Intelligent Analysis of City Residents Mobility Data for Transport Simulation

Data analysis is one of the key elements in the process of investigating of the transport processes in cities. Despite the large number of scientific papers in this area, the problem of obtaining of the urban population mobility data is not well studied. The most innovative method is the automated gathering of information by obtaining data from GPS trackers, social networks, mobile operators, etc. This paper describes a method for obtaining and processing population mobility open data taken from the Uber Movement source, as well as creating a theoretical model of population mobility based on people density distribution data. The developed method was tested on the example of the city of Amsterdam. In addition, a comparative analysis was carried out using open source data and data computed by developed method. As a result, we get a working method for obtaining population mobility data and analyzing these data.

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Intelligent Analysis of City Residents Mobility Data for Transport Simulation

Semantic Scholar · Computer Science · 2020

Abstract

Data analysis is one of the key elements in the process of investigating of the transport processes in cities. Despite the large number of scientific papers in this area, the problem of obtaining of the urban population mobility data is not well studied. The most innovative method is the automated gathering of information by obtaining data from GPS trackers, social networks, mobile operators, etc. This paper describes a method for obtaining and processing population mobility open data taken from the Uber Movement source, as well as creating a theoretical model of population mobility based on people density distribution data. The developed method was tested on the example of the city of Amsterdam. In addition, a comparative analysis was carried out using open source data and data computed by developed method. As a result, we get a working method for obtaining population mobility data and analyzing these data.

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