Modeling vehicular traffic networks. Part I
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.physa.2018.06.016 http://hdl.handle.net/11449/176457 |
Resumo: | We propose three models for the traffic of vehicles within a network formed by sites (cities, car-rental agencies, parking lots, etc.) and connected by two-way arteries (roads, highways), that allow forecasting the vehicular flux in a sequence of n consecutive steps, or units of time. An essential approach consists in using, as an a priori information, previous observations and measurements. The formal tools used in our analysis consists in: (1) associating a digraph to the network where the edges correspond to arteries and the vertices with loops represent the sites. (2) From a distribution of vehicles within the network, we construct a matrix from which we derive a stochastic matrix (SM). This matrix becomes the generator of the evolution of the traffic flow. And (3), we use the Perron–Frobenius theory for a formal analysis. We investigate three models: (a) a closed network with conserved number of vehicles; (b) to this network we add an influx and an outflux of vehicles to picture an open system. And (c), we construct a nonlinear model whose formal structure exhibits the existence of several (L) stationary states for the distribution of vehicles at each site, that alternate cyclically with time. Each state represents the traffic for L different moments. These models are hybridized and compared numerically to the effective vehicular traffic in a sector of the city of Tigre, localized in the province of Buenos Aires, Argentina. The empirical data and the traffic modelization are presented in a following paper, referred as Part II. |
id |
UNSP_5df478a69f753967321ec7367e6b615a |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/176457 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Modeling vehicular traffic networks. Part IDigraph theoryLinear and nonlinear modelsMarkov chainNetworkPerron–Frobenius theoryStochastic matrixVehicular trafficWe propose three models for the traffic of vehicles within a network formed by sites (cities, car-rental agencies, parking lots, etc.) and connected by two-way arteries (roads, highways), that allow forecasting the vehicular flux in a sequence of n consecutive steps, or units of time. An essential approach consists in using, as an a priori information, previous observations and measurements. The formal tools used in our analysis consists in: (1) associating a digraph to the network where the edges correspond to arteries and the vertices with loops represent the sites. (2) From a distribution of vehicles within the network, we construct a matrix from which we derive a stochastic matrix (SM). This matrix becomes the generator of the evolution of the traffic flow. And (3), we use the Perron–Frobenius theory for a formal analysis. We investigate three models: (a) a closed network with conserved number of vehicles; (b) to this network we add an influx and an outflux of vehicles to picture an open system. And (c), we construct a nonlinear model whose formal structure exhibits the existence of several (L) stationary states for the distribution of vehicles at each site, that alternate cyclically with time. Each state represents the traffic for L different moments. These models are hybridized and compared numerically to the effective vehicular traffic in a sector of the city of Tigre, localized in the province of Buenos Aires, Argentina. The empirical data and the traffic modelization are presented in a following paper, referred as Part II.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Facultad Regional General Pacheco Universidad Técnica Nacional (UTN)Instituto de Física Teórica Universidade Estadual Paulista (UNESP)Departamento de Física CCET Universidade Federal de São Carlos (UFSCar)Instituto de Física Teórica Universidade Estadual Paulista (UNESP)Universidad Técnica Nacional (UTN)Universidade Estadual Paulista (Unesp)Universidade Federal de São Carlos (UFSCar)Otero, DinoGaletti, Diógenes [UNESP]Mizrahi, Salomon S.2018-12-11T17:20:52Z2018-12-11T17:20:52Z2018-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article97-110application/pdfhttp://dx.doi.org/10.1016/j.physa.2018.06.016Physica A: Statistical Mechanics and its Applications, v. 509, p. 97-110.0378-4371http://hdl.handle.net/11449/17645710.1016/j.physa.2018.06.0162-s2.0-850485626372-s2.0-85048562637.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPhysica A: Statistical Mechanics and its Applications0,773info:eu-repo/semantics/openAccess2024-01-05T06:22:30Zoai:repositorio.unesp.br:11449/176457Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:09:56.039758Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Modeling vehicular traffic networks. Part I |
title |
Modeling vehicular traffic networks. Part I |
spellingShingle |
Modeling vehicular traffic networks. Part I Otero, Dino Digraph theory Linear and nonlinear models Markov chain Network Perron–Frobenius theory Stochastic matrix Vehicular traffic |
title_short |
Modeling vehicular traffic networks. Part I |
title_full |
Modeling vehicular traffic networks. Part I |
title_fullStr |
Modeling vehicular traffic networks. Part I |
title_full_unstemmed |
Modeling vehicular traffic networks. Part I |
title_sort |
Modeling vehicular traffic networks. Part I |
author |
Otero, Dino |
author_facet |
Otero, Dino Galetti, Diógenes [UNESP] Mizrahi, Salomon S. |
author_role |
author |
author2 |
Galetti, Diógenes [UNESP] Mizrahi, Salomon S. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidad Técnica Nacional (UTN) Universidade Estadual Paulista (Unesp) Universidade Federal de São Carlos (UFSCar) |
dc.contributor.author.fl_str_mv |
Otero, Dino Galetti, Diógenes [UNESP] Mizrahi, Salomon S. |
dc.subject.por.fl_str_mv |
Digraph theory Linear and nonlinear models Markov chain Network Perron–Frobenius theory Stochastic matrix Vehicular traffic |
topic |
Digraph theory Linear and nonlinear models Markov chain Network Perron–Frobenius theory Stochastic matrix Vehicular traffic |
description |
We propose three models for the traffic of vehicles within a network formed by sites (cities, car-rental agencies, parking lots, etc.) and connected by two-way arteries (roads, highways), that allow forecasting the vehicular flux in a sequence of n consecutive steps, or units of time. An essential approach consists in using, as an a priori information, previous observations and measurements. The formal tools used in our analysis consists in: (1) associating a digraph to the network where the edges correspond to arteries and the vertices with loops represent the sites. (2) From a distribution of vehicles within the network, we construct a matrix from which we derive a stochastic matrix (SM). This matrix becomes the generator of the evolution of the traffic flow. And (3), we use the Perron–Frobenius theory for a formal analysis. We investigate three models: (a) a closed network with conserved number of vehicles; (b) to this network we add an influx and an outflux of vehicles to picture an open system. And (c), we construct a nonlinear model whose formal structure exhibits the existence of several (L) stationary states for the distribution of vehicles at each site, that alternate cyclically with time. Each state represents the traffic for L different moments. These models are hybridized and compared numerically to the effective vehicular traffic in a sector of the city of Tigre, localized in the province of Buenos Aires, Argentina. The empirical data and the traffic modelization are presented in a following paper, referred as Part II. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-11T17:20:52Z 2018-12-11T17:20:52Z 2018-11-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.physa.2018.06.016 Physica A: Statistical Mechanics and its Applications, v. 509, p. 97-110. 0378-4371 http://hdl.handle.net/11449/176457 10.1016/j.physa.2018.06.016 2-s2.0-85048562637 2-s2.0-85048562637.pdf |
url |
http://dx.doi.org/10.1016/j.physa.2018.06.016 http://hdl.handle.net/11449/176457 |
identifier_str_mv |
Physica A: Statistical Mechanics and its Applications, v. 509, p. 97-110. 0378-4371 10.1016/j.physa.2018.06.016 2-s2.0-85048562637 2-s2.0-85048562637.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Physica A: Statistical Mechanics and its Applications 0,773 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
97-110 application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129398955573248 |