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


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dc.contributor.author Yakut, Oğuz
dc.contributor.author Eren, Haluk
dc.contributor.author Kaya, Mustafa
dc.contributor.author Öksüztepe, Eyyüp
dc.contributor.author Polat, Mehmet
dc.contributor.author Omaç, Zeki
dc.contributor.author Kürüm, Hasan
dc.contributor.author Celenk, Mehmet
dc.date.accessioned 2016-11-03T07:41:14Z
dc.date.available 2016-11-03T07:41:14Z
dc.date.issued 2014-12-17
dc.identifier.citation Yakut, 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. tr_TR
dc.identifier.uri http://hdl.handle.net/11508/8921
dc.description.abstract In 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 tr_TR
dc.language.iso İngilizce tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Fırat Üniversitesi Kütüphanesi::TEKNOLOJİ tr_TR
dc.subject.ddc Undefined faults tr_TR
dc.subject.ddc Safe driving with confidence regions tr_TR
dc.subject.ddc Disturbance functions tr_TR
dc.subject.ddc Fault simulation scenarios tr_TR
dc.subject.ddc Anomaly situations tr_TR
dc.title Estimation of confidence regions and severity of undefined faults in driving using synthetic disturbance signals tr_TR
dc.type Bildiri - Yayımlanmamış tr_TR
dc.contributor.YOKID TR118218 tr_TR
dc.contributor.YOKID TR120580 tr_TR
dc.contributor.YOKID TR9730 tr_TR
dc.contributor.YOKID TR147383 tr_TR
dc.contributor.YOKID TR1851 tr_TR
dc.contributor.YOKID TR3646 tr_TR
dc.relation.publishinghaddress Italya Floransa tr_TR
dc.meeting.name IEEE Electric Vehicle Conference (IEVC) tr_TR
dc.published.type Uluslararası Katılımlı tr_TR


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University of Fırat
23119
Elazığ-Merkez
TURKEY