scholarly journals Design of Lane Departure Warning System Based on ADSP-BF561

2012 ◽  
Author(s):  
Yongtao Liu ◽  
Lang Wei ◽  
Jie Qiao
Keyword(s):  
Warning System ◽  
Lane Departure Warning ◽  
Lane Departure

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

Development and Implementation of Lane Departure Warning System on ADAS Alpha Board

2021 ◽  
Author(s):  
Srdan Dragas ◽  
Ratko Grbic ◽  
Matteo Brisinello ◽  
Krsto Lazic
Keyword(s):  
Warning System ◽  
Lane Departure Warning ◽  
Lane Departure

A Novel Real-Time Lighting-Invariant Lane Departure Warning System

2018 ◽  
pp. 231-252
Author(s):  
Yassin Kortli ◽  
Mehrez Marzougui ◽  
Mohamed Atri
Keyword(s):  
Real Time ◽  
Traffic Accidents ◽  
Essential Element ◽  
Warning System ◽  
Lane Detection ◽  
Accuracy Evaluation ◽  
Lane Departure Warning ◽  
Lighting Conditions ◽  
Lane Departure ◽  
Driving Assistance

In recent years, in order to minimize traffic accidents, developing driving assistance systems for security has attracted much attention. Lane detection is an essential element of avoiding accidents and enhancing driving security. In this chapter, the authors implement a novel real-time lighting-invariant lane departure warning system. The proposed methodology works well in different lighting conditions, such as in poor conditions. The experimental results and accuracy evaluation indicates the efficiency of the system proposed for lane detection. The correct detection rate averages 97% and exceeds 95.6% in poor conditions. Furthermore, the entire process has only 29 ms per frame.

New Lane Departure Warning System Based on Side-View Cameras

2015 ◽  
Vol 764-765 ◽  
pp. 1361-1365
Author(s):  
Cheng Yu Chiu ◽  
Chih Han Chang ◽  
Hsin Jung Lin ◽  
Tsong Liang Huang
Keyword(s):  
Warning System ◽  
Side View ◽  
Lane Departure Warning ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Warning Messages ◽  
Warning Message ◽  
Lane Departure ◽  
Assistance Systems ◽  
The Right

This paper addressed a new lane departure warning system (LDWS). We used the side-view cameras to promote Advanced Driver Assistance Systems (ADAS). A left side-view camera detected the right lane next to vehicle, and a right side-view camera detected the right lane. Two cameras processed in their algorithm and gave warning message, independently and separately. Our algorithm combined those warning messages to analyze environment situations. At the end, we used the LUXGEN MPV to test and showed results of verifications and tests.

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