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A. Abu et al.
safety of the driver and passenger, and reduces road traffic. The important technology on the intelligent vehicle nowadays is being applied in different types of lane
detection, which is lane departure warning, lane-keeping assistance, lane centring
and others.
The lane departure warning is a system that warns the driver if the vehicle leaves
its lane using visual, audio and vibration warning. The system itself can be set to
warn the driver when the vehicles are crossing out of lane marking or give an early
warning before crossing the lane marking. The lane-keeping assistance is a system
that warns the driver when no action is taken; then it will automatically take action
to ensure the vehicle stays in their lanes. The actual application applies a torque to
the steering wheel to prevent unwanted motion out from its lane marking. The lane
centring is a system that continuously controls the steering wheel to keep vehicles
in the lane centre. The system itself controls the wheel to keep the lane centre with
information on the lane geometry.
The basic idea is to develop an algorithm for detecting the lane marking to assist
the driver. The algorithm that has been created can detect a lane marking in the
variable condition of the road such as in the urban road, highway or the city with
different printed marks such as a solid or dashed line. Furthermore, it is designed
for real-time applications. The challenging task that involves lane detection is to
eliminate the noise that occurs and it needs to detect the correct pattern of the line in
different road situations.
31.2 Related Works
The driver assistance for lane detection is using various techniques, one of them is
lane marking such as the colour-based method proposed by Chin and Lin [1] which
specified the colour information and extracted the landmarks. They have proposed a
new method based on the colour information which is applicable in complex environments. The first step is to choose the region of interest (ROI) to find out a threshold
by using a statistical method in the colour image. Then the threshold is used to distinguish possible lane boundaries from the road. The colour-based segmentation is used
to locate the lane boundary by using a quadratic function to accomplish it.
Chiu and Lin [2], the authors purposed a method of edge detection by matching
the potential candidates of the road line or boundary. This study used a real-time lane
detection algorithm in complex conditions which included coloured lane marks and
roads with special traffic marks. The hyperbola model algorithm is being presented
in the methodology used. The edges that have been used in this algorithm are formed
by the canny edge detector.
Another method has been introduced by Habib and Hannan [3] by using the Hough
transform function, which can detect line and road boundaries in different light
A. Abu et al.
safety of the driver and passenger, and reduces road traffic. The important technology on the intelligent vehicle nowadays is being applied in different types of lane
detection, which is lane departure warning, lane-keeping assistance, lane centring
and others.
The lane departure warning is a system that warns the driver if the vehicle leaves
its lane using visual, audio and vibration warning. The system itself can be set to
warn the driver when the vehicles are crossing out of lane marking or give an early
warning before crossing the lane marking. The lane-keeping assistance is a system
that warns the driver when no action is taken; then it will automatically take action
to ensure the vehicle stays in their lanes. The actual application applies a torque to
the steering wheel to prevent unwanted motion out from its lane marking. The lane
centring is a system that continuously controls the steering wheel to keep vehicles
in the lane centre. The system itself controls the wheel to keep the lane centre with
information on the lane geometry.
The basic idea is to develop an algorithm for detecting the lane marking to assist
the driver. The algorithm that has been created can detect a lane marking in the
variable condition of the road such as in the urban road, highway or the city with
different printed marks such as a solid or dashed line. Furthermore, it is designed
for real-time applications. The challenging task that involves lane detection is to
eliminate the noise that occurs and it needs to detect the correct pattern of the line in
different road situations.
31.2 Related Works
The driver assistance for lane detection is using various techniques, one of them is
lane marking such as the colour-based method proposed by Chin and Lin [1] which
specified the colour information and extracted the landmarks. They have proposed a
new method based on the colour information which is applicable in complex environments. The first step is to choose the region of interest (ROI) to find out a threshold
by using a statistical method in the colour image. Then the threshold is used to distinguish possible lane boundaries from the road. The colour-based segmentation is used
to locate the lane boundary by using a quadratic function to accomplish it.
Chiu and Lin [2], the authors purposed a method of edge detection by matching
the potential candidates of the road line or boundary. This study used a real-time lane
detection algorithm in complex conditions which included coloured lane marks and
roads with special traffic marks. The hyperbola model algorithm is being presented
in the methodology used. The edges that have been used in this algorithm are formed
by the canny edge detector.
Another method has been introduced by Habib and Hannan [3] by using the Hough
transform function, which can detect line and road boundaries in different light