• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.277-284
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• 2014

The detection method of curves for the lanes which is powerful for the variation by utilizing the lane variation vector and cardinal spline on the inverse perspective transformation screen images which do not required the camera parameters are suggested in this paper. This method detects the lane area by setting the expected lane area in the s frame and next s+1 frame where the inverse perspective transformation and entire process of the lane filter are adapted, and expects the points of lane location in the next frames with the lane variation vector calculation from the detected lane areas. The scan area is set from the nextly expected lane position and new lane positions are detected within these areas, and the lane variation vectors are renewed with the detected lane position and the lanes are detected with application of cardinal spline for the control points inside the lane areas. The suggested method is a powerful method for curved lane detection, but it was adopted to the linear lanes too. It showed an excellent lane detection speed of about 20ms in processing a frame.

• 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 Korean Society of Transportation
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• v.4 no.1
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• pp.72-87
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• 1986

본 연구의 목적은 주가로상 좌회전운전자의 문격수낙특성(gap-acceptance characteristics)을 파악하는 데 있다. 이 목적을 달성하기 위하여 포켓컴퓨터를 이용한 새로 운 자료수집기법이 개발되었다. 이 기법은 적은 비용으로 정확한 자료의 수집을 가능하게 하였다. 연구교차로는 마산시의 부도심에 위치한 2차선가로 및 4차선가로상의 전형적인 신 호등 비설치교차로가 선정되었다. 정규분포 및 대수정규분포가 probit분석을 이용하여 임계 수낙문격분포(critical acceptance gap distribution)로 검정되었다. 두 분포들은 5% 우의수준 에서 기각되지 않았다. 2차선가로의 임계수낙문격은 2.9∼3.0초의 범위였으며 표준편차는 1. 2∼1.5초의 범위였고, 4차선가로는 각각3.3∼3.4초와 1.3∼1.5초의 범위였다. 2차선가로의 임 계 lag는 2.6초였으며 4차선가로의 임계lag는 3.2초이었다. 국내 좌회전운전자의 임계수낙문 격이 미국인의 것에 비하여 짧은 것으로 나타났다. 이는 도시교통류의 주구성 차량이 직업 운전자들이 운전하는 소형 택시로 이루어지는 운전자 및 차량특성에 기인한 것으로 볼 수 있다.

• Journal of Korean Society of Transportation
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• v.13 no.3
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• pp.99-120
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• 1995

가속차선이 교통류의 운영상태와 안전에 기여하는 바는 벌써부터 인식되어 왔으나 이 변속차선이 유입형 연결로 접속부 전체의 운영에 미치는 영향을 수치화하거나 체계적으로 평가하기 위해 현장 자료를 바탕으로 한 실험적 연구는 진행되어 오지 못하엿다. 현재 널리 참고되고 있는 1985년 USHCM의 접속부 운영상태 분석 방법론은 단지 차선 1의 교통량을 예측하는 데 주안점을 두고 있는데 가속 차선의 길고 짧음에 따라 접속부 바로 전 차선 1의 교통량 분포가 크게 변화한다는 사실(많은 현장 관측을 통해 확인)은 고려하지 못하고 있다. 이는 접속부 운영 상태가 같은 교통량 조건하에서도 크게 차이가 나나다는 것을 뜻하며 가속차선의 존재를 무시한채 운영과 관련한 MOE를 도출하는 것이 서비스수준 산정 방법으로 충분한 것인가 하는 의문을 자연히 낳게 한다. 본 논문은 가속차선이 고속도로 연결로 접속부의 운영에 미치는 영향을 주로 다루고 있다. 가속차선의 독립적인 역할과 영향을 체계적으로 관찰하기 위해 미국내 여러 지역에서 8개의 고속도로 연결로접속부를 선택하고 각 지점에 접속부의 상하류 지역을 포함하는 2,000ft 구간내에 다섯대의 카메라를 설치, 지점별로 약 3시간 동안 자료를 수집하였다. 총 193개 자료수의 분석을 통해서 다중 회귀 모형을 구성하는 독립변수로 가속차선의 길이를 사용하는 것이 타당하다고 결론지었으며, 접속부 운영의 질, 특히 속도를 추정하기 위한 모형을 수립하였다. 본 연구를 통해 얻어진 관점과 방법론은 1994USHCM 고속도로 연결로 분석 방법론 설정에 일부분 반영되고 잇으며 특히 교통운영과 흐름의 방식에서 유사한 엇갈림 구간의 분석 방법과 일관성 있는 분석 체계 마련을 위해서 서비스수준 산정 절차 정립에 엇갈림 알고리즘을 활용하는 방안을 제시하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2755-2761
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• 2012

