A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads

This paper presents an intelligent speed adaption system for vehicles on conventional roads. The fuzzy logic based expert system outputs a recommended speed to ensure both safety and passenger comfort. This intelligent system includes geometrical features of the road, as well as subjective perceptio...

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Detalles Bibliográficos
Autores: Barreno, Felipe, Santos Peñas, Matilde, Romana, Manuel G.
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/71562
Acceso en línea:https://hdl.handle.net/20.500.14352/71562
Access Level:acceso abierto
Palabra clave:adaptive cruise control
expert system
fuzzy logic
industry 4.0
intelligent speed recommender
knowledge
two-lane roads
vehicle speed
Sistemas expertos
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oai_identifier_str oai:docta.ucm.es:20.500.14352/71562
network_acronym_str ES
network_name_str España
repository_id_str
spelling A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roadsBarreno, FelipeSantos Peñas, MatildeRomana, Manuel G.adaptive cruise controlexpert systemfuzzy logicindustry 4.0intelligent speed recommenderknowledgetwo-lane roadsvehicle speedSistemas expertosThis paper presents an intelligent speed adaption system for vehicles on conventional roads. The fuzzy logic based expert system outputs a recommended speed to ensure both safety and passenger comfort. This intelligent system includes geometrical features of the road, as well as subjective perceptions of the drivers. It has been developed and checked with real data that were measured with an instrumental system incorporated in a vehicle, on several two-lane roads located in the Madrid Region, Spain. Along with the road geometrical characteristics, other input variables to the system are external factors, such as weather conditions, distance to the preceding vehicle, tire pressure, and other subjective criteria, such as the desired comfort level, selected by the driver. The expert system output is the most suitable speed for the specific road type, considering real factors that may modify the category of the road and thus, the appropriate speed. This information could be added to the adaptive cruise control of the vehicle. The recommended speed can be a very useful input for both, drivers and the autonomous vehicles, to improve safety on the road system.WileyUniversidad Complutense de Madrid20222022-05-2720222022-05-27journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/71562reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución-NoComercial-SinDerivadas 3.0 Españahttps://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/715622026-06-02T12:44:21Z
dc.title.none.fl_str_mv A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
title A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
spellingShingle A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
Barreno, Felipe
adaptive cruise control
expert system
fuzzy logic
industry 4.0
intelligent speed recommender
knowledge
two-lane roads
vehicle speed
Sistemas expertos
title_short A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
title_full A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
title_fullStr A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
title_full_unstemmed A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
title_sort A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads
dc.creator.none.fl_str_mv Barreno, Felipe
Santos Peñas, Matilde
Romana, Manuel G.
author Barreno, Felipe
author_facet Barreno, Felipe
Santos Peñas, Matilde
Romana, Manuel G.
author_role author
author2 Santos Peñas, Matilde
Romana, Manuel G.
author2_role author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv adaptive cruise control
expert system
fuzzy logic
industry 4.0
intelligent speed recommender
knowledge
two-lane roads
vehicle speed
Sistemas expertos
topic adaptive cruise control
expert system
fuzzy logic
industry 4.0
intelligent speed recommender
knowledge
two-lane roads
vehicle speed
Sistemas expertos
description This paper presents an intelligent speed adaption system for vehicles on conventional roads. The fuzzy logic based expert system outputs a recommended speed to ensure both safety and passenger comfort. This intelligent system includes geometrical features of the road, as well as subjective perceptions of the drivers. It has been developed and checked with real data that were measured with an instrumental system incorporated in a vehicle, on several two-lane roads located in the Madrid Region, Spain. Along with the road geometrical characteristics, other input variables to the system are external factors, such as weather conditions, distance to the preceding vehicle, tire pressure, and other subjective criteria, such as the desired comfort level, selected by the driver. The expert system output is the most suitable speed for the specific road type, considering real factors that may modify the category of the road and thus, the appropriate speed. This information could be added to the adaptive cruise control of the vehicle. The recommended speed can be a very useful input for both, drivers and the autonomous vehicles, to improve safety on the road system.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-05-27
2022
2022-05-27
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/71562
url https://hdl.handle.net/20.500.14352/71562
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-SinDerivadas 3.0 España
https://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-SinDerivadas 3.0 España
https://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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