Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 115,68
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Añadir al carritoCondición: New. In.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 153,49
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Añadir al carritoHardcover. Condición: Brand New. 156 pages. 9.25x6.25x0.50 inches. In Stock.
Idioma: Inglés
Publicado por Springer International Publishing, 2016
ISBN 10: 3319449257 ISBN 13: 9783319449258
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing Sep 2016, 2016
ISBN 10: 3319449257 ISBN 13: 9783319449258
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 156 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing, 2016
ISBN 10: 3319449257 ISBN 13: 9783319449258
Librería: moluna, Greven, Alemania
EUR 92,27
Cantidad disponible: Más de 20 disponibles
Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an integrated solution for the detection of lane level irregular driving behaviourPresents an extensive literature review to capture the state-of-the-art in the existing irregular driving monitoring algorithms.
Idioma: Inglés
Publicado por Springer, Springer Sep 2016, 2016
ISBN 10: 3319449257 ISBN 13: 9783319449258
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 156 pp. Englisch.