Research on Lane Departure Warning System

2014 ◽  
Vol 598 ◽  
pp. 731-735 ◽  
Author(s):  
Hui Bao Yang
Keyword(s):  
Hough Transform ◽  
Warning System ◽  
Region Of Interest ◽  
Lane Departure Warning ◽  
Linear Mode ◽  
Detection And Tracking ◽  
Lane Departure ◽  
Calculation Parameter ◽  
Lane Line ◽  
Lane Position

Lane departure warning system includes lane identification and lane departure determination. Lane identification is crucial for lane departure warning system. In this paper, A linear mode which can only bring out small distance error and angle error is used to detect lane boundaries. A region of interest (ROI) appropriate is set to reduce nonessential cost of computation. According to the characteristics of lane position, we improve the Hough transform, reduce the detection and tracking transform angle and raise the speed of calculation. Parameter angle form Hough transform is used to lane departure determination, this method does not calibrate the camera and can get the lane departure rate. Experiments show that the system is well to detect and track the lane line and give alarm correctly.

scholarly journals Robust Lane Detection and Tracking Algorithm for Steering Assist Systems

Machines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Mihail-Alexandru Andrei ◽  
Costin-Anton Boiangiu ◽  
Nicolae Tarbă ◽  
Mihai-Lucian Voncilă
Keyword(s):  
Warning System ◽  
Region Of Interest ◽  
Original Method ◽  
Lane Detection ◽  
Light Sources ◽  
Detection And Tracking ◽  
Lane Departure ◽  
Increase In Accuracy ◽  
Safety Systems ◽  
Distinct Features

Modern vehicles rely on a multitude of sensors and cameras to both understand the environment around them and assist the driver in different situations. Lane detection is an overall process as it can be used in safety systems such as the lane departure warning system (LDWS). Lane detection may be used in steering assist systems, especially useful at night in the absence of light sources. Although developing such a system can be done simply by using global positioning system (GPS) maps, it is dependent on an internet connection or GPS signal, elements that may be absent in some locations. Because of this, such systems should also rely on computer vision algorithms. In this paper, we improve upon an existing lane detection method, by changing two distinct features, which in turn leads to better optimization and false lane marker rejection. We propose using a probabilistic Hough transform, instead of a regular one, as well as using a parallelogram region of interest (ROI), instead of a trapezoidal one. By using these two methods we obtain an increase in overall runtime of approximately 30%, as well as an increase in accuracy of up to 3%, compared to the original method.

scholarly journals Using ADAS to Future-Proof Roads—Comparison of Fog Line Detection from an In-Vehicle Camera and Mobile Retroreflectometer

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1737
Author(s):  
Ane Dalsnes Storsæter ◽  
Kelly Pitera ◽  
Edward McCormack
Keyword(s):  
Warning System ◽  
Management Systems ◽  
Warning Systems ◽  
Lane Departure Warning ◽  
Automated Driving ◽  
Pavement Markings ◽  
Lighting Conditions ◽  
Lane Marking ◽  
Lane Departure ◽  
Pavement Marking

Pavement markings are used to convey positioning information to both humans and automated driving systems. As automated driving is increasingly being adopted to support safety, it is important to understand how successfully sensor systems can interpret these markings. In this effort, an in-vehicle lane departure warning system was compared to data collected simultaneously from an externally mounted mobile retroreflectometer. The test, performed over 200 km of driving on three different routes in variable lighting conditions and road classes found that, depending on conditions, the retroreflectometer could predict whether the car’s lane departure systems would detect markings in 92% to 98% of cases. The test demonstrated that automated driving systems can be used to monitor the state of pavement markings and can provide input on how to design and maintain road infrastructure to support automated driving features. Since data about the condition of lane marking from multiple lane departure warning systems (crowd-sourced data) can provide input into the pavement marking management systems operated by many road owners, these findings also indicate that these automated driving sensors have an important role in enhancing the maintenance of pavement markings.

scholarly journals A Portable Vision-Based Real-Time Lane Departure Warning System: Day and Night

2009 ◽  
Vol 58 (4) ◽  
pp. 2089-2094 ◽  
Author(s):  
Pei-Yung Hsiao ◽  
Chun-Wei Yeh ◽  
Shih-Shinh Huang ◽  
Li-Chen Fu
Keyword(s):  
Real Time ◽  
Warning System ◽  
Lane Departure Warning ◽  
Lane Departure
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