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04069nam a22006375i 4500 |
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978-3-319-44926-5 |
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|a 9783319449265
|9 978-3-319-44926-5
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|a 10.1007/978-3-319-44926-5
|2 doi
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|a Sun, Rui.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a An Integrated Solution Based Irregular Driving Detection
|h [electronic resource] /
|c by Rui Sun.
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|a 1st ed. 2017.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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|a XXVIII, 127 p. 84 illus., 75 illus. in color.
|b online resource.
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|a text
|b txt
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|a online resource
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|a Springer Theses, Recognizing Outstanding Ph.D. Research,
|x 2190-5053
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|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.
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|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.
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|a Transportation engineering.
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|a Traffic engineering.
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|a Signal processing.
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|a Image processing.
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|a Speech processing systems.
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|a Quality control.
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|a Reliability.
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|a Industrial safety.
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|a Control engineering.
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|a Application software.
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|a Transportation Technology and Traffic Engineering.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T23120
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|a Signal, Image and Speech Processing.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T24051
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| 650 |
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|a Quality Control, Reliability, Safety and Risk.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T22032
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|a Control and Systems Theory.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T19010
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|a Computer Applications.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I23001
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|a Springer Theses, Recognizing Outstanding Ph.D. Research,
|x 2190-5053
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|u https://doi.org/10.1007/978-3-319-44926-5
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| 950 |
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