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Analysis of the State of Highways of Regional Importance in the Russian Federation
[journal article]

dc.contributor.authorPolyanskaya, Svetlana V.de
dc.contributor.authorUlzetueva, Darima D.de
dc.date.accessioned2025-05-21T12:52:16Z
dc.date.available2025-05-21T12:52:16Z
dc.date.issued2024de
dc.identifier.issn1726-1139de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/102492
dc.description.abstractThe purpose of the article is to analyze the regional road network of the Russian Federation, to identify the main factors affecting its condition depending on the federal district. Recently, investments have improved the situation in the field of repair and construction of regional roads, but the condition of regional roads remains unsatisfactory - about half of all regional roads do not meet regulatory requirements. Based on the analysis of the regional road network, it is necessary to make a decision on the investment of a particular road facility. The article examines the relationship between factors such as the percentage of regional highways that do not meet regulatory requirements and the individual rating of the standard of living. The question is also raised about identifying the most problematic places in the regional road network based on mathematical statistics methods, building dependencies of the share of bad regional roads on the length of federal roads, on the road climate zone, on the gross regional product per capita, on population, on the density of the road network and other factors. The main research methods are correlation and regression analysis. As a result of the study, a statistical analysis of the quality of the highway network of regional significance in the federal districts of the Russian Federation for 2007-2022 was carried out, the main patterns and dependencies of the percentage of roads that do not meet regulatory requirements on the density of the road network, gross regional product, and road climate zone were revealed. Conclusions are obtained that at the moment the state of regional highways and the gross regional product are poorly correlated values. On the contrary, the condition of regional roads strongly correlates with the index of quality of life in the region and the length of federal roads. In the first case, there is a strong positive correlation, in the second - a strong negative one.de
dc.languagerude
dc.subject.ddcStädtebau, Raumplanung, Landschaftsgestaltungde
dc.subject.ddcLandscaping and area planningen
dc.subject.otherregional road network; correlation dependence; regression model; gross regional productde
dc.titleАнализ состояния автомобильных дорог регионального значения Российской Федерацииde
dc.title.alternativeAnalysis of the State of Highways of Regional Importance in the Russian Federationde
dc.description.reviewbegutachtetde
dc.description.reviewrevieweden
dc.source.journalAdministrative Consulting
dc.publisher.countryRUSde
dc.source.issue2de
dc.subject.classozRaumplanung und Regionalforschungde
dc.subject.classozArea Development Planning, Regional Researchen
dc.subject.thesozInvestitionde
dc.subject.thesozinvestmenten
dc.subject.thesozStraßennetzde
dc.subject.thesozroad networken
dc.subject.thesozRusslandde
dc.subject.thesozRussiaen
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10037283
internal.identifier.thesoz10043511
internal.identifier.thesoz10057012
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo160-178de
internal.identifier.classoz20700
internal.identifier.journal2857
internal.identifier.document32
internal.identifier.ddc710
dc.identifier.doihttps://doi.org/10.22394/1726-1139-2024-2-160-178de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review2
dc.subject.classhort20700de
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse
ssoar.urn.registrationfalsede


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