Authors:
- Provides an integrated solution for the detection of lane level irregular driving behaviour
- Presents an extensive literature review to capture the state-of-the-art in the existing irregular driving monitoring algorithms
- Provides solutions to address basic underpinning issues such as system design, filter choice, vehicle motion model choice and driving pattern detection methods
Part of the book series: Springer Theses (Springer Theses)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
About this book
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.
Authors and Affiliations
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College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Rui Sun
Bibliographic Information
Book Title: An Integrated Solution Based Irregular Driving Detection
Authors: Rui Sun
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-3-319-44926-5
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-44925-8Published: 15 September 2016
Softcover ISBN: 978-3-319-83164-0Published: 15 June 2018
eBook ISBN: 978-3-319-44926-5Published: 07 September 2016
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XXVIII, 127
Number of Illustrations: 9 b/w illustrations, 75 illustrations in colour
Topics: Transportation Technology and Traffic Engineering, Signal, Image and Speech Processing, Quality Control, Reliability, Safety and Risk, Control and Systems Theory, Computer Applications