An Integrated Solution Based Irregular Driving Detection (Paperback, Softcover reprint of the original 1st ed. 2017)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Springer Theses
Release date:	June 2018
First published:	2017
Authors:	Rui Sun
Dimensions:	235 x 155 x 8mm (L x W x T)
Format:	Paperback
Pages:	127
Edition:	Softcover reprint of the original 1st ed. 2017
ISBN-13:	978-3-319-83164-0
Categories:	Books > Professional & Technical > Civil engineering, surveying & building > Highway & traffic engineering Books > Computing & IT > General theory of computing > General Books > Professional & Technical > Mechanical engineering & materials > Production engineering > Reliability engineering Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	3-319-83164-X
Barcode:	9783319831640

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