• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.49-58
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• 2014

This paper proposes a new assessment and reliability validation method of Lane Departure Assistance System based on DGPS-GIS by measuring lanes with camera vision. Assessment of lane departure is performed with yaw speed measurement and determination method for false alarm of ISO 17361 and performance validation is executed after generating departure warning boundary line by considering deviation error of LDAS using DGPS. Distance between the wheel and the lane is obtained through line abstraction using Hough transformation of the lane image with camera vision. Evaluation validation is obtained by comparing this value with the distance obtained with LDAS. The experimental result shows that the error of the extracted distance of the LDAS is within 5 cm. Also it proves performance of LDAS based on DGPS-GIS and assures effectiveness of the proposed validation method for system reliability using camera vision.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.65-77
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• 2013

Recent advanced sensors and communication technologies have been widely applied to advanced safety vehicle (ASV) for reducing traffic accident and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify the safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the advanced driver assistant system (ADAS), and applied the methodology to lane departure warning system (LDWS) and automatic emergency braking system (AEBS) which are typical advanced driver assistant systems. When the proposed methodology is applied to 2008-2010 gyeonggi-province crash data, LDWS would reduce about 10~14% of relevant crashes such as head-on, run-off-the road, rollover and fixed-object collisions on the road. In addition, AEBS could potentially prevent about 50% of total rear-end crashes. The outcomes of this study support decision making for developing not only vehicular technology but also relevant safety policies.

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.54-58
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• 2013

In recent days, vehicles have become equipped with electric systems that assist and help drivers driving safe by reducing possible accidents. LDWS(Lane Departure Warning System) and LKAS(Lane Keeping Assistant System) are involved in assist systems, especially for lateral motion of vehicles. Sudden and inattentive lateral motion of vehicles due to drivers' fatigue, illness, inattention, and drowsiness are major causes of accidents in highway. LDWS and LKAS provide drivers with warnings or assisting power to reduce any possibilities of accidents. In order to prevent or minimize the possibilities of accidents, lateral motion control of vehicles has been introduced in this research. DGPS/RTK(Differential Global Positioning System/Real Time Kinematics) and GIS(Geographic Information System) have been used to obtain the current position of vehicles and decide when activate controlling lateral motion of vehicles. The presented lateral motion control has been validated with actual vehicle tests.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.293-302
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• 2014

Recently, advanced sensors and communication technologies have been widely applied to advanced safety vehicles for reducing traffic accidents and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the Advanced Driver Assistant System (ADAS) with the Analytic Hierarchy Process (AHP). When the proposed methodology is applied to 2008-2010 Gyeonggi-province crash data, ADAS would reduce about 10.18% of crashes. In addition, Adaptive Cruise Control, Automatic Emergency Braking System, Lane Departure Warning System and Blind Spot Detection System are expected to reduce about 10.43%, 10.17%, 9.96%, and 10.18%, respectively. The outcomes of this study might support decision making for developing not only vehicular technologies but also relevant safety policies.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.18-25
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• 2016

As more people have cars, the threat of traffic accidents is posed on men and women of all ages. The main culprit of traffic accidents is driving while intoxicated or drowsy. The method to recognize and prevent the cause of traffic accidents is to use lane detection. In this study, a total of 4,000 frames (day image: 2,900 frames, night image: 1,100 frames) were used to test lane detection. According to the test, in the case of day image, when the threshold of Sobel edge detection technique was detected with second-order differential equation, there was the highest candidate lane detection rate which was 86.1%. In the threshold of Canny edge detection technique, the highest detection rate of 88.0% was found at Low=50, and High=300. In the case of night image, the threshold of Sobel edge detection technique, when horizontal calculation and vertical calculation had second-order differential equation, and when horizontal-vertical calculation had 1.5th-order differential equation, there was the highest detection rate which was 83.1%. In the threshold of Canny edge detection technique, the highest detection rate of 89.9% was found at Low=50, and High=300.