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An Integrated Solution Based Irregular Driving Detection

  • Rui Sun

Part of the Springer Theses book series (Springer Theses)

Table of contents

  1. Front Matter
    Pages i-xxviii
  2. Rui Sun
    Pages 1-8
  3. Back Matter
    Pages 127-127

About this book

Introduction

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.

Keywords

Irregular Driving Detection Lane Level Vehicle Dynamic Parameters Driving Transport Safety

Authors and affiliations

  • Rui Sun
    • 1
  1. 1.College of Civil AviationNanjing University of Aeronautics and AstronauticsNanjingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-44926-5
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-44925-8
  • Online ISBN 978-3-319-44926-5
  • Series Print ISSN 2190-5053
  • Series Online ISSN 2190-5061
  • Buy this book on publisher's site
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