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Intelligent Decision Support System for Modeling Transport and Passenger Flows in Human-Centric Urban Transport Systems

Author

Listed:
  • Natalia Davidich

    (Department of Transport Systems and Logistics, O. M. Beketov National University of Urban Economy in Kharkiv, 61002 Kharkiv, Ukraine)

  • Andrii Galkin

    (Department of Transport Systems and Logistics, O. M. Beketov National University of Urban Economy in Kharkiv, 61002 Kharkiv, Ukraine
    Department of Transportation Engineering, Faculty of Civil Engineering, Slovak University of Technology, 810 05 Bratislava, Slovakia)

  • Yurii Davidich

    (Department of Transport Systems and Logistics, O. M. Beketov National University of Urban Economy in Kharkiv, 61002 Kharkiv, Ukraine)

  • Tibor Schlosser

    (Department of Transportation Engineering, Faculty of Civil Engineering, Slovak University of Technology, 810 05 Bratislava, Slovakia)

  • Silvia Capayova

    (Department of Transportation Engineering, Faculty of Civil Engineering, Slovak University of Technology, 810 05 Bratislava, Slovakia)

  • Joanna Nowakowska-Grunt

    (Department of Logistics, Faculty of Management, Czestochowa University of Technology, 42-201 Czestochowa, Poland)

  • Yevhen Kush

    (Department of Transport Systems and Logistics, O. M. Beketov National University of Urban Economy in Kharkiv, 61002 Kharkiv, Ukraine)

  • Russell Thompson

    (Department of Infrastructure Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Melbourne, VIC 3010, Australia)

Abstract

Engineering human-centric urban transport systems should be carried out using information technology in forecasting traffic and passenger flows. One of the most important objects of urban transport systems’ progress is modeling patterns of transport flows and their distribution on the road network. These patterns are determined by the subjective choice of city residents of traffic routes using public and private transport. This study aimed to form a sequence of stages of modeling transport and passenger flows in human-centric urban transport systems and passenger flows in the human-centric urban intelligent transport systems and to determine the patterns of change to the gravity function of employees of municipal services. It was revealed that the trip distribution function of workers of urban service enterprises can be described by the attributes of the structure of the city, socio-economic data, and attributes characterizing the zones and its residents.

Suggested Citation

  • Natalia Davidich & Andrii Galkin & Yurii Davidich & Tibor Schlosser & Silvia Capayova & Joanna Nowakowska-Grunt & Yevhen Kush & Russell Thompson, 2022. "Intelligent Decision Support System for Modeling Transport and Passenger Flows in Human-Centric Urban Transport Systems," Energies, MDPI, vol. 15(7), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2495-:d:781833
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    References listed on IDEAS

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