• Title/Summary/Keyword: 차선 예측

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Methodology to Predict Service Lives of Pavement Marking Materials (도로 차선 재료의 공용수명 예측방법)

  • Oh, Heung-Un;Lee, Hyun-Seock;Jang, Jung-Hwa;Kang, Jai-Soo
    • International Journal of Highway Engineering
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    • v.10 no.4
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    • pp.151-159
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    • 2008
  • Performances of retroreflectivity vary place to place, according to traffic volumes and time lengths after striping, depending on pavement marking materials and colors. The present paper uses the nation wide data of retroreflectivity, which has been collected from freeways and then tries to develop the regression curve setting traffic volume and service life as independent variables and retroreflectivities as dependent variables. The DB system includes two year's measurement in $2005{\sim}2006$ over Korean freeway pavement marking at an interval of three months for the period. The mobile measurement system, a laserlux, was employed for the purpose. The DB has provided a lot of information about materials and performance of the specific pavement marking such as geometric features, traffic volumes, material characteristics and the installation date. This study provides the comparison of pavement marking performances under diversified conditions. Based on accumulated pavement marking performances, this study provides performance curves based on the diversified factors. The goal of the retroreflectivity modeling is to develop equations that can be used to estimate an average retroreflectivity of pavement markings as a function time since application and traffic volume. After representing the variation of retroreflectivities and estimating regression curves by linear, exponential, logarithmic and power function, the regression curve which had the highest coefficient of determination and the value similar to the last field measurement was regarded as the retroreflectivity decay model. As a result of verification, the decay model showed the signification within the 90% confidence level and especially showed the clear relation with field data according to increase of cumulative vehicle exposure. Accordingly, these models can be used to determine service lives, retroreflectivity degradation rates, and retroreflectivity of new markings.

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Real-time Lane Detection Method using Inverse Perspective Transform and Lane Filter (역 투시변환과 차선 필터를 이용한 실시간 차선 검출방법)

  • Heo, Hwan;Kim, Sung-Hun;Chae, Il-Moon;Han, Ki-Tea
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.545-548
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    • 2012
  • 본 논문에서는 영상내 관심영역의 역 투시변환과 차선검출필터를 적용한 실시간 차선검출방법을 제안한다. 영상의 시작 프레임에서 소실점을 찾고 이를 기준으로 관심영역을 설정하고 차선을 예측하였으며, 예측된 차선을 기반으로 역 투시변환계수를 추출하여 원근감이 제거된 영상을 얻고, 이로부터 차선을 검출하였다. 제안한 방법은 원근감이 제거된 영상에 차선검출 필터를 적용하여 차선을 검출하는 방법으로, 처리영역을 축소하고 처리과정을 단순화 함으로써 초당 50 frames 정도의 양호한 차선검출 결과를 보였다.

A Curve Lane Detection Method using Lane Variation Vector and Cardinal Spline (차선 변화벡터와 카디널 스플라인을 이용한 곡선 차선 검출방법)

  • Heo, Hwan;Han, Gi-Tae
    • 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.

Lane Detection & Prediction of Vihicle's Progress-Direction Using improved Hough Transform (차선 인식을 위한 Hough Transform과 차량 진행 방향 예측)

  • Kang, Sei-Bum;Yang, Seung-Ju;Kim, Eun-Ju;Lyu, Sung-Pil
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.04a
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    • pp.165-168
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    • 2009
  • 차선 검출을 위한 영상처리연구는 Hough Transform을 이용하는 방법과 주파수 변환 방법, 히스토그램을 이용하는 방법, 템플릿을 이용하는 방법등이 사용되고 있다. 차선 검출에 가장 많이 사용되는 Hough Transform은 연산 과정이 복잡하여 차량의 속도가 증가하면 실제 상황과 오차가 생길 확률이 높다. 이러한 문제를 해결하기 위해 영상을 분할하여 최소한의 영역을 처리하여 처리량을 줄였으며, 차선 이외의 선이 추출될 경우 그 선의 각도와 위치를 고려하여 연산에 방해되는 선을 삭제한다. 또한 고속으로 진행하는 차량의 경우, 점선으로 이루어져 선이 보이지 않는 부분에서는 차선의 인식이 불가능하여 위험한 상황을 초래한다. 따라서 최소한의 차선을 이용하여 차선을 연장하고, 여러 직선으로 곡선을 표현하여 차량 진행 방향을 예측할 수 있다.

