rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: An
    title: Integrated Solution Based Irregular Driving Detection
  name:
    name part: Sun, Rui.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXVIII, 127 p. 84 illus., 75 illus. in color. online resource.
  abstract: 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.
  table of contents: 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.
  note: by Rui Sun.
  subject:
    topic: Engineering
  subject:
    topic: Application software
  subject:
    topic: Control engineering
  subject:
    topic: Quality control
  subject:
    topic: Reliability
  subject:
    topic: Industrial safety
  subject:
    topic: Transportation engineering
  subject:
    topic: Traffic engineering
  subject:
    topic: Engineering
  subject:
    topic: Transportation Technology and Traffic Engineering
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Quality Control, Reliability, Safety and Risk
  subject:
    topic: Control
  subject:
    topic: Computer Applications
  classification: TA1001-TA1280
  classification: HE331-HE380
  classification: 629.04
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Theses, Recognizing Outstanding Ph.D. Research
  identifier: 9783319449265
  identifier: http://dx.doi.org/10.1007/978-3-319-44926-5
  record info:
    record creation date: 160907
    record change date: 20160907164455.0
    record identifier: 978-3-319-44926-5