• Title, Summary, Keyword: Curve Road Detection

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Model-based Curved Lane Detection using Geometric Relation between Camera and Road Plane (카메라와 도로평면의 기하관계를 이용한 모델 기반 곡선 차선 검출)

  • Jang, Ho-Jin;Baek, Seung-Hae;Park, Soon-Yong
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.2
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    • pp.130-136
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    • 2015
  • In this paper, we propose a robust curved lane marking detection method. Several lane detection methods have been proposed, however most of them have considered only straight lanes. Compared to the number of straight lane detection researches, less number of curved-lane detection researches has been investigated. This paper proposes a new curved lane detection and tracking method which is robust to various illumination conditions. First, the proposed methods detect straight lanes using a robust road feature image. Using the geometric relation between a vehicle camera and the road plane, several circle models are generated, which are later projected as curved lane models on the camera images. On the top of the detected straight lanes, the curved lane models are superimposed to match with the road feature image. Then, each curve model is voted based on the distribution of road features. Finally, the curve model with highest votes is selected as the true curve model. The performance and efficiency of the proposed algorithm are shown in experimental results.

Design of Curve Road Detection System by Convergence of Sensor (센서 융합에 의한 곡선차선 검출 시스템 설계)

  • Kim, Gea-Hee;Jeong, Seon-Mi;Mun, Hyung-Jin;Kim, Chang-Geun
    • Journal of Digital Convergence
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    • v.14 no.8
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    • pp.253-259
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    • 2016
  • Regarding the research on lane recognition, continuous studies have been in progress for vehicles to navigate autonomously and to prevent traffic accidents, and lane recognition and detection have remarkably developed as different algorithms have appeared recently. Those studies were based on vision system and the recognition rate was improved. However, in case of driving at night or in rain, the recognition rate has not met the level at which it is satisfactory. Improving the weakness of the vision system-based lane recognition and detection, applying sensor convergence technology for the response after accident happened, among studies on lane detection, the study on the curve road detection was conducted. It proceeded to study on the curve road detection among studies on the lane recognition. In terms of the road detection, not only a straight road but also a curve road should be detected and it can be used in investigation on traffic accidents. Setting the threshold value of curvature from 0.001 to 0.06 showing the degree of the curve, it presented that it is able to compute the curve road.

Survey on Detection and Recognition of Road Marking

  • Vokhidov, Husan;Hong, Hyung Gil;Hoang, Toan Minh;Kang, JinKyu;Park, Kang Ryoung;Cho, Hyeong Oh
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.1408-1410
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    • 2015
  • Information about the painted road markings and other painted road objects play an important part in keeping safety of drivers. Some researchers have presented research approaches and dealt with road markings detection. In this paper, we present comprehensive survey of these techniques, and review some of them like a machine learning method, template matching method for road markings detection and classification, method of detection and classification of road markings using curve-based prototype fitting, signed edge signature method.

A Study on the Installation Method of Delineation System Using Detection Distance and Lateral Position (인지거리와 측방위치를 이용한 시선유도시설의 설치방법에 관한 연구)

  • Jeon, Woo-Hoon;Cho, Hye-Jin
    • International Journal of Highway Engineering
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    • v.9 no.3
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    • pp.29-38
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    • 2007
  • This study investigated the effects of delineation systems on drivers' maneuver and how the effectiveness of delineation system can be further improved according to the road geometry. The experiments were conducted to collect lateral placement data and detection distance data using GPS equipped vehicles. The main results are summarizedas follows. Firstly, installing the delineation facilities on the roads helps drivers to recognize road alignment. Secondly, the detection distance is longer for delineators than for raised pavement marker in tangent section, while there is no difference in curve section. The chevron show the longest detection distance in the curve section, while the raised pavement markers showed no distinctive performance in terms of detection distance and lateral placement. Therefore, we can recommend install delineators in the tangent sections and chevrons in curve sections, based on the analysis results of effects of delineation facilities.

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Lane Detection Using Road Geometry Estimation

  • Lee, Choon-Young;Park, Min-Seok;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • pp.226-231
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    • 1998
  • This paper describes how a priori road geometry and its estimation may be used to detect road boundaries and lane markings in road scene images. We assume flat road and road boundaries and lane markings are all Bertrand curves which have common principal normal vectors. An active contour is used for the detection of road boundary, and we reconstruct its geometric property and make use of it to detect lane markings. Our approach to detect road boundary is based on minimizing energy function including edge related term and geometric constraint term. Lane position is estimated by pixel intensity statistics along the parallel curve shifted properly from boundary of the road. We will show the validity of our algorithm by processing real road images.

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The Detection of the Lane Curve using the Lane Model on the Image Coordinate Systems (이미지 좌표계상의 차선 모델을 이용한 차선 휨 검출)

  • 박종웅;이준웅;장경영;정지화;고광철
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.1
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    • pp.193-200
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    • 2003
  • This paper proposes a novel algorithm to recognize the curve of a structured road. The proposed algorithm uses an LCF (Lane Curve Function) obtained by the transformation of a parabolic function defined on world coordinate into image coordinate. Unlike other existing methods, the algorithm needs no transformation between world coordinate and image coordinate owing to the LCF. In order to search for an LCF describing the lane best, the differential comparison between the slope of an assumed LCF and the phase angle of edge pixels in the LROI (Lane Region Of Interest) constructed by the LCF is implemented. As finding the true LCF, the lane curve is determined. The proposed method is proved to be efficient through various kinds of images, providing the reliable curve direction and the valid curvature compared to the real road.

