國立高雄大學圖資館 |

Language: English

Back to Search results for [ subject:"Motor vehicle driving." ]

An integrated solution based irregul...

SpringerLink (Online service)

An integrated solution based irregular driving detection

Record Type:	Electronic resources : Monograph/item
Title/Author:	An integrated solution based irregular driving detectionby Rui Sun.
Author:	Sun, Rui.
Published:	Cham :Springer International Publishing :2017.
Description:	xxviii, 127 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Intelligent transportation systems.
Online resource:	http://dx.doi.org/10.1007/978-3-319-44926-5
ISBN:	9783319449265$q(electronic bk.)

An integrated solution based irregular driving detection
Sun, Rui.

An integrated solution based irregular driving detection[electronic resource] /by Rui Sun. - Cham :Springer International Publishing :2017. - xxviii, 127 p. :ill. (some col.), digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

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.

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.

ISBN: 9783319449265$q(electronic bk.)

Standard No.: 10.1007/978-3-319-44926-5doiSubjects--Topical Terms:

403795
Intelligent transportation systems.

LC Class. No.: TE228.3

Dewey Class. No.: 388.312

An integrated solution based irregular driving detection
LDR:02385nmm a2200325 a 4500 001 504945
003 DE-He213
005 20160907164455.0
006 m d
007 cr nn 008maaau
008 171030s2017 gw s 0 eng d
020 $a 9783319449265$q(electronic bk.)
020 $a 9783319449258$q(paper)
024 7 $a 10.1007/978-3-319-44926-5 $2 doi
035 $a 978-3-319-44926-5
040 $a GP $c GP
041 0 $a eng
050 4 $a TE228.3
072 7 $a TNH $2 bicssc
072 7 $a TEC009020 $2 bisacsh
082 0 4 $a 388.312 $2 23
090 $a TE228.3 $b .S957 2017
100 1 $a Sun, Rui. $3 770018
245 1 3 $a An integrated solution based irregular driving detection $h [electronic resource] / $c by Rui Sun.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xxviii, 127 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Springer theses, $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 Intelligent transportation systems. $3 403795
650 0 $a Motor vehicle driving. $3 770019
650 0 $a Global Positioning System. $3 184981
650 1 4 $a Engineering. $3 210888
650 2 4 $a Transportation Technology and Traffic Engineering. $3 724870
650 2 4 $a Signal, Image and Speech Processing. $3 273768
650 2 4 $a Quality Control, Reliability, Safety and Risk. $3 274011
650 2 4 $a Control. $3 349080
650 2 4 $a Computer Applications. $3 273760
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Springer theses. $3 557607
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-44926-5
950 $a Engineering (Springer-11647)