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An Integrated Solution Based Irregular Driving Detection (Paperback, Softcover reprint of the original 1st ed. 2017)
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An Integrated Solution Based Irregular Driving Detection (Paperback, Softcover reprint of the original 1st ed. 2017)
Series: Springer Theses
Expected to ship within 10 - 15 working days
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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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