An Integrated Solution Based Irregular Driving Detection (Record no. 79295)

000 -LEADER
fixed length control field 03705nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-3-319-44926-5
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801221112.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160907s2017 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319449265
-- 978-3-319-44926-5
082 04 - CLASSIFICATION NUMBER
Call Number 629.04
100 1# - AUTHOR NAME
Author Sun, Rui.
245 13 - TITLE STATEMENT
Title An Integrated Solution Based Irregular Driving Detection
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XXVIII, 127 p. 84 illus., 75 illus. in color.
490 1# - SERIES STATEMENT
Series statement Springer Theses, Recognizing Outstanding Ph.D. Research,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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 ## - SUMMARY, ETC.
Summary, etc 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-44926-5
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
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-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2017.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Transportation engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Traffic engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Security systems.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Application software.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Transportation Technology and Traffic Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing .
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Security Science and Technology.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control and Systems Theory.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer and Information Systems Applications.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2190-5061
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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