MODEL OF POPULATION MIGRATION IN AGGLOMERATIONS WITHIN THE FRAMEWORK OF THE “SMART CITY” PARADIGM
Journal Title: Scientific Journal of Astana IT University - Year 2020, Vol 4, Issue 4
Abstract
The urban agglomeration is a multitude of united settlements according to economic, labor, cultural, household, and recreational characteristics. Agglomeration is perceived as an integral territorial union; therefore, it is essential to consider it in the framework of the “smart city” paradigm. All movements of the population within the agglomeration, despite the seeming chaos, can be presented systematically and identified certain patterns. These regularities will optimize the city’s infrastructure by shaping its transport system in such a way that it will be possible to exclude potentially emergency sections on the roads and reduce the traffic load on highways. In order to optimize the infrastructure of the agglomeration, the existing model of transport networks and population movement (migration) within it are considered. The article presents an analysis of the “smart city” paradigm, describes its multidimensional structure and levels on which the urban infrastructure is built, and provides mathematical models based on which the agglomeration transport system is formed. To describe the model of population movement within the framework of an agglomeration, a data warehouse is considered, which contains information about an urban transport network comprising a set of points and communications laid between them. Based on this transport network, a route network is formed, which is a collection of all transport routes. The paper describes a model of a transport and distribution system taking into account temporal and spatial characteristics and a model of an intelligent city transport system based on a hyper network. The models of transport systems used foreign countries’ experience, where there is a tendency to improve navigation and monitoring systems within the transport intelligent system of the city, are described.
Authors and Affiliations
Ye. Kazantseva, G. Danenova
Keywords
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- EP ID EP711941
- DOI 10.37943/AITU.2020.26.65.009
- Views 63
- Downloads 0
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