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dc.contributor.authorZhang, Zhiming
dc.contributor.authorSun, Chao
dc.contributor.authorBridgelall, Raj
dc.contributor.authorSun, Mingxuan
dc.description.abstractPractitioners analyze the elevation profile of a roadway to detect localized defects and to produce the international roughness index. The prevailing method of measuring road profiles uses a specially instrumented vehicle and trained technicians, which usually leads to a high cost and an insufficient measurement frequency. The recent availability of probe data from connected vehicles provides a method that is cost-effective, continuous, and covers the entire roadway network. However, no method currently exists that can reproduce the elevation profile from multi-resolution features of the vehicle inertial response signal. This research uses the wavelet decomposition of the vehicle inertial responses and a nonlinear autoregressive artificial neural network with exogenous inputs to reconstruct the elevation profile. The vehicle inertial responses are a function of both the vehicle suspension characteristics and its speed. Therefore, the authors normalized the vehicle response models by the traveling speed and then numerically solved their inertial response equations to simulate the vehicle dynamic responses. The results demonstrate that applying the artificial neural network to the wavelet decomposed inertial response signals provides an effective estimation of the road profile.en_US
dc.rightsIn copyright. Permission to make this version available has been granted by the author and publisher.
dc.titleRoad Profile Reconstruction Using Connected Vehicle Responses and Wavelet Analysisen_US
dc.typeArticleen_US
dc.typePreprinten_US
dc.descriptionRaj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).en_US
dc.date.accessioned2021-08-03T22:33:39Z
dc.date.available2021-08-03T22:33:39Z
dc.date.issued2018
dc.identifier.urihttps://hdl.handle.net/10365/31981
dc.subjectRoad roughness.en_US
dc.subjectProfile reconstruction.en_US
dc.subjectVehicle response.en_US
dc.subjectWavelet analysis.en_US
dc.subjectNeural network.en_US
dc.identifier.orcid0000-0002-7678-605X
dc.identifier.citationZhang, Zhiming, Chao Sun, Raj Bridgelall, and Mingxuan Sun, "Road Profile Reconstruction Using Connected Vehicle Responses and Wavelet Analysis," Journal of Terramechanics, DOI: 10.1016/j.jterra.2018.10.004, Vol. 80, December 2018, Pages 21-30.en_US
dc.description.sponsorshipLouisiana Transportation Research Center (grant number DOTLT1000138)en_US
dc.description.sponsorshipLouisiana State University Start-up Fund (grant number 127150013)en_US
dc.description.urihttps://www.ugpti.org/about/staff/viewbio.php?id=79
dc.language.isoen_USen_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.contributor.organizationUpper Great Plains Transportation Institute
ndsu.collegeCollege of Business
ndsu.departmentTransportation and Logistics
dc.identifier.doi10.1016/j.jterra.2018.10.004


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