Cities road networks

Road network infrastructure is the basis of any urban area. This article compares the structural characteristics (meshedness coefficient, clustering coefficient) road networks of Moscow center (Old Moscow), formed as a result of self-organization and roads near Leninsky Prospekt (postwar Moscow), wh...

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Main Authors: Igor Alexeevich Yevin, Vladislav Viktorovich Komarov, Marina Sergeevna Popova, Denis Konstantinovich Marchenko, Anastasiya Jurevna Samsonova
Format: Article
Language:Russian
Published: Institute of Computer Science 2016-10-01
Series:Компьютерные исследования и моделирование
Subjects:
Online Access:http://crm.ics.org.ru/uploads/crmissues/crm_2016_5/2016.08.05.pdf
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spelling doaj-c67488a4eaeb48fc86cac13bd69ae2542020-11-25T01:30:20ZrusInstitute of Computer ScienceКомпьютерные исследования и моделирование2076-76332077-68532016-10-018577578610.20537/2076-7633-2016-8-5-775-7862501Cities road networksIgor Alexeevich YevinVladislav Viktorovich KomarovMarina Sergeevna PopovaDenis Konstantinovich MarchenkoAnastasiya Jurevna SamsonovaRoad network infrastructure is the basis of any urban area. This article compares the structural characteristics (meshedness coefficient, clustering coefficient) road networks of Moscow center (Old Moscow), formed as a result of self-organization and roads near Leninsky Prospekt (postwar Moscow), which was result of cetralized planning. Data for the construction of road networks in the form of graphs taken from the Internet resource OpenStreetMap, allowing to accurately identify the coordinates of the intersections. According to the characteristics of the calculated Moscow road networks areas the cities with road network which have a similar structure to the two Moscow areas was found in foreign publications. Using the dual representation of road networks of centers of Moscow and St. Petersburg, studied the information and cognitive features of navigation in these tourist areas of the two capitals. In the construction of the dual graph of the studied areas were not taken into account the different types of roads (unidirectional or bi-directional traffic, etc), that is built dual graphs are undirected. Since the road network in the dual representation are described by a power law distribution of vertices on the number of edges (scale-free networks), exponents of these distributions were calculated. It is shown that the information complexity of the dual graph of the center of Moscow exceeds the cognitive threshold 8.1 bits, and the same feature for the center of St. Petersburg below this threshold, because the center of St. Petersburg road network was created on the basis of planning and therefore more easy to navigate. In conclusion, using the methods of statistical mechanics (the method of calculating the partition functions) for the road network of some Russian cities the Gibbs entropy were calculated. It was found that with the road network size increasing their entropy decreases. We discuss the problem of studying the evolution of urban infrastructure networks of different nature (public transport, supply , communication networks, etc.), which allow us to more deeply explore and understand the fundamental laws of urbanization.http://crm.ics.org.ru/uploads/crmissues/crm_2016_5/2016.08.05.pdfmeshedness coefficientbetweenness centralitythe dual representation of the networknavigationthe Gibbs entropy
collection DOAJ
language Russian
format Article
sources DOAJ
author Igor Alexeevich Yevin
Vladislav Viktorovich Komarov
Marina Sergeevna Popova
Denis Konstantinovich Marchenko
Anastasiya Jurevna Samsonova
spellingShingle Igor Alexeevich Yevin
Vladislav Viktorovich Komarov
Marina Sergeevna Popova
Denis Konstantinovich Marchenko
Anastasiya Jurevna Samsonova
Cities road networks
Компьютерные исследования и моделирование
meshedness coefficient
betweenness centrality
the dual representation of the network
navigation
the Gibbs entropy
author_facet Igor Alexeevich Yevin
Vladislav Viktorovich Komarov
Marina Sergeevna Popova
Denis Konstantinovich Marchenko
Anastasiya Jurevna Samsonova
author_sort Igor Alexeevich Yevin
title Cities road networks
title_short Cities road networks
title_full Cities road networks
title_fullStr Cities road networks
title_full_unstemmed Cities road networks
title_sort cities road networks
publisher Institute of Computer Science
series Компьютерные исследования и моделирование
issn 2076-7633
2077-6853
publishDate 2016-10-01
description Road network infrastructure is the basis of any urban area. This article compares the structural characteristics (meshedness coefficient, clustering coefficient) road networks of Moscow center (Old Moscow), formed as a result of self-organization and roads near Leninsky Prospekt (postwar Moscow), which was result of cetralized planning. Data for the construction of road networks in the form of graphs taken from the Internet resource OpenStreetMap, allowing to accurately identify the coordinates of the intersections. According to the characteristics of the calculated Moscow road networks areas the cities with road network which have a similar structure to the two Moscow areas was found in foreign publications. Using the dual representation of road networks of centers of Moscow and St. Petersburg, studied the information and cognitive features of navigation in these tourist areas of the two capitals. In the construction of the dual graph of the studied areas were not taken into account the different types of roads (unidirectional or bi-directional traffic, etc), that is built dual graphs are undirected. Since the road network in the dual representation are described by a power law distribution of vertices on the number of edges (scale-free networks), exponents of these distributions were calculated. It is shown that the information complexity of the dual graph of the center of Moscow exceeds the cognitive threshold 8.1 bits, and the same feature for the center of St. Petersburg below this threshold, because the center of St. Petersburg road network was created on the basis of planning and therefore more easy to navigate. In conclusion, using the methods of statistical mechanics (the method of calculating the partition functions) for the road network of some Russian cities the Gibbs entropy were calculated. It was found that with the road network size increasing their entropy decreases. We discuss the problem of studying the evolution of urban infrastructure networks of different nature (public transport, supply , communication networks, etc.), which allow us to more deeply explore and understand the fundamental laws of urbanization.
topic meshedness coefficient
betweenness centrality
the dual representation of the network
navigation
the Gibbs entropy
url http://crm.ics.org.ru/uploads/crmissues/crm_2016_5/2016.08.05.pdf
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