An Integrated Solution Based Irregular Driving Detection

This thesis introduces a new integrated algorithm for the detection of lane-level irregular driving. To date, there has been very little improvement in the ability to detect lane level irregular driving styles, mainly due to a lack of high performance positioning techniques and suitable driving patt...

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Detaylı Bibliyografya
Yazar: Sun, Rui (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : Imprint: Springer, 2017.
Edisyon:1st ed. 2017.
Seri Bilgileri:Springer Theses, Recognizing Outstanding Ph.D. Research,
Konular:
Transportation engineering.
Traffic engineering.
Signal processing.
Security systems.
Control engineering.
Application software.
Transportation Technology and Traffic Engineering.
Signal, Speech and Image Processing.
Security Science and Technology.
Control and Systems Theory.
Computer and Information Systems Applications.
Online Erişim:Full-text access
OPAC'ta görüntüle
Diğer Bilgiler
Özet:This thesis introduces a new integrated algorithm for the detection of lane-level irregular driving. To date, there has been very little improvement in the ability to detect lane level irregular driving styles, mainly due to a lack of high performance positioning techniques and suitable driving pattern recognition algorithms. The algorithm combines data from the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and lane information using advanced filtering methods. The vehicle state within a lane is estimated using a Particle Filter (PF) and an Extended Kalman Filter (EKF). The state information is then used within a novel Fuzzy Inference System (FIS) based algorithm to detect different types of irregular driving. Simulation and field trial results are used to demonstrate the accuracy and reliability of the proposed irregular driving detection method.
Fiziksel Özellikler:XXVIII, 127 p. 84 illus., 75 illus. in color. online resource.
ISBN:9783319449265
ISSN:2190-5061
DOI:10.1007/978-3-319-44926-5

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