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A Dempster-Shafer based approach to the detection of trajectory stop points

hal.structure.identifierSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran [SSGE]
dc.contributor.authorHOSSEINPOOR, AMIN
hal.structure.identifierSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran [SSGE]
dc.contributor.authorABBASPOUR, Rahim Ali
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorCLARAMUNT, Christophe
dc.date.accessioned2021-05-14T09:42:25Z
dc.date.available2021-05-14T09:42:25Z
dc.date.issued2018-10
dc.identifier.issn0198-9715
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/76734
dc.description.abstractEnNowadays, location-based data collected by GPS-equipped devices such as smartphones and cars are often stored as spatio-temporal sequences of points denoted as trajectories. The analysis of the large generated trajectory databases such as the detection of patterns, outliers, and stops has a great importance for many application domains. Over the past few years, several successful trajectory data infrastructures have been progressively developed for a large range of applications in both the terrestrial and maritime environments. However, it still appears that amongst many research issues to consider, the resulting uncertainties when analyzing local trajectory properties have not been completely taken into account. In particular, determining for instance certainty rates, while detecting stop points, might have valuable impacts on most cases. The framework developed in this paper introduces an approach based on the Dempster-Shafer theory of evidence, and whose objective is to detect trajectory stop points and associated degrees of uncertainty. The approach is experimented using a large urban trajectory database and is compared to several computational algorithms introduced in previous studies. The results show that our approach reduces uncertainty values when detecting trajectory stop points as well as a significant improvement of the recall and precision values.
dc.language.isoen
dc.publisherElsevier
dc.subject.enTrajectory
dc.subject.enStop points
dc.subject.enUncertainty
dc.subject.enTheory of evidence
dc.subject.enBelief function
dc.title.enA Dempster-Shafer based approach to the detection of trajectory stop points
dc.typeArticle de revue
dc.subject.halInformatique [cs]
bordeaux.journalComputers, Environment and Urban Systems
bordeaux.page189-196
bordeaux.volume70
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.peerReviewedoui
hal.identifierhal-02140629
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02140629v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Computers,%20Environment%20and%20Urban%20Systems&rft.date=2018-10&rft.volume=70&rft.spage=189-196&rft.epage=189-196&rft.eissn=0198-9715&rft.issn=0198-9715&rft.au=HOSSEINPOOR,%20AMIN&ABBASPOUR,%20Rahim%20Ali&CLARAMUNT,%20Christophe&rft.genre=article


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