• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.2
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• pp.255-263
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• 2016

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 the international committees such as ISO (the International Organization for Standardization) and UNECE (United Nations Economic Commission for Europe). 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 and proposed 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). And then, to evaluate the validity of the proposed test procedures, a series of experiments were conducted using commercially available two vehicles equipped with LKAS. Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1130-1133
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• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.187-192
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• 2017

Autonomous driving vehicle research demands complex road and lane understanding such as lane departure warning, adaptive cruise control, lane keeping and centering, lane change and turn assist, and driving under complex road conditions. A fast and robust road lane detection subsystem is a basic but important building block for this type of research. In this paper, we propose a method that performs road lane detection from black box input. The proposed system applies Random Sample Consensus to find the best model of road lanes passing through divided regions of the input image under HSV color model. HSV color model is chosen since it explicitly separates chromaticity and luminosity and the narrower hue distribution greatly assists in later segmentation of the frames by limiting color saturation. The implemented method was successful in lane detection on real world on-board testing, exhibiting 86.21% accuracy with 4.3% standard deviation in real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4489-4501
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• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• Annual Conference of KIPS
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• 2010.11a
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• pp.1628-1631
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• 2010

본 연구에서는 최근 인기를 끌고 있는 스마트폰 중 하나인 Apple 사의 iPhone 3GS 용 차선이탈경보 애플리케이션 개발을 수행하였다. 국내외적으로 수행되고 있는 지능형 자동차 연구를 통해 개발된 다양한 안전주행 지원 기술들이 단계적으로 상용화되면서 자동차를 지능화시키고 있는 시점에서 고가의 안전주행 지원장치를 대체할 수 있는 플랫폼으로 스마트폰을 활용하고, 안전주행 지원기술을 애플리케이션으로 개발하여 사용자가 쉽고 저렴하고 편리하게 사용할 수 있는 제품을 개발하고자 하였다. Before-Market 에만 집중된 차선이탈경보장치 기능을 iPhone 에 적용하기 위해서 제한된 컴퓨팅 자원을 효율적으로 활용할 수 있는 차선인식알고리즘이 필요하고, 본 연구에서는 Hough Transform 기반의 알고리즘을 사용하였다. 이외에도 iPhone 이라는 플랫폼의 여러 가지 특징을 고려하여 애플리케이션을 개발하였다. 효율적인 영상처리를 위해 OpenCV 라이브러리를 사용하였고, 개발은 매킨토시 컴퓨터에서 개발 후 iPhone 에 탑재하여 확인하였다. 현재까지 개발된 애플리케이션의 기능에서 보완할 점은 차선인식률과 처리 속도를 향상 시키는 것이다. 2011 년 2 월까지 완제품을 개발하여 앱스토어에 등록하는 것을 목표로 하고 있으며, 향후 안드로이드용 애플리케이션도 개발할 계획이다.

• Journal of Auto-vehicle Safety Association
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• v.6 no.1
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• pp.27-32
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• 2014

A study assessing driver acceptance level for various active safety systems against Korean drivers has been conducted. A 2013 Cadillac ATS model vehicle was tested along southern outskirt of Seoul including local roadway and interurban highway. Active safety systems included were FCA(Forward Collision Alert), LDW(Lane Departure Warning), SBZA(Side Blind Zone Alert), FRPA(Front/Rear Park Assist), RCTA(Rear Cross Traffic Alert), ACC(Adaptive Cruise Control), and AEB(Autonomous Emergency Braking). Participants experienced the FRPA, RCTA and AEB features in a controlled parking lot with a dummy vehicle and traffic cones as target obstacles. Remaining features have been tested on the accumulated stretched of 106 km long urban and interurban roadway. Series of questionnaires corresponding to each active safety systems have been conducted. Tentative results revealed that RCTA and SBZA systems received favourable ratings compared to the other ones.

• Annual Conference of KIPS
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• 2013.11a
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• pp.1540-1543
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• 2013

최근 자동차 관련 연구 분야 중 안전사고 예방에 대한 관심이 높아짐에 따라 안전지능형 기술들의 연구가 활발히 이루어지고 있다. 졸음운전과 같이 운전자의 의지와 상관없는 무의식적인 차선 이탈은 중앙선 침범으로 이어져 대형 사고를 유발할 가능성이 크다. 이와 같은 요인들은 의식적인 상황에서의 차량의 통제를 방해하고 결국 예기치 않은 차선 이탈로 연결될 수 있다. 따라서 본 논문에서는 차선 이탈 여부를 미리 판단하여 주행차선을 이탈하기 전에 운전자게에 알려줌으로써 운전자의 안전을 향상 시켜주며 자동차 안전사고 예방기술에 관련하여 차선검출과 차선이탈경고시스템 알고리즘을 설계하였다.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.103-107
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• 2013

In this paper, A real-time lane tracking algorithm is proposed for lane departure warning system. To eliminate perspective effect, input image is converted into Bird's View by inverse perspective mapping. Next, suitable features are extracted for lane detection. Lane feature that correspond to area of interest and RANSAC are used to detect lane candidates. And driving lane is decided by clustering of lane candidates. Finally, detected lane is tracked using the Kalman filter. Experimental results show that the proposed algorithm can be processed within 30ms and its detection rate is approximately 90% on the highway in a variety of environments such as day and night.

• Journal of Auto-vehicle Safety Association
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• v.7 no.1
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• pp.33-39
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• 2015

This study examined the drivers' acceptance level of various active safety features with Korean drivers on Seoul urban and city roads. The test vehicle, 2013 Cadillac ATS, was equipped with FCA(Forward Collision Alert), LDW(Lane Departure Warning), SBZA(Side Blind Zone Alert), FRPA(Front/Rear Park Assist), RCTA(Rear Cross Traffic Alert), ACC(Adaptive Cruise Control), and AEB(Autonomous Emergency Braking). Participants had chances to run the tests on those systems in the parking lot accompanied by the 106km long stretch of predetermined route including local road and interurban highway in Seoul and Gyeonggi-do under normal traffic flowing environment. After the test, participants completed a series of questionnaires about the features they experienced. The results revealed that RCTA and SBZA systems received more favourable ratings compared to the other features in avoiding crashes. The respondents preferred sound alerts to haptic ones even though haptic warning methods were better in providing directional information.