Adaptive, real-time traffic control management
Autor(a) principal: | |
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Data de Publicação: | 2002 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/219395 |
Resumo: | This paper presents an architecture for distributed control systems and its underlying methodological framework. Ideas and concepts of distributed systems, artificial intelligence, and soft computing are merged into a unique architecture to provide cooperation, flexibility, and adaptability required by knowledge processing in intelligent control systems. The distinguished features of the architecture include a local problem solving capability to handle the specific requirements of each part of the system, an evolutionary case-based mechanism to improve performance and optimize controls, the use of linguistic variables as means for information aggregation, and fuzzy set theory to provide local control. A distributed traffic control system application is discussed to provide the details of the architecture, and to emphasize its usefulness. The performance of the distributed control system is compared with conventional control approaches under a variety of traffic situations. © 2002 KSAE. |
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Repositório Institucional da UNESP |
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Adaptive, real-time traffic control managementComputational intelligenceIntelligent controlUrban traffic controlThis paper presents an architecture for distributed control systems and its underlying methodological framework. Ideas and concepts of distributed systems, artificial intelligence, and soft computing are merged into a unique architecture to provide cooperation, flexibility, and adaptability required by knowledge processing in intelligent control systems. The distinguished features of the architecture include a local problem solving capability to handle the specific requirements of each part of the system, an evolutionary case-based mechanism to improve performance and optimize controls, the use of linguistic variables as means for information aggregation, and fuzzy set theory to provide local control. A distributed traffic control system application is discussed to provide the details of the architecture, and to emphasize its usefulness. The performance of the distributed control system is compared with conventional control approaches under a variety of traffic situations. © 2002 KSAE.not available, Rua Alaro Faria de Barros, 1371, casa 22, 13098-393-Campinas-SPPaulista State UniversityPaulista State Universitynot availableUniversidade Estadual Paulista (UNESP)Nakamiti, G.Freitas, R. [UNESP]2022-04-28T18:55:17Z2022-04-28T18:55:17Z2002-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article89-94International Journal of Automotive Technology, v. 3, n. 3, p. 89-94, 2002.1229-9138http://hdl.handle.net/11449/2193952-s2.0-33745589199Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal of Automotive Technologyinfo:eu-repo/semantics/openAccess2022-04-28T18:55:17Zoai:repositorio.unesp.br:11449/219395Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:13:25.822878Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Adaptive, real-time traffic control management |
title |
Adaptive, real-time traffic control management |
spellingShingle |
Adaptive, real-time traffic control management Nakamiti, G. Computational intelligence Intelligent control Urban traffic control |
title_short |
Adaptive, real-time traffic control management |
title_full |
Adaptive, real-time traffic control management |
title_fullStr |
Adaptive, real-time traffic control management |
title_full_unstemmed |
Adaptive, real-time traffic control management |
title_sort |
Adaptive, real-time traffic control management |
author |
Nakamiti, G. |
author_facet |
Nakamiti, G. Freitas, R. [UNESP] |
author_role |
author |
author2 |
Freitas, R. [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
not available Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Nakamiti, G. Freitas, R. [UNESP] |
dc.subject.por.fl_str_mv |
Computational intelligence Intelligent control Urban traffic control |
topic |
Computational intelligence Intelligent control Urban traffic control |
description |
This paper presents an architecture for distributed control systems and its underlying methodological framework. Ideas and concepts of distributed systems, artificial intelligence, and soft computing are merged into a unique architecture to provide cooperation, flexibility, and adaptability required by knowledge processing in intelligent control systems. The distinguished features of the architecture include a local problem solving capability to handle the specific requirements of each part of the system, an evolutionary case-based mechanism to improve performance and optimize controls, the use of linguistic variables as means for information aggregation, and fuzzy set theory to provide local control. A distributed traffic control system application is discussed to provide the details of the architecture, and to emphasize its usefulness. The performance of the distributed control system is compared with conventional control approaches under a variety of traffic situations. © 2002 KSAE. |
publishDate |
2002 |
dc.date.none.fl_str_mv |
2002-01-01 2022-04-28T18:55:17Z 2022-04-28T18:55:17Z |
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 |
International Journal of Automotive Technology, v. 3, n. 3, p. 89-94, 2002. 1229-9138 http://hdl.handle.net/11449/219395 2-s2.0-33745589199 |
identifier_str_mv |
International Journal of Automotive Technology, v. 3, n. 3, p. 89-94, 2002. 1229-9138 2-s2.0-33745589199 |
url |
http://hdl.handle.net/11449/219395 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Journal of Automotive Technology |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
89-94 |
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_ |
1808128775471235072 |