Development of Reliable Models of Signal-Controlled Intersections

The paper considers an approach to building various mathematical models for homogeneous groups of intersections manifested through the use of clustering methods. This is because of a significant spread in their traffic capacity, as well as the influence of several random factors. The initial data on...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Glushkov Alexandr, Shepelev Vladimir
Formato:	article
Lenguaje:	EN
Publicado:	Sciendo 2021
Materias:	signal-controlled transport network right turn clustering of intersections statistical significance of differences regression analysis fuzzy logic Transportation and communication K4011-4343
Acceso en línea:	https://doaj.org/article/128e58ff907b4dec8d85cc460d6e34ec
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:128e58ff907b4dec8d85cc460d6e34ec
record_format	dspace
spelling	oai:doaj.org-article:128e58ff907b4dec8d85cc460d6e34ec2021-12-05T14:11:11ZDevelopment of Reliable Models of Signal-Controlled Intersections1407-617910.2478/ttj-2021-0032https://doaj.org/article/128e58ff907b4dec8d85cc460d6e34ec2021-11-01T00:00:00Zhttps://doi.org/10.2478/ttj-2021-0032https://doaj.org/toc/1407-6179The paper considers an approach to building various mathematical models for homogeneous groups of intersections manifested through the use of clustering methods. This is because of a significant spread in their traffic capacity, as well as the influence of several random factors. The initial data on the traffic flow of many intersections was obtained from real-time recorders of the convolutional neural network. As a result of the analysis, we revealed statistically significant differences between the groups of intersections and compiled their linear regression models as a basis for the subsequent formation of generic management decisions. To demonstrate visually the influence of random factors on the traffic capacity of intersections, we built distribution fields based on the fuzzy logic methods for one of the clusters consisting of 14 homogeneous intersections. Modeling was based on the Gaussian type of membership functions as it most fully reflects the random nature of the pedestrian flow and its discontinuity.Glushkov AlexandrShepelev VladimirSciendoarticlesignal-controlled transport networkright turnclustering of intersectionsstatistical significance of differencesregression analysisfuzzy logicTransportation and communicationK4011-4343ENTransport and Telecommunication, Vol 22, Iss 4, Pp 417-424 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	signal-controlled transport network right turn clustering of intersections statistical significance of differences regression analysis fuzzy logic Transportation and communication K4011-4343
spellingShingle	signal-controlled transport network right turn clustering of intersections statistical significance of differences regression analysis fuzzy logic Transportation and communication K4011-4343 Glushkov Alexandr Shepelev Vladimir Development of Reliable Models of Signal-Controlled Intersections
description	The paper considers an approach to building various mathematical models for homogeneous groups of intersections manifested through the use of clustering methods. This is because of a significant spread in their traffic capacity, as well as the influence of several random factors. The initial data on the traffic flow of many intersections was obtained from real-time recorders of the convolutional neural network. As a result of the analysis, we revealed statistically significant differences between the groups of intersections and compiled their linear regression models as a basis for the subsequent formation of generic management decisions. To demonstrate visually the influence of random factors on the traffic capacity of intersections, we built distribution fields based on the fuzzy logic methods for one of the clusters consisting of 14 homogeneous intersections. Modeling was based on the Gaussian type of membership functions as it most fully reflects the random nature of the pedestrian flow and its discontinuity.
format	article
author	Glushkov Alexandr Shepelev Vladimir
author_facet	Glushkov Alexandr Shepelev Vladimir
author_sort	Glushkov Alexandr
title	Development of Reliable Models of Signal-Controlled Intersections
title_short	Development of Reliable Models of Signal-Controlled Intersections
title_full	Development of Reliable Models of Signal-Controlled Intersections
title_fullStr	Development of Reliable Models of Signal-Controlled Intersections
title_full_unstemmed	Development of Reliable Models of Signal-Controlled Intersections
title_sort	development of reliable models of signal-controlled intersections
publisher	Sciendo
publishDate	2021
url	https://doaj.org/article/128e58ff907b4dec8d85cc460d6e34ec
work_keys_str_mv	AT glushkovalexandr developmentofreliablemodelsofsignalcontrolledintersections AT shepelevvladimir developmentofreliablemodelsofsignalcontrolledintersections
_version_	1718371281795022848

Development of Reliable Models of Signal-Controlled Intersections

Ejemplares similares