Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving

This article presents a machine learning-based technique to build a predictive model and generate rules of action to allow autonomous vehicles to perform roundabout maneuvers. The approach consists of building a predictive model of vehicle speeds and steering angles based on collected data related t...

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Authors: García Cuenca, Laura, Sánchez Soriano, Javier, Puertas Sanz, Enrique, Fernández Andrés, Javier, Aliane, Nourdine
Format: article
Publication Date:2019
Country:España
Institution:Universidad Europea (UEM)
Repository:ABACUS. Repositorio de Producción Científica
Language:English
OAI Identifier:oai:abacus.universidadeuropea.com:11268/8000
Online Access:http://hdl.handle.net/11268/8000
Access Level:Open access
Keyword:Inteligencia artificial
Aprendizaje automático
Coches
Vehículo automotor
Autoaprendizaje
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oai_identifier_str oai:abacus.universidadeuropea.com:11268/8000
network_acronym_str ES
network_name_str España
repository_id_str
spelling Machine Learning Techniques for Undertaking Roundabouts in Autonomous DrivingGarcía Cuenca, LauraSánchez Soriano, JavierPuertas Sanz, EnriqueFernández Andrés, JavierAliane, NourdineInteligencia artificialAprendizaje automáticoCochesVehículo automotorInteligencia artificialAutoaprendizajeThis article presents a machine learning-based technique to build a predictive model and generate rules of action to allow autonomous vehicles to perform roundabout maneuvers. The approach consists of building a predictive model of vehicle speeds and steering angles based on collected data related to driver–vehicle interactions and other aggregated data intrinsic to the traffic environment, such as roundabout geometry and the number of lanes obtained from Open-Street-Maps and offline video processing. The study systematically generates rules of action regarding the vehicle speed and steering angle required for autonomous vehicles to achieve complete roundabout maneuvers. Supervised learning algorithms like the support vector machine, linear regression, and deep learning are used to form the predictive models.20192019-05-2520192019-01-0120192019-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/11268/8000reponame:ABACUS. Repositorio de Producción Científicainstname:Universidad Europea (UEM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:abacus.universidadeuropea.com:11268/80002026-06-11T12:41:27Z
dc.title.none.fl_str_mv Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
title Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
spellingShingle Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
García Cuenca, Laura
Inteligencia artificial
Aprendizaje automático
Coches
Vehículo automotor
Inteligencia artificial
Autoaprendizaje
title_short Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
title_full Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
title_fullStr Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
title_full_unstemmed Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
title_sort Machine Learning Techniques for Undertaking Roundabouts in Autonomous Driving
dc.creator.none.fl_str_mv García Cuenca, Laura
Sánchez Soriano, Javier
Puertas Sanz, Enrique
Fernández Andrés, Javier
Aliane, Nourdine
author García Cuenca, Laura
author_facet García Cuenca, Laura
Sánchez Soriano, Javier
Puertas Sanz, Enrique
Fernández Andrés, Javier
Aliane, Nourdine
author_role author
author2 Sánchez Soriano, Javier
Puertas Sanz, Enrique
Fernández Andrés, Javier
Aliane, Nourdine
author2_role author
author
author
author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv Inteligencia artificial
Aprendizaje automático
Coches
Vehículo automotor
Inteligencia artificial
Autoaprendizaje
topic Inteligencia artificial
Aprendizaje automático
Coches
Vehículo automotor
Inteligencia artificial
Autoaprendizaje
description This article presents a machine learning-based technique to build a predictive model and generate rules of action to allow autonomous vehicles to perform roundabout maneuvers. The approach consists of building a predictive model of vehicle speeds and steering angles based on collected data related to driver–vehicle interactions and other aggregated data intrinsic to the traffic environment, such as roundabout geometry and the number of lanes obtained from Open-Street-Maps and offline video processing. The study systematically generates rules of action regarding the vehicle speed and steering angle required for autonomous vehicles to achieve complete roundabout maneuvers. Supervised learning algorithms like the support vector machine, linear regression, and deep learning are used to form the predictive models.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-05-25
2019
2019-01-01
2019
2019-01-01
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 http://hdl.handle.net/11268/8000
url http://hdl.handle.net/11268/8000
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
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
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
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:ABACUS. Repositorio de Producción Científica
instname:Universidad Europea (UEM)
instname_str Universidad Europea (UEM)
reponame_str ABACUS. Repositorio de Producción Científica
collection ABACUS. Repositorio de Producción Científica
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869413146357137408
score 15,300719

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