Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren

In order to establish general principles in the topic of motion planning for fully-automated driving, an intuitive problem statement in the form of an Euler–Lagrange Model is derived and transformed into a corresponding Hidden Markov Model for global optimization. Geometric and topologic considerati...

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Autores:
Tipo de recurso:
Book
Fecha de publicación:
2018
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
ger
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/17591
Acceso en línea:
https://directory.doabooks.org/handle/20.500.12854/48490
http://hdl.handle.net/20.500.12010/17591
Palabra clave:
SPARC
Probabilistic environment modelling
Optimierung
SPARC
Probabilistic environment modelling
Optimierung
Rights
License
Abierto (Texto Completo)
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dc.title.spa.fl_str_mv Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
title Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
spellingShingle Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
SPARC
Probabilistic environment modelling
Optimierung
SPARC
Probabilistic environment modelling
Optimierung
title_short Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
title_full Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
title_fullStr Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
title_full_unstemmed Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
title_sort Geometrie und Topologie von Trajektorienoptimierung für vollautomatisches Fahren
dc.subject.spa.fl_str_mv SPARC
Probabilistic environment modelling
Optimierung
topic SPARC
Probabilistic environment modelling
Optimierung
SPARC
Probabilistic environment modelling
Optimierung
dc.subject.lemb.spa.fl_str_mv SPARC
Probabilistic environment modelling
Optimierung
description In order to establish general principles in the topic of motion planning for fully-automated driving, an intuitive problem statement in the form of an Euler–Lagrange Model is derived and transformed into a corresponding Hidden Markov Model for global optimization. Geometric and topologic considerations lead to a probabilistic environment modelling in combination with the C² model and result in general conclusions about the structure of traffic situations.
publishDate 2018
dc.date.created.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2021-02-22T19:38:52Z
dc.date.available.none.fl_str_mv 2021-02-22T19:38:52Z
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2f33
format http://purl.org/coar/resource_type/c_2f33
dc.identifier.isbn.none.fl_str_mv 9783731508328
dc.identifier.other.none.fl_str_mv https://directory.doabooks.org/handle/20.500.12854/48490
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/17591
dc.identifier.doi.none.fl_str_mv 10.5445/KSP/1000085281
identifier_str_mv 9783731508328
10.5445/KSP/1000085281
url https://directory.doabooks.org/handle/20.500.12854/48490
http://hdl.handle.net/20.500.12010/17591
dc.language.iso.spa.fl_str_mv ger
language ger
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Abierto (Texto Completo)
dc.rights.creativecommons.none.fl_str_mv https://creativecommons.org/licenses/by-sa/4.0/
rights_invalid_str_mv Abierto (Texto Completo)
https://creativecommons.org/licenses/by-sa/4.0/
http://purl.org/coar/access_right/c_abf2
dc.format.extent.spa.fl_str_mv XVII, 253 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv KIT Scientific Publishing
institution Universidad de Bogotá Jorge Tadeo Lozano
bitstream.url.fl_str_mv https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17591/2/license.txt
https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17591/1/978-3-7315-0832-8.pdf
https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17591/3/978-3-7315-0832-8.pdf.jpg
bitstream.checksum.fl_str_mv abceeb1c943c50d3343516f9dbfc110f
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bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
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repository.name.fl_str_mv Repositorio Institucional - Universidad Jorge Tadeo Lozano
repository.mail.fl_str_mv expeditio@utadeo.edu.co
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spelling 2021-02-22T19:38:52Z2021-02-22T19:38:52Z20189783731508328https://directory.doabooks.org/handle/20.500.12854/48490http://hdl.handle.net/20.500.12010/1759110.5445/KSP/1000085281In order to establish general principles in the topic of motion planning for fully-automated driving, an intuitive problem statement in the form of an Euler–Lagrange Model is derived and transformed into a corresponding Hidden Markov Model for global optimization. Geometric and topologic considerations lead to a probabilistic environment modelling in combination with the C² model and result in general conclusions about the structure of traffic situations.XVII, 253 páginasapplication/pdfgerKIT Scientific PublishingSPARCProbabilistic environment modellingOptimierungSPARCProbabilistic environment modellingOptimierungGeometrie und Topologie von Trajektorienoptimierung für vollautomatisches FahrenAbierto (Texto Completo)https://creativecommons.org/licenses/by-sa/4.0/http://purl.org/coar/access_right/c_abf2http://purl.org/coar/resource_type/c_2f33Ruf, MiriamLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17591/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open accessORIGINAL978-3-7315-0832-8.pdf978-3-7315-0832-8.pdfVer documentoapplication/pdf20195135https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17591/1/978-3-7315-0832-8.pdf1f9b70bc2efe458b272f05ac741e70c1MD51open accessTHUMBNAIL978-3-7315-0832-8.pdf.jpg978-3-7315-0832-8.pdf.jpgIM Thumbnailimage/jpeg14605https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17591/3/978-3-7315-0832-8.pdf.jpg52f51fbfbead0ce858e84ba3af827ff2MD53open access20.500.12010/17591oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/175912021-02-22 14:39:50.847open accessRepositorio Institucional - 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