Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from Poland
A method is proposed for forecasting traffic intensity at the border of an agglomeration’s core, using demographic data such as amount (number) and structure of population and housing in the surrounding (suburban) area. Relationships between groups of variables are analyzed by calibrating traffic an...
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MDPI AG
2021-01-01
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Online Access: | https://www.mdpi.com/2073-445X/10/1/47 |
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author | Maciej Kruszyna Przemysław Śleszyński Jeremi Rychlewski |
author_facet | Maciej Kruszyna Przemysław Śleszyński Jeremi Rychlewski |
author_sort | Maciej Kruszyna |
collection | DOAJ |
description | A method is proposed for forecasting traffic intensity at the border of an agglomeration’s core, using demographic data such as amount (number) and structure of population and housing in the surrounding (suburban) area. Relationships between groups of variables are analyzed by calibrating traffic and demographic models for a selected agglomeration in Poland. The choice of Poland is justified by an intensive suburbanization process that took place during the transition from a centrally controlled market to a free market economy after 1989, such research being quite novel and original for this country. Three assumptions concerning this research methodology (concerning how to specify the research area and parameters characterizing traffic and population) were formulated and tested. Models (dependencies) acquired this way were tested in another Polish agglomeration of similar size, yielding similar results. Very high correlations between characteristic groups of variables were indicated. The best correlation occurred between an intensity of cars leaving the center of an agglomeration in the afternoon rush hour (as a traffic group variable), with the total population, the number of economically active people, and the number of dwellings in the surrounding areas (being population group variables). A novel way of specifying the range of the surrounding areas influencing the main city traffic was proposed. The results obtained and the models constructed should be applicable for other agglomerations, since the universality of the observed phenomena and their relationships are expected. |
first_indexed | 2024-03-10T13:27:16Z |
format | Article |
id | doaj.art-9d29695da14742bfbd6c768313073b57 |
institution | Directory Open Access Journal |
issn | 2073-445X |
language | English |
last_indexed | 2024-03-10T13:27:16Z |
publishDate | 2021-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Land |
spelling | doaj.art-9d29695da14742bfbd6c768313073b572023-11-21T08:54:40ZengMDPI AGLand2073-445X2021-01-011014710.3390/land10010047Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from PolandMaciej Kruszyna0Przemysław Śleszyński1Jeremi Rychlewski2Faculty of Civil Engineering, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, PolandInstitute of Geography and Spatial Organization, Polish Academy of Sciences, Twarda 51/55, 00-818 Warsaw, PolandFaculty of Civil and Transport Engineering, Poznań University of Technology, Piotrowo 3, 60-965 Poznań, PolandA method is proposed for forecasting traffic intensity at the border of an agglomeration’s core, using demographic data such as amount (number) and structure of population and housing in the surrounding (suburban) area. Relationships between groups of variables are analyzed by calibrating traffic and demographic models for a selected agglomeration in Poland. The choice of Poland is justified by an intensive suburbanization process that took place during the transition from a centrally controlled market to a free market economy after 1989, such research being quite novel and original for this country. Three assumptions concerning this research methodology (concerning how to specify the research area and parameters characterizing traffic and population) were formulated and tested. Models (dependencies) acquired this way were tested in another Polish agglomeration of similar size, yielding similar results. Very high correlations between characteristic groups of variables were indicated. The best correlation occurred between an intensity of cars leaving the center of an agglomeration in the afternoon rush hour (as a traffic group variable), with the total population, the number of economically active people, and the number of dwellings in the surrounding areas (being population group variables). A novel way of specifying the range of the surrounding areas influencing the main city traffic was proposed. The results obtained and the models constructed should be applicable for other agglomerations, since the universality of the observed phenomena and their relationships are expected.https://www.mdpi.com/2073-445X/10/1/47agglomerationsuburbanizationurban sprawlspatial chaosroad traffic volumestraffic growth factors |
spellingShingle | Maciej Kruszyna Przemysław Śleszyński Jeremi Rychlewski Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from Poland Land agglomeration suburbanization urban sprawl spatial chaos road traffic volumes traffic growth factors |
title | Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from Poland |
title_full | Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from Poland |
title_fullStr | Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from Poland |
title_full_unstemmed | Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from Poland |
title_short | Dependencies between Demographic Urbanization and the Agglomeration Road Traffic Volumes: Evidence from Poland |
title_sort | dependencies between demographic urbanization and the agglomeration road traffic volumes evidence from poland |
topic | agglomeration suburbanization urban sprawl spatial chaos road traffic volumes traffic growth factors |
url | https://www.mdpi.com/2073-445X/10/1/47 |
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