Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/40087
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dc.contributor.authorARIEN, Caroline-
dc.contributor.authorVANROELEN, Giovanni-
dc.contributor.authorROSS, Veerle-
dc.contributor.authorSONG, Yanchao-
dc.contributor.authorBRIJS, Tom-
dc.contributor.authorWETS, Geert-
dc.contributor.authorJONGEN, Ellen-
dc.contributor.authorCORNU, Joris-
dc.contributor.authorMOLLU, Kristof-
dc.contributor.authorDANIELS, Stijn-
dc.contributor.authorBRIJS, Kris-
dc.date.accessioned2023-05-10T12:57:54Z-
dc.date.available2023-05-10T12:57:54Z-
dc.date.issued2023-
dc.date.submitted2023-04-17T08:30:07Z-
dc.identifier.citationTransportmetrica A-Transport Science, , p. 1 -29-
dc.identifier.urihttp://hdl.handle.net/1942/40087-
dc.description.abstractDriving simulator data can be sampled in function of distance (equally spaced) or time (with constant frequency). Consequently, the sampling data might have problems in the envisaged type of analysis (i.e. point location based analysis vs. zonal-based analysis). These issues are illustrated by means of five driving simulator datasets. The nearest sampled parameter value in the direct vicinity of the specific point is a very good proxy for the driving parameter value at the point of interest along the road. The analysis of driving parameters in zones requires a different approach. In summary, the interpolation technique is preferred over using raw sampled data to calculate mean parameter values. We introduce an equivalent time integral formula to compute the mean value of a driving parameter with respect to distance. Based on this paper, we demonstrate that it is very important to mention the data processing approach in driving simulator methodology. ARTICLE HISTORY-
dc.description.sponsorshipPart of this research was funded by the European Regional Development Fund (ERDF). Acknowledgments The authors thank Dirk Roox and Marc Geraerts for technical support.-
dc.language.isoen-
dc.publisher-
dc.rightsNo open access. We just got free eprints when first published.-
dc.subject.otherDriving simulator-
dc.subject.otherzonal parameter analysis-
dc.subject.otherpoint located parameter analysis-
dc.subject.otherdata sampling-
dc.subject.otherinterpolation-
dc.titleProcessing driving simulator data before statistical analysis by means of interpolation and an integral formula-
dc.typeJournal Contribution-
dc.identifier.epage29-
dc.identifier.spage1-
local.bibliographicCitation.jcatA1-
local.publisher.place2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.bibliographicCitation.statusEarly view-
dc.identifier.doi10.1080/23249935.2023.2179347-
dc.identifier.isiWOS:000937536800001-
local.provider.typePdf-
local.uhasselt.internationalyes-
item.fullcitationARIEN, Caroline; VANROELEN, Giovanni; ROSS, Veerle; SONG, Yanchao; BRIJS, Tom; WETS, Geert; JONGEN, Ellen; CORNU, Joris; MOLLU, Kristof; DANIELS, Stijn & BRIJS, Kris (2023) Processing driving simulator data before statistical analysis by means of interpolation and an integral formula. In: Transportmetrica A-Transport Science, , p. 1 -29.-
item.contributorARIEN, Caroline-
item.contributorVANROELEN, Giovanni-
item.contributorROSS, Veerle-
item.contributorSONG, Yanchao-
item.contributorBRIJS, Tom-
item.contributorWETS, Geert-
item.contributorJONGEN, Ellen-
item.contributorCORNU, Joris-
item.contributorMOLLU, Kristof-
item.contributorDANIELS, Stijn-
item.contributorBRIJS, Kris-
item.accessRightsClosed Access-
item.fulltextNo Fulltext-
crisitem.journal.issn2324-9935-
crisitem.journal.eissn2324-9943-
Appears in Collections:Research publications
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