Real-Time Lane Detection Based on Inverse Perspective Transform and Search Range Prediction (역원근 변환과 검색 영역 예측에 의한 실시간 차선 인식)

  • Kim, S.H.;Lee, D.H.;Lee, M.H.;Be, J.I.
    • Proceedings of the KIEE Conference
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    • pp.2843-2845
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    • 2000
  • A lane detection based on a road model or feature all need correct acquirement of information on the lane in a image, It is inefficient to implement a lane detection algorithm through the full range of a image when being applied to a real road in real time because of the calculating time. This paper defines two searching range of detecting lane in a road, First is searching mode that is searching the lane without any prior information of a road, Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It is allow to extract accurately and efficiently the edge candidates points of a lane as not conducting an unnecessary searching. By means of removing the perspective effect of the edge candidate points which are acquired by using the inverse perspective transformation, we transform the edge candidate information in the Image Coordinate System(ICS) into the plane-view image in the World Coordinate System(WCS). We define linear approximation filter and remove the fault edge candidate points by using it This paper aims to approximate more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.

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Real-Time Lane Detection Based on Inverse Perspective Transform and Search Range Prediction (역 원근 변환과 검색 영역 예측에 의한 실시간 차선 인식)

  • Jeong, Seung-Gweon;Kim, In-Soo;Kim, Sung-Han;Lee, Dong-Hwoal;Yun, Kang-Sup;Lee, Man-Hyung
    • Journal of the Korean Society for Precision Engineering
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    • v.18 no.3
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    • pp.68-74
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    • 2001
  • A lane detection based on a road model or feature all needs correct acquirement of information on the lane in an image. It is inefficient to implement a lane detection algorithm through the full range of an image when it is applied to a real road in real time because of the calculating time. This paper defines two (other proper terms including"modes") for detecting lanes on a road. First is searching mode that is searching the lane without any prior information of a road. Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It allows to extract accurately and efficiently the edge candidate points of a lane without any unnecessary searching. By means of inverse perspective transform which removes the perspective effect on the edge candidate points, we transform the edge candidate information in the Image Coordinate System(ICS) into the plan-view image in the World Coordinate System(WCS). We define a linear approximation filter and remove faulty edge candidate points by using it. This paper aims at approximating more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.e fitting.

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Curb Detection and Following in Various Environments by Adjusting Tilt Angle of a Laser Scanner (레이저 스캐너의 틸트 각도 조절을 통한 다양한 환경에서의 연석 탐지 및 추종)

  • Lee, Dong-Wook;Lee, Yong-Ju;Song, Jae-Bok;Baek, Joo-Hyun;Ryu, Jae-Kwan
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.11
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    • pp.1068-1073
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    • 2010
  • When a robot navigates in an outdoor environment, a curb or a sidewalk separated from the road can be used as a robust feature. However, most algorithms could detect the curb only in the straight road, and could not detect highly curved corners, ramps, and so on. This paper proposes an algorithm which enables the robot to detect and follow the curbs in various types of roads. In the proposed method, the robot tilts a laser scanner and computes the error between the predicted and the measured distances to the road in front of the robot. Based on this error, the curbs at corners and curves can be classified. It is also difficult to detect a curb near a ramp because of its low height. In this case, the robot also tilts a laser scanner to detect the curb beyond the ramp. Once the robot classifies the road into the curve, corner, ramp, the robot selects the proper navigation strategies depending on the classified road types and is able to continue to detect and follow the curb. The results of a series of experiments show that the robot can stably detect and follows the curb in curves, corners and ramps as well as the straight road.

Lane and Curvature Detection Algorithm based on the Curve Template Matching Method using Top View Image (탑뷰(top view) 영상을 이용한 곡선 템플릿 정합 기반 차선 및 곡률 검출 알고리즘)

  • Han, Sung-Ji;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.6
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    • pp.97-106
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    • 2010
  • In this paper, lane and curvature detection algorithm based on the curve template matching method is proposed. To eliminate the perspective effect of the original image, the input image is transformed to a top view image. From this top view image, its edge image is created. To increase the accuracy of detection, a novel edge detection method, which shows a strength in lane detection, is proposed. In the first step, straight lanes are detected from the edge image, and then the Curve Template Matching(CTM) method is applied to detect the curved lanes and to find their curvatures. Since the proposed CTM method uses only the simple equations, such as line and circle equations, to detect the curved lane, the algorithm is simple. Moreover, we used the detected lane information in the previous frames to detect the current frame's lanes, the detection results become more reliable. The proposed algorithm has been tested in various road conditions (highway, urban street, night time highway, etc.). Experimental results show that the proposed algorithm can process about 70 frames per second with the successful lane detection rate over 95% and curvature detection rate about 90%.