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Using a bike as a probe vehicle: Experimental study to determine road roughness with piezoelectric sensors

dc.contributor.authorRizelioğlu, M.
dc.contributor.authorArslan, T.
dc.contributor.authorYiğit, E.
dc.contributor.authorYazıcı, M.
dc.contributor.buuauthorRİZELİOĞLU, MEHMET
dc.contributor.buuauthorARSLAN, TURAN
dc.contributor.buuauthorYİĞİT, ENES
dc.contributor.buuauthorYAZICI, MURAT
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentİnşaat Mühendisliği Bölümü
dc.contributor.departmentElektrik-Elektronik Mühendisliği Bölümü
dc.contributor.departmentOtomotiv Mühendisliği Bölümü
dc.contributor.orcid0000-0003-1313-3091
dc.contributor.orcid0000-0001-7584-8581
dc.contributor.researcheridAAL-9217-2020
dc.contributor.researcheridABB-9374-2020
dc.contributor.researcheridGKZ-7542-2022
dc.contributor.researcheridKIV-2085-2024
dc.date.accessioned2025-02-11T13:06:08Z
dc.date.available2025-02-11T13:06:08Z
dc.date.issued2024-09-01
dc.description.abstractRoad roughness, defined by the International Roughness Index (IRI), is a critical criterion for ride quality and comfort, meticulously monitored by road authorities to address maintenance needs. This paper introduces a new method to explore the suitability of bicycles as probe vehicles for measuring nonmotorized road roughness. For this purpose, polyvinylidene fluoride (PVDF) sensors are attached to the front wheel of a mountain bike to capture road roughness through tire-road interaction. To validate this approach, a study was conducted on a motorized dual-lane road, where each direction spanned 660 m, totaling 1,320 m, to verify the method's accuracy in measuring IRI. Data from both the PVDF sensors and their specific locations were recorded simultaneously. The values obtained from a laser profilometer vehicle served as benchmark reference points for the PVDF sensor readings. Thirty-two features are extracted from the PVDF sensor data. The Support Vector Regression (SVR) algorithm is then used to estimate IRI values from these features. The mean absolute percentage error (MAPE) results of the data sets for the distances covered by 15, 30, and 50 full rotations of the bicycle's front wheel, corresponding to 30, 60, and 100 m, respectively, are found to be 13.64%, 10.73%, and 5.34%. These results highlight the potential of this innovative approach as a reliable tool for determining road roughness on nonmotorized pathways.
dc.identifier.doi10.1061/JITSE4.ISENG-2442
dc.identifier.issn1076-0342
dc.identifier.issue3
dc.identifier.urihttps://doi.org/10.1061/JITSE4.ISENG-2442
dc.identifier.urihttps://ascelibrary.org/doi/10.1061/JITSE4.ISENG-2442
dc.identifier.urihttps://hdl.handle.net/11452/50284
dc.identifier.volume30
dc.identifier.wos001267506800012
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherAsce-Amer Soc Civil Engineers
dc.relation.journalJournal of Infrastructure Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectPavement roughness
dc.subjectPrediction
dc.subjectEngineering
dc.titleUsing a bike as a probe vehicle: Experimental study to determine road roughness with piezoelectric sensors
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/İnşaat Mühendisliği Bölümü
local.contributor.departmentMühendislik Fakültesi/Elektrik-Elektronik Mühendisliği Bölümü
local.contributor.departmentMühendislik Fakültesi/Otomotiv Mühendisliği Bölümü
local.indexed.atWOS
relation.isAuthorOfPublicationf7abeb05-c492-41cd-9c17-30ed9d8f3057
relation.isAuthorOfPublication79f0fe8a-0375-4a19-9df5-552a8eeca5dd
relation.isAuthorOfPublication1b0a8078-edd4-454b-b251-2d465c101031
relation.isAuthorOfPublication399822ef-6146-4b15-b42f-09551b61eb11
relation.isAuthorOfPublication.latestForDiscoveryf7abeb05-c492-41cd-9c17-30ed9d8f3057

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