• Journal of Auto-vehicle Safety Association
• /
• v.8 no.2
• /
• pp.6-10
• /
• 2016

The objective of this paper is to understand value of active safety features on the customer perspective. In this study, 30 participants who don't have experience with active safety features were recruited and asked for preference, usefulness and consideration of each active safety feature after driving evaluation by them. Through this research, the preference of active safety features were analyzed and which of active safety features were the most useful and the most considered by customer when they purchase new vehicle. As a result, adaptive cruise control and side blind zone alert were the most strongly preferred and considered features by respondents and it means that respondents wanted comfort environment while driving and seemed to value features that compensated for limited visibility. On the other hand, active safety features that warned driver without control of the vehicle was deemed generally less desirable such as lane departure warning and forward collision alert. But autonomous emergency braking was higher than the other active safety features with only warning even if they did not have experience for it while this test. They thought it will be helpful in case of front-end collision situation even they just listened description before the test.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.1
• /
• pp.137-144
• /
• 2009

Understanding lane markings in a live video captured from a moving vehicle is essential to build services for intelligent vehicles such as LDWS(Lane Departure Warning Systems), unmanned vehicles, video-based car navigation systems. In this paper, we present a novel approach to recognize the color of lane markings and the lane number that he/she is driving on. More specifically, we present a background-color removal approach to understand the color of lane markings for various illumination conditions, such as backlight, sunset, and so on. In addition, we present a probabilistic network approach to decide the lane number. According to our experimental results, the proposed idea shows promising results to detect lane number in a various illumination conditions and road environments.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.11
• /
• pp.2492-2498
• /
• 2013

In this paper, A lane tracking algoritm 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. Using clustering and lane similarity function with noise suppression features are extracted. Finally, lane model is calculated using RANSAC and lane model is tracked using Kalman Filter. Experimental results show that the proposed algorithm can be processed within 20ms and its detection rate approximately 90% on the highway in a variety of environments.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.1
• /
• pp.126-136
• /
• 2014

In the Advanced Driver Assistance Systems (ADAS) of smart vehicle and Intelligent Transportation System (ITS) for to detect the boundary of lane is being studied a lot of Hough Transform. This method detects correctly recognition the lane. But recognition rate can fall due to detecting straight lines outside of the lane. In order to solve this problems, this paper proposed an algorithm to recognize the lane boundaries and the accumulator cells in Hough space. Based on proposed algorithm, we develop application for Android was developed by H/W verification. Users of smart phone devices could use lane detection and lane departure warning systems for driver's safety whenever and wherever. Software verification using the OpenCV showed efficiency recognition correct rate of 93.8% and hardware real-time verification for an application development in the Android phone showed recognition correct rate of 70%.

• International Journal of Highway Engineering
• /
• v.16 no.6
• /
• pp.169-179
• /
• 2014

PURPOSES : This study is to conduct the research on the design principle for the driver's safety and comfort in installing consecutive curves of superhighway. METHODS : Superhighway does not currently exist in domestic area. Thus, this study is conducted by collecting driving behavior usage of 30 people who are involved in the members of the virtual driving simulation. By identifying the distribution characteristics of each scenario in ANOVA & Tukey Test, the distribution are categorized into three groups. RESULTS : In the case of Group A in Section 3 (R2 entry part), lane departure exceeds the safety standard, which means to be risky condition. And then in the case of Group B and C, the lane departure values applying theoretical formula was evenly distributed compared to the proven values. CONCLUSIONS : Based on the result, the continuous curve design principles at superhighway should follow three standards as follow. First, an additional linear part needs to be inserted between two curves. Second, what if inserting the linear part is difficult, it would be better to insert a curve more than 2,000m. Third, R1/R2 ratio should not be over two. This design primarily aims to the safety of the operator. Such road alignment also meets the expectations of drivers, thus, it may help drivers to be compatible and amenable while driving continuous curve in superhighway.

• Smart Media Journal
• /
• v.6 no.3
• /
• pp.15-20
• /
• 2017

Recently, the automotive industry has been studied about driver assistance systems for helping drivers to drive their cars easily by integrating them with the IT technology. This study suggests a method of detecting lanes, robust to road condition changes and applicable to lane departure warning and autonomous vehicles mode. The proposed method uses the method of detecting candidate areas by using the Gaussian filter and by determining the Otsu threshold value and edge. Moreover, the proposed method uses lane gradient and width information through the Hough transform to detect lanes. The method uses road lane information detected before to detect dashed lines as well as solid lines, calculates routes in which the lanes will be located in the next frame to draw virtual lanes. The proposed algorithm was identified to be able to detect lanes in both dashed- and solid-line situations, and implement real-time processing where applied to Raspberry Pi 2 which is open source hardware.

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

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.5
• /
• pp.186-201
• /
• 2021

As autonomous driving technology advances, the accuracy of the vehicle position is important for recognizing the environments around driving. Map-matching localization techniques based on high definition (HD) maps have been studied to improve localization accuracy. Because conventional map-matching techniques estimate the vehicle position based on an HD map reference dataset representing the center of the lane, the estimated position does not reflect the deviation of the lateral distance within the lane. Therefore, this paper proposes a localization system based on the reference lateral position dataset extracted using image processing and HD maps. Image processing extracts the driving lane number using inverse perspective mapping, multi-lane detection, and yellow central lane detection. The lane departure method estimates the lateral distance within the lane. To collect the lateral position reference dataset, this approach involves two processes: (i) the link and lane node is extracted based on the lane number obtained from image processing and position from GNSS/INS, and (ii) the lateral position is matched with the extracted link and lane node. Finally, the vehicle position is estimated by matching the GNSS/INS local trajectory and the reference lateral position dataset. The performance of the proposed method was evaluated by experiments carried out on a highway environment. It was confirmed that the proposed method improves accuracy by about 1.0m compared to GNSS / INS, and improves accuracy by about 0.04m~0.21m (7~30%) for each section when compared with the existing lane-level map matching method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.11a
• /
• pp.273-275
• /
• 2011

본 논문에서는 허프변환 및 HSV 색변환을 이용한 효율적인 차선검출의 최적화 알고리즘을 제안한다. 차선 검출의 고속화를 위해 차선과 카메라의 위치를 감안하여 고정된 관심영역(ROI_LB)을 정하고 검출 영역을 감소시킨다. 정해진 관심영역 내에서 허프변환을 적용해 차선을 검출하고 이를 위해 Sobel Mask와 Threshold를 사용한다. 또한, HSV 색 공간을 이용하여 황색 선과 백색 선을 구별해내며 차선 이동 시에 "MOVEMENT"이라는 문자열을, 중앙선을 넘어가면 "DANGEROUS"이라는 문자열을 출력한다. 제안하는 방법의 실험 결과는 복잡한 도로 동영상에서 효과적으로 차선을 인식하고 색 구별을 하였으며 제안 방법의 유효성을 검증하기 위해 다양한 실제 차선 패턴을 대상으로 한 실험결과를 제시한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.06a
• /
• pp.332-333
• /
• 2018

본 논문에서는 딥러닝 기반의 주행 차로 인식 기법을 활용한 차선 변경 검출 기술을 제안한다. 제안한 방법은 주행 차로, 좌우 차로, 차량 등 3 종의 이미지 데이터를 학습, 검증, 실험 데이터로 나눠 활용하였다. 주행 차로 및 차선 변경 인식을 위하여 변형된 AlexNet 모델을 개발하였다. 실험 결과 주행 차로 69.45%, 좌우 차로 66.9%, 차량 76.4%의 인식률 결과를 보여 기존 패턴인식 방법과 비교하여 우수한 결과를 보였다.