Lane Departure Detection Using a Partial Top-view Image (부분 top-view 영상을 이용한 차선 이탈 검출)

  • Park, Han-dong;Oh, Jeong-su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.8
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    • pp.1553-1559
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    • 2017
  • This paper proposes a lane departure detection algorithm using a single camera equipped in front of a vehicle. The proposed algorithm generates a partial top-view image for a small ROI (region of interest) designated on the top-view space form the image acquired by the camera, detects lanes on the small partial top-view image, and makes a decision on the lane departure by checking overlap between the pre-assigned virtual vehicle and the detected lanes. The proposed algorithm also includes the removal of lines occurred by road symbols (noises) disturbing the lane departure detection between lanes and the prediction of lost lanes using lane information of previous fames. In lane departure detection test using real road videos, the proposed algorithm makes the right decision of 99.0% in lane keeping conditions and 94.7% in lane departure conditions.

A Robust Real-Time Lane Detection for Sloping Roads (경사진 도로 환경에서도 강인한 실시간 차선 검출방법)

  • Heo, Hwan;Han, Gi-Tae
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.6
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    • pp.413-422
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    • 2013
  • In this paper, we propose a novel method for real-time lane detection that is robust for inclined roads and not require a camera parameter, the Inverse Perspective Transform of the image, and the proposed lane filter. After finding the vanishing point from the start frame of the image and storing the region surrounding the vanishing point as the Template Area(TA), our method predict the lanes by scanning toward the lower part from the vanishing point of the image and obtain the image removed the perspective effect using the Inverse Perspective Transform coefficients extracted based on the predicted lanes. To robustly determine lanes on inclined roads, the region surrounding the vanishing point is set up as the template area (TA), and, by recalculating the vanishing point by tracing the area similar to the TA (SA) in the input image through template matching, it responds to the changes on the road conditions. The proposed method for a more robust lane detection method for inclined roads is a lane detection method by applying a lane detection filter on an image removed of the perspective effect. Through this method, the processing region is reduced and the processing procedure is simplified to produce a satisfactory lane detection result of about 40 frames per second.

Lane detection system for self-driving car (이동 상황에서의 실시간 차선 인식을 통한 무인자동차 제어 - labeling을 사용한 dynamic한 상황에서의 강인한 차선 인식)

  • Kim, Hyun-Jun;Ryu, Moon-Wook;Lee, Suk-Han
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.205-209
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    • 2008
  • Recently, for development of hardware systems, it has been comercially developed for lane detection system of assistive funtion to drivers. There are so many driving systems that is capable of detecting lane for ideal environment like quite visible lane and sweep curve just like highway, but these kinds of system are hard to apply for self driving system because it is difficult to detect lane in dynamic environment, which have rapid curve or only one sided lane For this paper, we proposed intelligent driving system that is able to detect the lane in case of rapid curve by labeling, or one sided lane by lane prediction. based on experimental results, we prove our lane detection system is able to detect lane not only in ideal environment, but also environment which have rapid curve or one sided lane.

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Lane Information Fusion Scheme using Multiple Lane Sensors (다중센서 기반 차선정보 시공간 융합기법)

  • Lee, Soomok;Park, Gikwang;Seo, Seung-woo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.12
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    • pp.142-149
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    • 2015
  • Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.

Speed Prediction Models for Freeway Merging Area (고속도로 연결로 접속부에서의 속도 추정 모형)

  • 신치현
    • 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.

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Steering Control of an Autonomous Vehicle Using CNN (CNN을 이용한 자율주행차 조향 제어)

  • Hwang, Kwang-Bok;Park, Jin-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.7
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    • pp.834-841
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    • 2020
  • Among the autonomous driving systems based on visual sensors, the control method using a vanishing point is the most general method for autonomous driving. However, if the lane is lost or does not exist, it is very difficult to detect this and estimate the vanishing point. In this paper, we predict the vanishing point of the road and the vanishing point lines on the left and right sides using CNN for the camera image and design the steering controller for autonomous driving from the predicted results. As a result of the simulation, it was confirmed that the proposed method well tracked the center of the road regardless of the presence or absence of a solid lane, and was superior to the control method using a general method using the vanishing point.