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Modeling Demand for Passenger Transfers in the Bounds of Public Transport Network

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Data Analytics: Paving the Way to Sustainable Urban Mobility (CSUM 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 879))

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Abstract

The proposed model is based on the developed approach to perform the routing assignment stage in the classical four-stage urban planning procedure. Demand for trips is generated for each stop of a public transport system on the grounds of stochastic variable of the time interval between passengers arrival to the respective stop. After defining of the destination stop, the route for the passenger’s trip is determined with the use of Dijkstra’s algorithm within the frame of a public transport network which is presented as a graph model with stops for vertices and route segments for edges. Transfer nodes are defined in the model as such graph vertices which are common for at least two lines of the public transport system. The author presents a class library implemented with the use of the Python programming language. On the basis of this library, the model for simulations of demand for transfers within the given public transport system was developed. The proposed approach to the demand modeling and the developed software were used for simulations of demand for transfers within the bounds of the public transport system of Bochnia (Poland).

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Author information

Authors and Affiliations

  1. Cracow University of Technology, Warszawska 24, 31-155, Krakow, Poland

    Vitalii Naumov

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  1. Vitalii Naumov
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Correspondence to Vitalii Naumov .

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Editors and Affiliations

  1. Department of Civil Engineering, Traffic, Transportation and Logistics Laboratory (TTLog), University of Thessaly, Volos, Greece

    Eftihia G. Nathanail

  2. Department of Civil Engineering, Traffic, Transportation and Logistics Laboratory (TTLog), University of Thessaly, Volos, Greece

    Ioannis D. Karakikes

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Naumov, V. (2019). Modeling Demand for Passenger Transfers in the Bounds of Public Transport Network. In: Nathanail, E., Karakikes, I. (eds) Data Analytics: Paving the Way to Sustainable Urban Mobility. CSUM 2018. Advances in Intelligent Systems and Computing, vol 879. Springer, Cham. https://doi.org/10.1007/978-3-030-02305-8_19

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  • DOI: https://doi.org/10.1007/978-3-030-02305-8_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02304-1

  • Online ISBN: 978-3-030-02305-8

  • eBook Packages: EngineeringEngineering (R0)

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