• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• 한국군사과학기술학회지
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• 제10권3호
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• pp.139-147
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• 2007

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.435-444
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• 2005

This paper presents a lane-departure identification (LDI) algorithm for a traveling vehicle on a structured road. The algorithm makes up for the weak points of the former method based on EDF[1] by introducing a Lane Boundary Pixel Extractor (LBPE), the well known Hough transform, and liner regression. As a filter to extract pixels expected to be on lane boundaries, the LBPE plays an important role in enhancing the robustness of LDI. Utilizing the pixels from the LBPE the Hough transform provides the lane-related parameters composed of orientation and distance, which are used in the LDI. The proposed LDI is based on the fact the lane-related parameters of left and right lane boundaries are symmetrical as for as the optical axis of a camera mounted on a vehicle is coincident with the center of lane; as the axis deviates from the center of lane, the symmetrical property is correspondingly lessened. In addition, the LDI exploits a linear regression of the lane-related parameters of a series of successive images. It plays the key role of determining the trend of a vehicle's traveling direction and minimizing the noise effect. Except for the two lane-related parameters, the proposed algorithm does not use other information such as lane width, a curvature, time to lane crossing, and of feet between the center of a lane and the optical axis of a camera. The system performed successfully under various degrees of illumination and on various road types.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.908-911
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• 2004

In this paper, we describe a robust image processing algorithm to recognize the road lane in real-time. For the real-time processing, a detection area is decided by a lane segment of a previous frame and edges are detected on the basis of the lane width. For the robust driving, the global threshold with the Otsu algorithm is used to get a binary image in a frame. Therefore, reliable edges are obtained from the algorithms suggested in this paper in a short time. Lastly, the lane segment is found by hough transform. We made a RC(Radio Control) car equipped with a vision system and verified these algorithms using the RC Car.

• 대한토목학회논문집
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• 제32권4D호
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• pp.305-311
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• 2012

단차로 무인 자동통행료 징수시스템(하이패스) 이용률증가와 함께 차단차로 운영, 차단기 작동 등에 따라 단차로 무인 자동통행료 징수시스템 차로 정체는 필연적이다. 이를 개선하기 위해 단차로 무인 자동통행료 징수시스템 차로 용량을 개선하기 위한 많은 연구가 진행 중이며, 대표적으로 스마트하이웨이사업에서 다차로 기반의 무정차 영업시스템(스마트톨링)을 들 수 있다. 본 고는 이러한 시스템의 효율성 개선으로써 스마트톨링의 용량증대 정도를 판단하고자 하였다. 이를 위해 기존 단차로 무인 자동통행료 징수시스템 자료를 바탕으로 스마트톨링시스템의 용량을 추정하는 방법을 제시하였다. 먼저, 단차로 무인 자동통행료 징수시스템 자료를 이용하여 포화차두시간을 산출한다. 그 다음으로 단차로 무인 자동통행료 징수시스템 차로의 용량을 산출한 다음, 단차로에서 다차로로 변경됨에 따라 바뀌는 주변도로환경을 계수화(양측장애물단측장애물 차로폭 및 측방여유폭 보정계수 증가분, 차단기 운영미운영 함에 따라 증가하는 용량 증가분, 차로폭 증가에 따른 용량 증가분)하고 이를 적용하여 다차로 용량을 추정하였다. 그 결과 각각의 경우 용량은 2172~2187대/시로 나타났으며, 기존 문헌에서 제시하는 최대값보다 약 370대/시 정도 많으며, 포화차두시간은 기존 단차로 무인 자동통행료 징수시스템의 차두시간에서 0.5초 정도 단축되어 용량개선 효과가 있는 것으로 판단되었다. 일부 한계와 향후연구사항이 같이 논의되었다.

• 한국도로학회논문집
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• 제8권2호
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• pp.75-85
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• 2006

현재 우리나라 2차로도로 횡단면 설계기준은 설계속도별 최소 차로폭과 길어깨 기준은 있으나, 다양한 횡단면 구성안이 없어 전국이 획일적인 도로구조 형태를 보이고 있다. 따라서 본 연구에서는 2차로도로의 사고유형별 원인을 규명하고 그에 따른 교통운영 및 안전성 측면에서 횡단면 개선 방안을 수립하고, 평가척도를 선정하였으며, 평가과정을 통해 새로운 횡단면 설계기준을 제시하고 이를 검증하였다. 연구결과 같은 2차로도 도로폭 $9{\sim}12.9m$ 보다 $6{\sim}8.9m$ 도로가 사고율이 매우 높은 것으로 나타났으며, 대표적 사고유형들의 개선점은 차로 및 길어깨 확장으로 나타났다. 시뮬레이션 결과 도로폭 6$\sim$7m 는 교통량 1,000vph에서 급격한 지체 시간 상승을 보이고 있으나. 도로폭 10$\sim$11.5m도로는 1.200vph에서 약간의 변화를 보였다. 이 결과(pcu/일)를 국도와 지방도 일평균교통량(대/일)분포와 비교분석 하여 다양한 횡단면 기준을 제시하였다.

