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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Sun, Rui (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
Σειρά:Springer Theses, Recognizing Outstanding Ph.D. Research,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Sun, Rui.  |e author. 
245 1 3 |a An Integrated Solution Based Irregular Driving Detection  |h [electronic resource] /  |c by Rui Sun. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2017. 
300 |a XXVIII, 127 p. 84 illus., 75 illus. in color.  |b online resource. 
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490 1 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5053 
505 0 |a Table of Contents -- Acknowledgements -- Declaration of Contribution -- Copyright Declaration -- Abstract.-Chapter 1 Introduction -- Chapter 2 Road Safety and Intelligent Transport Systems -- Chapter 3 State-of-the-art in Irregular Driving Detection -- Chapter 4 A New System for Lane Level Irregular Driving Detection.-Chapter 5 Testing, Analysis and Performance Validation -- Chapter 6 Conclusion and Recommendations for Future Work -- Publications Related to This Thesis -- Reference -- APPENDIX 1. Field Test Risk Assessment. 
520 |a 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. 
650 0 |a Engineering. 
650 0 |a Application software. 
650 0 |a Control engineering. 
650 0 |a Quality control. 
650 0 |a Reliability. 
650 0 |a Industrial safety. 
650 0 |a Transportation engineering. 
650 0 |a Traffic engineering. 
650 1 4 |a Engineering. 
650 2 4 |a Transportation Technology and Traffic Engineering. 
650 2 4 |a Signal, Image and Speech Processing. 
650 2 4 |a Quality Control, Reliability, Safety and Risk. 
650 2 4 |a Control. 
650 2 4 |a Computer Applications. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319449258 
830 0 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5053 
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950 |a Engineering (Springer-11647)