Estimation of confidence regions and severity of undefined faults in driving using synthetic disturbance signals

dc.contributor.YOKIDTR118218
dc.contributor.YOKIDTR120580
dc.contributor.YOKIDTR9730
dc.contributor.YOKIDTR147383
dc.contributor.YOKIDTR1851
dc.contributor.YOKIDTR3646
dc.contributor.authorYakut, Oğuz
dc.contributor.authorEren, Haluk
dc.contributor.authorKaya, Mustafa
dc.contributor.authorÖksüztepe, Eyyüp
dc.contributor.authorPolat, Mehmet
dc.contributor.authorOmaç, Zeki
dc.contributor.authorKürüm, Hasan
dc.contributor.authorCelenk, Mehmet
dc.date.accessioned2016-11-03T07:41:14Z
dc.date.available2016-11-03T07:41:14Z
dc.date.issued2014-12-17
dc.descriptionBildiri - Yayımlanmamış
dc.description.abstractIn this study, we aim to determine fault severity in an electric car that may be caused by yawing due to such disturbances as non-uniform road pavements, in-wheel bearing clearance, suspension system, driver under Influence of alcohol (DUI), and tire deformation. The major research contribution herein is to alert drivers about an unforeseen situation on steering wheel whether it refers to a severe fault or contemporary states. In a sense, the undertaken study serves as a state of the art driving assistant system operating under unsteady conditions. We determine the fault severity of the system via classifying it into specified confidence regions by estimating the deviation from a monotonous straight route for any unstable situation. In this way, the proposed system informs driver to gain an insight about the severity level of arising problematic scenario. In order to realize the classification of confidence regions, we initially obtain the overall dynamic model of the system. Then, disturbance functions with different amplitudes and frequencies are characterized and included in the dynamic system specification. Here, the confidence regions have been constructed as to respective fault severity level of the car through the system response. Trajectory of vehicle in dynamic driving conditions considering these perturbations and noises are interrelated through the Kalman filtering to predict deviations from the desired trajectory and the prediction error. In simulation scenarios, Dynamic Time Warping (DTW) is employed to obtain deviation from ground truth under different noise functions, and results are sketched graphically assigning rate of fault severity into specified confidence regions. Initially, we have modeled the proposed system considering an electric car although the idea can readily be generalized for all cars with four tires. Presently, fault severity with classified confidence regions has been investigated under a simple car model. Keywords
dc.identifier.citationYakut, O., Eren, H., Kaya, M., Öksüztepe, E., Polat, M. ve diğerleri. (2014, Aralık). Estimation of confidence regions and severity of undefined faults in driving using synthetic disturbance signals. IEEE Electric Vehicle Conference (IEVC), Italya Floransa sunulan bildiri.
dc.identifier.scopus2-s2.0-84934324808
dc.identifier.scopusqualityN/A
dc.identifier.urihttp://hdl.handle.net/11508/8921
dc.identifier.wosWOS:000380394300107
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.relation.ispartofIEEE Electric Vehicle Conference (IEVC)
dc.relation.publicationcategoryUluslararası Katılımlı
dc.relation.publishinghaddressItalya Floransa
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectUndefined faults
dc.subjectSafe driving with confidence regions
dc.subjectDisturbance functions
dc.subjectFault simulation scenarios
dc.subjectAnomaly situations
dc.titleEstimation of confidence regions and severity of undefined faults in driving using synthetic disturbance signals
dc.typeConference Object

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