction for Trams in Warsaw. In: Kurzynski, M., Wozniak, M., Burduk, R. (eds) Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017. CORES 2017. Advances in Intelligent Systems and Computing, vol 578. Springer, Cham. https://doi.org/10.1007/978-3-319-59162-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-59162-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59161-2

  • Online ISBN: 978-3-319-59162-9

  • eBook Packages: EngineeringEngineering (R0)

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