In this paper, a lane detection algorithm using Eccentricity calculation is proposed. Lane detection is used for lane departure warning which can support safe driving to prevent accidents. In other to enhance the detection rate, we define the Eccentricity calculation which is introduced in graph theory, and evaluate the Eccentricity. The Eccentricity for any straight line is equal to 1, hence computing the Eccentricity allows the implementation of a first order equation. As a results of simulation, we confirmed that the proposed algorithm was enhanced by time and space complexity, and superior to the performance of the conventional lane detections.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.9-16
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• 2012

The performance of road markings is classified into the visibility at daytime, night time, wet condition and rainy conditions. The objective of this study is to obtain the driving safety of drivers under conditions of unstable weather condition such as the rain. The visibility of road markings is closely related to the preview time and detection distances and the ways to improve road marking materials and increase the dry retroreflectivity and wet retroreflectivity, which are the measures of daytime and nighttime visibility is researched to decrease the traffic accidents. For this purpose, Road marking glass beads with the refraction rate of 1.5 and 2.2 are introduced to raise the retroreflectivity. After investigating the minimum threshold retroreflectivity and Install Minimum retroreflectivity at home and abroad, minimum control values for the roadmarking visibility and improvement of nightime rainy retroreflectivity are suggested by physical properties and retroreflectivity experiments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.1-11
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• 2021

This paper presents a procedure to extract lane line models using a set of proposed methods. Firstly, an image warping method based on homography is proposed to transform a target image into an image which is efficient to find lane pixels within a certain region in the image. Secondly, a method to use the combination of the results of edge detection and HSL (Hue, Saturation, and Lightness) transform is proposed to detect lane candidate pixels with reliability. Thirdly, erroneous candidate lane pixels are eliminated using a selection area method. Fourthly, a method to fit lane pixels to quadratic polynomials is proposed. In order to test the validity of the proposed procedure, a set of black-box images captured under varying illumination and noise conditions were used. The experimental results show that the proposed procedure could overcome the problems of color-only and edge-only based methods and extract lane pixels and model the lane line geometry effectively within less than 0.6 seconds per frame under a low-cost computing environment.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.88-93
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• 2012

Lane detection methods using camera, which are part of the driver assistance system, have been developed due to the growth of the vehicle technologies. However, lane detection methods are often failed by varying road conditions such as rainy weather and degraded lanes. This paper proposes a method for lane detection which is robust in varying road condition. Lane candidates are extracted by intensity comparison and lane detection filter. Hough transform is applied to compute the lane pair using lane candidates which is straight line in image. Then, a curved lane is calculated by using B-Snake algorithm. Also, weighting value is computed using previous lane detection result to detect the lanes even in varying road conditions such as degraded/missed lanes. Experimental results proved that the proposed method can detect the lane even in challenging road conditions because of weighting process.

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

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.85-94
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• 2012

Lane marking detection is essential to both ITS and DAS systems. The objective of this paper is to provide more robust technique for lane marking detection than traditional techniques by using scale-space technique. Variable thresholding that is based on the local statistics may be very effective for detecting such objects as lane markings that have prominent intensities. However, such techniques that only rely on local statistics have limitations containing irrelevant areas as well. We reduce the candidate areas by combining the variable thresholding result with cost-efficient horizontal 1D LoG filtered scale space. Through experiments using practical images, we could achieve significant improvement over the techniques based not only on the variable thresholding but also on the Hough transform that is another very popular technique for this purpose.