• Journal of Auto-vehicle Safety Association
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• v.6 no.2
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• pp.29-35
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• 2014

Lane Keeping Assistance System(LKAS) is a kind of Advanced Driver Assistance Systems(ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in international committees such as ISO(the International Organization for Standardization). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP(Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System(LDWS). Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1778-1784
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• 2016

we improved the performance by parallelizing lane detection algorithms. Lane detection, as a intellectual assisting system, helps drivers make an alarm sound or revise the handle in response of lane departure. Four kinds of algorithms are implemented in order as following, Gaussian filtering algorithm so as to remove the interferences, gray conversion algorithm to simplify images, sobel edge detection algorithm to find out the regions of lanes, and hough transform algorithm to detect straight lines. Among parallelized methods, the data level parallelism algorithm is easy to design, yet still problem with the bottleneck. The high-speed data level parallelism is suggested to reduce this bottleneck, which resulted in noticeable performance improvement. In the result of applying actual road video of black-box on our parallel algorithm, the measurement, in the case of single-core, is approximately 30 Frames/sec. Furthermore, in the case of octa-core parallelism, the data level performance is approximately 100 Frames/sec and the highest performance comes close to 150 Frames/sec.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.216-216
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• 2000

In this paper, we introduce a new roadway-departure prevention algorithm and the developed Hardware-in-the-Loop-Simulator (HiLS) for applying the new algorithm. A sliding-mode controller is used for lateral position control. And, the HiLS consists of real car elements, a micro-control board, and a self-aligning torque generator Finally from the display module, the perspective view and bird view of the animated vehicle can be seen simultaneously.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• Journal of Auto-vehicle Safety Association
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• v.8 no.1
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• pp.13-18
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• 2016

More than 80 percent of traffic accidents related with lane departure believed to be the result of crossing the lane due to either negligence or drowsiness of the driver. Lane-departure related accident in the highway usually involve high fatality. Even though LDWS is believed to prevent accident 25% and reduce fatalities by 15% respectively, its effectiveness in performance is yet to be confirmed in many aspects. In this study, the vehicle lateral locations relative to warning zone envelop (earliest and latest warning zone) defined in ISO standard, ECE and NHTSA regulations are compared with respect to various factors including delays, vehicle speed and vehicle heading angle with respect to the lane. Since LDWS is designed to be activated at the speed over 60 km/h, vehicle speed range for the study is set to be from 60 to 100 km/h. The vehicle heading angle (yaw angle) is set to be up to 5 degree away from the lane (abrupt lane change) considering standard for lane change test using double lane-change test specification. The TLC is calculated using factors like vehicle speed, yaw angle and reaction time. In addition, the effect of vehicle type and reaction time have been considered to assess LDWS safety.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.671-674
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• 2018

In this study, we implement a YOLO driving assistance system using a model car. The YOLO is an object detection and recognition algorithm using deep running which is becoming an issue recently. The system alerts the lane departure by applying the image processing technology to the image acquired through the camera, recognizes the objects using the YOLO, and performs various functions according to the type of the object and the distance between the vehicle. the YOLO, which is superior to the existing object detection and recognition algorithm, improves the performance of the driving assist system without additional equipment. The driving assist system using the YOLO will ensure the safety of the driver with low cost.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.40-47
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• 2014

This paper proposes a matching method of GIS lane information with a vehicle position using camera image to reduce DGPS error. Images of straight road are taken using a camera that is installed on the front center of the vehicle, and the distance between the vehicle and the lane are estimated using the images. The current GIS lane data is matched by comparing the estimated distance and the measured distance using a DGPS. Inverse perspective mapping is used to minimize the error of image processing from the heading angle, and single buffering method is applied to decide the exact moment of GIS match. Through practical test on the highway, feasibility of the GIS matching using camera image is confirmed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.317-318
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• 2022

최근 인공지능 기술이 발전함에 따라 자율주행, 첨단 운전자 지원 시스템과 같은 기술들이 개발되고 있다. 이런 기술들은 교통사고를 예방하여 사망률 등을 감소시키고, 운전자의 편의성을 향상시킨다. 본 논문에서는 자율주행과 첨단 운전자 지원 시스템에서 사용할 수 있는 기술들을 개발하고, 이를 RC카에 적용하여 구현하였고, 인공트랙에서 실험하여 평가하였다. 딥러닝 기반 실시간 객체 인식 및 Opencv 를 이용한 차선 인식기술을 통해 차선을 인식하여 이탈하지 않고 주행하며 표지판 등 객체를 인식하여 상황에 따른 대응으로 모터를 제어하는 기술을 개발하고 인공트랙을 자율주행하는 RC카를 구현하고 실험하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1081-1087
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• 2015

This article aims to provide a design method of warning thresholds for active safety systems based on the performance-based approach considering driver behaviors. Both positive and negative consequences of warnings are considered, and the main idea is to choose a warning threshold where the positive consequence is maximized, whereas the negative consequence is minimized. The process of the performance-based approach involves: Defining the operating scenarios; setting the trajectory models, including human characteristics; estimating the alert and nominal trajectories; estimating the performance metrics; generating a performance-metric plot; and determining the alert thresholds. This paper chose a lane-departure warning system as an example to show the usefulness of the performance-based approach. Both human and sensor characteristics were considered in the system design, and this paper provided a quantitative method to include human factors in designing active safety systems.