Inferenz von Kreuzungsinformationen aus Flottendaten

The next generation of driver assistance systems and highly automated driving functions are based on digital maps. In order to meet the high requirements on the correctness and up-to-dateness of this information, this work presents new automated methods to extract up-to-date map information from fle...

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Egile nagusia: Ruhhammer, Christian
Formatua: Online
Hizkuntza:alemana
Argitaratua: KIT Scientific Publishing 2021
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Sarrera elektronikoa:34272
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author Ruhhammer, Christian
author_browse Ruhhammer, Christian
author_facet Ruhhammer, Christian
author_sort Ruhhammer, Christian
collection Directory of Open Access Books
description The next generation of driver assistance systems and highly automated driving functions are based on digital maps. In order to meet the high requirements on the correctness and up-to-dateness of this information, this work presents new automated methods to extract up-to-date map information from fleet data. The focus is on the inference of static intersection information from fleet data through machine learning and statistical methods.
format Online
id doab-20.500.12854ir-50183
institution Directory of Open Access Books
language ger
publishDate 2021
publishDateRange 2021
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publisherStr KIT Scientific Publishing
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spelling doab-20.500.12854ir-501832024-04-09T23:15:32Z Inferenz von Kreuzungsinformationen aus Flottendaten Ruhhammer, Christian T1-995 Maschinelles Lernen Flottendaten Intersection Information Lichtsignalanlage Automated Map Creation Fleet Data Traffic Light Automatisierte Kartenerstellung Kreuzungsinformationen Machine Learning thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues The next generation of driver assistance systems and highly automated driving functions are based on digital maps. In order to meet the high requirements on the correctness and up-to-dateness of this information, this work presents new automated methods to extract up-to-date map information from fleet data. The focus is on the inference of static intersection information from fleet data through machine learning and statistical methods. 2021-02-11T16:10:14Z 2021-02-11T16:10:14Z 2019-07-30 20:01:57 2017 book 34272 16134214 9783731507215 https://directory.doabooks.org/handle/20.500.12854/50183 ger Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie image/jpeg Attribution-ShareAlike 4.0 International https://www.ksp.kit.edu/9783731507215 KIT Scientific Publishing 10.5445/KSP/1000073704 10.5445/KSP/1000073704 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731507215 XIX, 171 p. open access
spellingShingle T1-995
Maschinelles Lernen
Flottendaten
Intersection Information
Lichtsignalanlage
Automated Map Creation
Fleet Data
Traffic Light
Automatisierte Kartenerstellung
Kreuzungsinformationen
Machine Learning
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Ruhhammer, Christian
Inferenz von Kreuzungsinformationen aus Flottendaten
title Inferenz von Kreuzungsinformationen aus Flottendaten
title_full Inferenz von Kreuzungsinformationen aus Flottendaten
title_fullStr Inferenz von Kreuzungsinformationen aus Flottendaten
title_full_unstemmed Inferenz von Kreuzungsinformationen aus Flottendaten
title_short Inferenz von Kreuzungsinformationen aus Flottendaten
title_sort inferenz von kreuzungsinformationen aus flottendaten
topic T1-995
Maschinelles Lernen
Flottendaten
Intersection Information
Lichtsignalanlage
Automated Map Creation
Fleet Data
Traffic Light
Automatisierte Kartenerstellung
Kreuzungsinformationen
Machine Learning
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
topic_facet T1-995
Maschinelles Lernen
Flottendaten
Intersection Information
Lichtsignalanlage
Automated Map Creation
Fleet Data
Traffic Light
Automatisierte Kartenerstellung
Kreuzungsinformationen
Machine Learning
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
url 34272
work_keys_str_mv AT ruhhammerchristian inferenzvonkreuzungsinformationenausflottendaten