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AutorWestenberger, Antjedc.contributor.author
Aufnahmedatum2016-03-15T10:39:55Zdc.date.accessioned
In OPARU verfügbar seit2016-03-15T10:39:55Zdc.date.available
Jahr der Erstellung2014dc.date.created
ZusammenfassungAutomated driving systems must reliably and quickly perceive the environment in which they operate. Multi-sensor fusion is a suitable means to combine the advantages of different measurement techniques. However, fusion of different sensors may lead to out-of-sequence measurements (OOSM), i.e., asynchronous measurements where the original order of the measurements is lost. High-performance out-of-sequence algorithms are therefore needed that do not depend on the order of the measurements. In addition, existence probabilities can increase the reliability of the fusion system, especially in safety critical applications. A well-known approach to include existence probabilities in tracking is the Joint Integrated Probabilistic Data Association (JIPDA) filter. This algorithm has proven very reliable in practice. However, the handling of out-of-sequence measurements in JIPDA has been an unsolved problem up until now. This work therefore derives two new algorithms that can handle out-of-sequence measurements in state estimation as well as in existence estimation with JIPDA. A prototype Mercedes test vehicle is used for sensor fusion of a monocular camera and different radar sensors. Special emphasis is put on the temporal synchronization and determination of time characteristics of all sensors. Several different methods for precise timestamping and temporal calibration are therefore developed and validated. The derived OOSM algorithms for state and existence estimation are evaluated in different test drives. The two new algorithms are shown to perform better than state-of-the-art filters. For the first time, the correct handling of out-of-sequence measurements is now possible not only in state estimation, but also in existence estimation.dc.description.abstract
Sprachededc.language.iso
Verbreitende StelleUniversität Ulmdc.publisher
LizenzStandarddc.rights
Link zum Lizenztexthttps://oparu.uni-ulm.de/xmlui/license_v3dc.rights.uri
SchlagwortExistenzschätzungdc.subject
SchlagwortOut-of-Sequence-Messungendc.subject
SchlagwortSensorfusiondc.subject
SchlagwortUmgebungserfassungdc.subject
DDC-SachgruppeDDC 620 / Engineering & allied operationsdc.subject.ddc
LCSHDriver assistance systemsdc.subject.lcsh
LCSHMultisensor data fusiondc.subject.lcsh
TitelSimultane Zustands- und Existenzschätzung mit chronologisch ungeordneten Sensordaten für die Fahrzeugumfelderfassungdc.title
RessourcentypDissertationdc.type
DOIhttp://dx.doi.org/10.18725/OPARU-3216dc.identifier.doi
PPN42966401Xdc.identifier.ppn
URNhttp://nbn-resolving.de/urn:nbn:de:bsz:289-vts-93613dc.identifier.urn
GNDFahrerassistenzsystemdc.subject.gnd
FakultätFakultät für Ingenieurwissenschaften und Informatikuulm.affiliationGeneral
Datum der Freischaltung2015-04-21T08:33:52Zuulm.freischaltungVTS
Peer-Reviewneinuulm.peerReview
Signatur DruckexemplarW: W-H 14.163uulm.shelfmark
DCMI MedientypTextuulm.typeDCMI
VTS-ID9361uulm.vtsID
KategoriePublikationenuulm.category


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