Intelligent Decision Support System for Modeling Transport and Passenger Flows in Human-Centric Urban Transport Systems
Natalia Davidich,
Andrii Galkin,
Yurii Davidich,
Tibor Schlosser,
Silvia Capayova,
Joanna Nowakowska-Grunt,
Yevhen Kush,
Russell Thompson
Affiliations
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
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
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.
