• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.328-330
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• 2016

A lane departure warning system based on single lane mark detection is presented in this paper. The proposed system is focused on the robust detection of lane departure, even when one of the left or the right lane mark cannot be detected because of poor illumination or abrasion. Experimental results show that the proposed system warns lane departure, even if only a single lane is detected.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.428-437
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• 2005

In this paper, we developed lane departure warning system for lane departure situation of vehicle, accidentally. Color level of yellow lane of road side is changed to black and white level. And black and white level value of relevant pixel of original and yellow lane through added process of this are emphasized. In lane departure detection system, color image data processing method could improve the recognition of the yellow lane(central lane). We could get a system Performance of the high-speed image data Processing. Therefore, lane departure warning system will be utilized at the device for the safety going of the vehicle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1553-1559
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• 2017

This paper proposes a lane departure detection algorithm using a single camera equipped in front of a vehicle. The proposed algorithm generates a partial top-view image for a small ROI (region of interest) designated on the top-view space form the image acquired by the camera, detects lanes on the small partial top-view image, and makes a decision on the lane departure by checking overlap between the pre-assigned virtual vehicle and the detected lanes. The proposed algorithm also includes the removal of lines occurred by road symbols (noises) disturbing the lane departure detection between lanes and the prediction of lost lanes using lane information of previous fames. In lane departure detection test using real road videos, the proposed algorithm makes the right decision of 99.0% in lane keeping conditions and 94.7% in lane departure conditions.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.860-867
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• 2021

Lane detection is important technology for implementing ADAS or autonomous driving. Although edge detection has been typically used for the lane detection however, false detections occur frequently. To improve this problem, a deep learning based lane detection algorithm is proposed in this paper. This algorithm is mounted on an ARM-based embedded system to implement a LDW(lane departure warning). Since the embedded environment lacks computing power, the VGG-11, a lightweight model based on VGG-13, has been proposed. In order to evaluate the performance of the LDW, the test was conducted according to the test scenario of NHTSA.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.81-90
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• 2016

As an autonomous driving vehicle (AV) need to cope with external road conditions by itself, its perception performance for road environment should be better than that of a human driver. A vision sensor, one of AV sensors, performs lane detection function to percept road environment for performing safe vehicle steering, which relates to define vehicle heading and lane departure prevention. Performance standards for a vision sensor in an ADAS(Advanced Driver Assistance System) focus on the function of 'driver assistance', not on the perception of 'independent situation'. So the performance requirements for a vision sensor in AV may different from those in an ADAS. In assuming that an AV keep previous steering due to lane detection failure, this study calculated lane departure distances between the AV location following curved road alignment and the other one driving to the straight in a curved section. We analysed lane departure distance and time with respect to the allowance of lane detection malfunction of an AV vision sensor. With the results, we found that an AV would encounter a critical lane departure situation if a vision sensor loses lane detection over 1 second. Therefore, it is concluded that the performance standards for an AV should contain more severe lane departure situations than those of an ADAS.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.110.3-110
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• 2002

$\textbullet$ Lane detection by TFALDA $\textbullet$ SVM for large scale data and multiclass classification problem $\textbullet$ TLC Classification $\textbullet$ Lateral offset estimation by IPT $\textbullet$ Lane departure warning by a fuzzy system $\textbullet$ Experimental results by HiLS $\textbullet$ Conclusion

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2793-2800
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• 2011

The purpose of this research is to develop and optimize a lane departure warning application based on a smartphone which can be applicable as a new platform for various mobile information applications. Recently, a lane detection warning system which is a representative application among safe driving assistant solutions is being commercialized. Due to the necessity of powerful embedded hardware platform and its price, its market is still not growing. In this research, it is proposed to develop and optimize a lane departure warning application on iPhone 3GS. OpenCV is used for efficient image processing, and for lane detection a heuristic algorithm based on Hough Transform is proposed. The application was developed under Macintosh PC platform with Xcode 3.2.4 development tools, downloaded to the iPhone and has been tested on the real paved road. The experimental result has shown that the detection ratio of the straight lane was over 90% and the processing speed was 1.52fps. For the enhancement of the speed, a few optimization methods were introduced and the fastest speed was 3.84fps. Through the improvement of lane detection algorithm, additional optimization works and the adoption of a new powerful platform, it will be successfully commercialized on smartphone application market.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.815-818
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• 2016

Forward collision warning systems(FCWS) and lane departure warning systems(LDWS) need regions of interest for detecting lanes and objects as road regions. In general, the lane departure warning system using a vehicle front camera is tracking a lane curve using RANSAC or the like in the form of a straight line obtained image are compared with the center of the vehicle. This algorithm has weaknesses that requires a wide range of the lane being vulnerable to the curve. This paper presents an algorithm that checks whether the current lane departure by car from the Top-view space. The algorithm also can check whether the vehicle in the lane departure of the narrow range, and shows the result that is almost not affected by noise.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.35-46
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• 2009

Lane extraction and lane departure warning algorithms using the image sensor attached in the vehicle are addressed. With the research about intelligent automobile, there have been many algorithms about lane recognition and lane departure warning system. However, since these algorithms require to detect 2 lanes, the high time complexity and the low recognition rate under various driving circumstances are critical problems. In this paper, we present a lane departure warning algorithm using single lane extraction and center point analysis that achieves the fast processing time and high detection rate. From the geometry between camera and objects, the region of interest (ROI) is determined and splitted into two parts. Hough transform detects the part of the lane. After the detected lane is restored to have a pre-determined size, lane departure is estimated by calculating the distance from the center point. On real driving environments, the presented algorithm is compared with previous algorithms. Experiment results support that the presented algorithm is fast and accurate.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.791-799
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• 2010

In this paper, integrated navigation algorithm is designed for land transport sector which is needed high accuracy and monitoring program is developed for lane departure warning. High accuracy position information which is possible lane separation is needed for lane departure warning, so position detection algorithm based GPS/DR which combine GPS with dead reckoning is proposed. For the verification of the designed integrated navigation algorithm, we drived to acquire data and showed post-processing experiment results with monitoring program. Vehicle driving movie and aerial photograph in monitoring program is designed to show lane keeping and lane separation.