• 한국안전학회지
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• 제32권4호
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• pp.107-113
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• 2017

This paper deals with the traffic factors related to the collisions of circular intersections. The purpose of this study is to develop traffic accident models by type of collision based on land use. In pursuing the above, the traffic accident data from 2010 to 2014 were collected from the "Traffic Accident Analysis System (TAAS)" data set of the Road Traffic Authority. A multiple regression model was utilized in this study to develop the traffic accident models by type of collision. 17 explanatory variables such as geometry and traffic volume factors were used. The main results are as follows. First, the null hypothesis that the type of land use does not affect the number of accidents by type of collision is rejected. Second, 10 accident models by type of collision based on land use are developed, which are all statistically significant. Finally, the ADT, inscribed circle diameter, bicycle lane, area of central island, number of speed hump, circulatory roadway width, splitter island, area of circulatory roadway, mean number of entry lane and mean width of entry lane are analyzed to see how they affect accident by type of accident based on land use.

• 대한전자공학회논문지SP
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• 제42권4호
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• pp.21-30
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• 2005

본 논문에서는 B-snake 차선 모델을 이용한 차선 검출 및 추적에 관한 알고리즘을 제안한다. 제안된 이론의 특성은 첫째, 다른 알고리즘에 비해 직선, 굴곡이 있는 도로와 같은 보다 넓은 범위의 차선 구조의 표현이 가능하며, 또한 평면 도로의 평행 특성을 이용하여 그림자, 잡음 등에 강하고, 둘째, 잡음에 강한 CHEVP(Canny/Hough Estimation Vanish Point) 알고리즘을 사용하여 차선 위치의 초기값을 제공한다. 셋째, GYP(Gradient Vector Flow)와 최소 평균 제곱 에러를 이용하여 B-Snake 차선 모델에서 발생하는 외부의 힘을 줄여 차선 검출의 에러를 줄이고 차선 추적을 효과적으로 수행한다. 측정 실험 결과 도로영상을 날씨 별로 맑은 날, 흐린 날 그리고 비오는 날로 구분하여 본 알고리즘을 수행하였으며 95$\%$ 이상의 차선 검출률을 보였다.

• 제어로봇시스템학회논문지
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• 제20권9호
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• pp.950-956
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• 2014

In this paper, the real-time detection method of a DDP (Driving Direction Point) is proposed for an unmanned vehicle to safely follow the center of the road. Since the DDP is defined as a center point between two lanes, the lane is first detected using a web camera. For robust detection of the lane, the binary thresholding and the labeling methods are applied to the color camera image as image preprocessing. From the preprocessed image, the lane is detected, taking the intrinsic characteristics of the lane such as width into consideration. If both lanes are detected, the DDP can be directly obtained from the preprocessed image. However, if one lane is detected, the DDP is obtained from the inverse perspective image to guarantee reliability. To verify the proposed method, several experiments to detect the DDPs are carried out using a 4 wheeled vehicle ERP-42 with a web camera.

• 한국안전학회지
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• 제32권5호
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• pp.135-140
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• 2017

This study deals with the safety of roundabout. The purpose of this study is to analyze the factors affecting the pedestrian accidents of roundabout near schools. In pursuing the above, this study gives particular attentions to comparatively analyzing the pedestrian accident by number of entry and circulatory lane. The traffic accident data from 2013 to 2015 are collected from TAAS data set of Road Traffic Authority. To develop the pedestrian accident model, the Poisson and negative binomial models has been utilized in this study. Such the dependent variable as the number of pedestrian accidents and the 24 independent variables as geometry, traffic volume and others are used. The main results are as follows. First, 3 Poisson and 2 negative binomial models(${\rho}^2$ of 0.153~0.426) which are all statistically significant are developed. Second, the common variable of models based on the number of circulatory roadway lane is analyzed to be the entry lane width and that of the number of entry lane is evaluated to be the design speed. Also specific variables are evaluated to splitter island, roundabout sign, number of approach road, bus stop and elementary school. Finally, the design speed might be expected to decrease the number of pedestrian accidents near schools.