Abstract: Driver fatigue is an important factor in the increasing
number of road accidents. Dynamic template matching method was
proposed to address the problem of real-time driver fatigue detection
system based on eye-tracking. An effective vision based approach
was used to analyze the driver’s eye state to detect fatigue. The driver
fatigue system consists of Face detection, Eye detection, Eye
tracking, and Fatigue detection. Initially frames are captured from a
color video in a car dashboard and transformed from RGB into YCbCr
color space to detect the driver’s face. Canny edge operator was used
to estimating the eye region and the locations of eyes are extracted.
The extracted eyes were considered as a template matching for eye
tracking. Edge Map Overlapping (EMO) and Edge Pixel Count
(EPC) matching function were used for eye tracking which is used to
improve the matching accuracy. The pixel of eyeball was tracked
from the eye regions which are used to determine the fatigue state of
the driver.
Abstract: A robust wheel slip controller for electric vehicles is
introduced. The proposed wheel slip controller exploits the dynamics
of electric traction drives and conventional hydraulic brakes for
achieving maximum energy efficiency and driving safety. Due to
the control of single wheel traction motors in combination with a
hydraulic braking system, it can be shown, that energy recuperation
and vehicle stability control can be realized simultaneously. The
derivation of a sliding mode wheel slip controller accessing two
drivetrain actuators is outlined and a comparison to a conventionally
braked vehicle is shown by means of simulation.