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Cooperative GNSS positioning aided by road-features measurements

dc.contributor.authorConde Bento, Luis
dc.contributor.authorBonnifait, Philippe
dc.contributor.authorNunes, Urbano J.
dc.date.accessioned2025-09-04T14:37:40Z
dc.date.available2025-09-04T14:37:40Z
dc.date.issued2017-06
dc.description.abstractCooperation between road users through V2X communication is a way to improve GNSS localization accuracy. When vehicles localization systems involve standalone GNSS receivers, the resulting accuracy can be affected by satellite-specific errors of several meters. This paper studies how road-features like lane marking detected by on-board cameras can be exploited to reduce absolute position errors of cooperative vehicles sharing information in real-time in a network. The algorithms considered in this work are based on a error bounded set membership strategy. In every vehicle, a set membership algorithm computes the absolute position and an estimation of the satellite-specific errors by using raw GNSS pseudoranges, lane boundary measurements and a 2D georeferenced road map which provides absolute geometric constraints. As lane-boundary measurements provide essentially cross-track corrections in the position estimation process, cooperation enables the vehicles to improve their own estimates thanks to the different orientation of the roads. Set-membership methods are very efficient to solve this problem since they do not involve any independence hypothesis of the errors and so, the same information can be used several times in the computation. Such class of algorithm provides a novel approach to improve position accuracy for connected vehicles guaranteeing the integrity of the computed solution which is pivoting for automated automotive systems requiring guaranteed safety-critical solutions. Results from simulations and real experiments show that sharing position corrections reduces significantly satellite-specific GNSS errors effects in both cross-track and along-track components. Moreover, it is shown that lane-boundary measurements help reducing estimation errors for all the networked vehicles even those which are not equipped with an embedded perception system.eng
dc.description.sponsorshipThis work has been supported by Fundação para a Ciência e Tecnologia (FCT) through project grant AMS-HMI12: RECI/EEIAUT/ 0181/2012, cofounded by FEDER (COMPETE program). We also acknowledge the support of QREN Project BMobility4People (maisCENTRO program).
dc.identifier.citationLuís Conde Bento, Philippe Bonnifait, Urbano J. Nunes, Cooperative GNSS positioning aided by road-features measurements, Transportation Research Part C: Emerging Technologies, Volume 79, 2017, Pages 42-57, ISSN 0968-090X, https://doi.org/10.1016/j.trc.2017.01.002
dc.identifier.doi10.1016/j.trc.2017.01.002
dc.identifier.issn0968-090X
dc.identifier.urihttp://hdl.handle.net/10400.8/13982
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier BV
dc.relationHMI12: RECI/EEIAUT/ 0181/2012
dc.relation.hasversionhttps://www.sciencedirect.com/science/article/pii/S0968090X17300025
dc.relation.ispartofTransportation Research Part C: Emerging Technologies
dc.rights.uriN/A
dc.subjectITS
dc.subjectCooperative
dc.subjectInterval analysis
dc.subjectBounded-error
dc.subjectGNSS and sensor fusion
dc.titleCooperative GNSS positioning aided by road-features measurementseng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage57
oaire.citation.startPage42
oaire.citation.titleTransportation Research Part C: Emerging Technologies
oaire.citation.volume79
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameConde Bento
person.givenNameLuis
person.identifier.ciencia-idFE12-AAD0-3AB3
person.identifier.orcid0000-0002-9689-3637
person.identifier.ridF-7888-2013
person.identifier.scopus-author-id14070145000
relation.isAuthorOfPublication0cfbb9a8-48d2-4547-bc90-01cde9d31be0
relation.isAuthorOfPublication.latestForDiscovery0cfbb9a8-48d2-4547-bc90-01cde9d31be0

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