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Data Fusion considering ‘Negative’ Information for Cooperative Vehicles

dc.contributor.authorTischler, Karin
dc.contributor.authorVogt, Heike S.
dc.contributor.editorHerzog, Otthein
dc.contributor.editorRödiger, Karl-Heinz
dc.contributor.editorRonthaler, Marc
dc.contributor.editorKoschke, Rainer
dc.date.accessioned2019-05-15T09:04:50Z
dc.date.available2019-05-15T09:04:50Z
dc.date.issued2007
dc.description.abstractNegative information provides important additional knowledge that is not exploited for sensor data fusion tasks by default. This paper presents a new approach to incorporate such information about unoccupied, observed areas or missing measurements in the Kalman filtering process. For this purpose, a combination with a grid-based method is proposed to generate a visibility map. This enables a plausibility check and an enhanced understanding for the collaborative perception of the environment with multiple cognitive vehicles. Results from a realistic traffic simulation are presented.en
dc.identifier.isbn978-3-88579-206-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/22470
dc.language.isoen
dc.publisherGesellschaft für Informatik e. V.
dc.relation.ispartofInformatik 2007 – Informatik trifft Logistik – Band 2
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-110
dc.titleData Fusion considering ‘Negative’ Information for Cooperative Vehiclesen
dc.typeText/Conference Paper
gi.citation.endPage154
gi.citation.publisherPlaceBonn
gi.citation.startPage150
gi.conference.date24.-27. September 2007
gi.conference.locationBremen
gi.conference.sessiontitleRegular Research Papers

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