Inferenz von Kreuzungsinformationen aus Flottendaten

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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Bibliographic Details
Main Author: Ruhhammer, Christian (auth)
Format: Electronic Book Chapter
Published: KIT Scientific Publishing 2017
Series:Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
Subjects:
Technology: general issues
Maschinelles Lernen
Flottendaten
Intersection Information
Lichtsignalanlage
Automated Map Creation
Fleet Data
Traffic Light
Automatisierte Kartenerstellung
Kreuzungsinformationen
Machine Learning
Online Access:DOAB: download the publication
DOAB: description of the publication
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Description
Summary: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.
Physical Description:1 electronic resource (XIX, 171 p. p.)
ISBN:KSP/1000073704
9783731507215
Access:Open Access

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