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Vehicle Localization Using Infrastructure Sensing

Digel, Holger; Gabb, Michael; Erlinghagen, Lukas; Sax, Eric

Abstract (englisch):

Infrastructure supported autonomous driving is getting in the focus of current research. In this work, we investigated the usage of a traffic monitoring infrastructure combined with the environmental model of an autonomous driving vehicle for localization. The forwarded environmental model of the infrastructure contains tracked road users, but the used tracking algorithm is unknown. The result is based on a two-stage transformation process with optimized fusion and tracking by a Kalman filter. Experiments show, that the algorithm provides a consistent localization at the first time step.

DOI: 10.1007/978-3-030-65871-7_1
Zitationen: 1
Zitationen: 1
Zugehörige Institution(en) am KIT Institut für Technik der Informationsverarbeitung (ITIV)
Publikationstyp Buchaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISBN: 978-3-030-65871-7
ISSN: 2196-5544, 2196-5552
KITopen-ID: 1000128832
Erschienen in Intelligent System Solutions for Auto Mobility and Beyond : Advanced Microsystems for Automotive Applications 2020. Ed: C. Zachäus,
Auflage 1st ed.
Verlag Springer International Publishing
Seiten 3–13
Serie Lecture Notes in Mobility
Vorab online veröffentlicht am 11.12.2020
Schlagwörter Localization, Infrastructure sensors, Intelligent vehicles, MEC-View project, Roadside sensors, MEC-Server, Automated driving, Information fusion, Kalman filter, Pose estimation, Optimized fusion
Nachgewiesen in Dimensions
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