Probabilistic Maneuver Recognition in Traffic Scenarios

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https://www.ksp.kit.edu/9783731502876
Author(s)
Firl, Jonas
Language
English
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Abstract
In this work an approach is presented to model and recognize traffic maneuvers in terms of interactions between different traffic participants on extra urban roads. Results of the recognition concept are presented and evaluated using different sensor setups and its benefit is outlined by an integration into a software framework in the field of Car-to-Car (C2C) communications. Furthermore, recognition results are used in this work to robustly predict vehicle’s trajectories while driving dynamic
URI
https://directory.doabooks.org/handle/20.500.12854/57005
Keywords
Nachrichtenverifizierung; Trajectory Prediction; Maneuver Recognition; Probabilistic Models; Message Verification; Situationsanalyse; Probabilistische Modellierung; TrajektorienprädiktionSituation Assessment; Fahrmanövererkennung
DOI
10.5445/KSP/1000043680
ISBN
9783731502876
Publisher
KIT Scientific Publishing
Publisher website
http://www.ksp.kit.edu/
Publication date and place
2014
Series
Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie,
Classification
Technology: general issues
Pages
VI, 150 p.
Review type
Full text
Anonymity
All identities known
Reviewer type
Editorial board member; External peer reviewer
Review stage
Pre-publication
Open review
No
Publish responsibility
Books or series editor
Rights
https://creativecommons.org/licenses/by-sa/4.0/
https://creativecommons.org/licenses/by-sa/4.0/
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-sa/4.0/