Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/6736
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dc.contributor.authorBotshekan, Meshkaten_US
dc.contributor.authorRoxon, Jacoben_US
dc.contributor.authorWanichkul, Athikomen_US
dc.contributor.authorChirananthavat, Theemathasen_US
dc.contributor.authorChamoun, Joyen_US
dc.contributor.authorZiq, Maliken_US
dc.contributor.authorAnini, Baderen_US
dc.contributor.authorDaher, Naseemen_US
dc.contributor.authorAwad, Abdalkarimen_US
dc.contributor.authorGhanem, Waselen_US
dc.contributor.authorTootkabon, Mazdaken_US
dc.contributor.authorLouhghalam, Arghavanen_US
dc.contributor.authorUlm, Franz-Josefen_US
dc.date.accessioned2021-04-01T08:46:30Z-
dc.date.available2021-04-01T08:46:30Z-
dc.date.issued2020-12-
dc.identifier.urihttp://hdl.handle.net/20.500.11889/6736-
dc.description.abstractWe propose, calibrate, and validate a crowdsourced approach for estimating power spectral density (PSD) of road roughness based on an inverse analysis of vertical acceleration measured by a smartphone mounted in an unknown position in a vehicle. Built upon random vibration analysis of a half-car mechanistic model of roughness-induced pavement–vehicle interaction, the inverse analysis employs an L2 norm regularization to estimate ride quality metrics, such as the widely used International Roughness Index, from the acceleration PSD. Evoking the fluctuation– dissipation theorem of statistical physics, the inverse framework estimates the half-car dynamic vehicle properties and related excess fuel consumption. The method is validated against (a) laser-measured road roughness data for both inner city and highway road conditions and (b) road roughness data for the state of California.We also show that the phone position in the vehicle only marginally affects road roughness predictions, an important condition for crowdsourced capabilities of the proposed approach.en_US
dc.language.isoen_USen_US
dc.publisherCambridge University Pressen_US
dc.relation.ispartofData-Centric Engineering (2020), 1: e16en_US
dc.subjectInternational Roughness Indexen_US
dc.subjectInverse analysisen_US
dc.subjectRandom Vibration Theoryen_US
dc.subjectRoadsen_US
dc.subjectPavements - Measurementen_US
dc.subjectSurface roughnessen_US
dc.subjectRoughness-induced pavement–vehicle interactionen_US
dc.subjectSmartphone signal analysisen_US
dc.titleRoughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theoryen_US
dc.typeArticleen_US
newfileds.departmentEngineering and Technologyen_US
newfileds.custom-issue-dateData-Centric Engineering , Volume 1 , 2020 , e16en_US
newfileds.item-access-typeopen_accessen_US
newfileds.thesis-prognoneen_US
newfileds.general-subjectComputers and Information Technology | الحاسوب وتكنولوجيا المعلوماتen_US
dc.identifier.doihttps://doi.org/10.1017/dce.2020.17-
item.grantfulltextopen-
item.languageiso639-1other-
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