Probabilistische Vorhersage von Fahrstreifenwechseln für hochautomatisiertes Fahren auf Autobahnen

A concept for time-related forecasts of lane change maneuvers in highway scenarios is presented within the present work. Automated driving systems rely on understanding the driving environment to fulfill their driving task transparently and safely. This involves the perception of the driving environ...

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Bibliographic Details
Main Author: Weiser, Andreas (auth)
Format: Electronic Book Chapter
Published: KIT Scientific Publishing 2019
Series:Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
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Online Access:DOAB: download the publication
DOAB: description of the publication
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245 1 0 |a Probabilistische Vorhersage von Fahrstreifenwechseln für hochautomatisiertes Fahren auf Autobahnen 
260 |b KIT Scientific Publishing  |c 2019 
300 |a 1 electronic resource (XI, 232 p. p.) 
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520 |a A concept for time-related forecasts of lane change maneuvers in highway scenarios is presented within the present work. Automated driving systems rely on understanding the driving environment to fulfill their driving task transparently and safely. This involves the perception of the driving environment as well as its interpretation to detect and predict driving maneuvers of road users. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-sa/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-sa/4.0/ 
546 |a German 
650 7 |a Technology: general issues  |2 bicssc 
653 |a Fahrstreifenwechsel 
653 |a Automatisches Fahren 
653 |a Maschinelles Lernen 
653 |a dynamic Bayesian networks 
653 |a Dynamische Bayes'sche Netzwerke 
653 |a lane change 
653 |a machine learning 
653 |a automated driving 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/57010  |7 0  |z DOAB: description of the publication