• 대한교통학회지
• /
• 제31권4호
• /
• pp.32-46
• /
• 2013

고속도로의 도시부 구간에서는 IC간 구간의 길이가 짧아 단거리 통행 차량의 많은 이용으로 지 정체 현상의 원인이 되고 있다. 그리고 중앙버스전용차로가 시행되고 있는 고속도로는 버스가 버스전용차로에 진출입을 하면서 일반차로 차량 흐름에 방해를 주며 차량 간의 상충으로 위험한 상황을 초래하기도 한다. 이에 본 연구의 목적은 고속도로의 도시부 구간에서 효율적으로 운영하기 위한 새로운 차로운영 방안으로 버스전용차로를 활용한 Express Lane을 제안하고, 경부고속도로의 판교-한남구간을 대상으로 구축한 Express Lane에 대한 효과를 분석하는 것이다. 본 연구에서는 VISSIM 5.4를 활용하여 시나리오 설정에 따른 효과 분석을 실시하였다. 효과를 평가하기 위한 지표로 평균지체시간, 통행속도, 총 통행시간 등을 사용하였다. 분석 결과, 대상구간에서는 Express Lane의 수를 1개 설치할 경우에 가장 좋은 효과를 나타나고, 전체교통량 중 장거리 교통량이 25%를 차지할 때 가장 이상적인 교통상황이 구현되는 것으로 판단된다. 따라서 버스전용차로를 활용한 Express Lane 구축은 도로의 소통을 원활하게 할 뿐만 아니라 안전적, 비용적 측면에서도 긍정적인 효과를 나타내므로 의미있는 연구라고 판단된다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.1130-1133
• /
• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• 한국자동차공학회논문집
• /
• 제11권6호
• /
• pp.222-228
• /
• 2003

Lane departure avoidance system is one of the key technologies for the future active-safety passenger cars. The lane departure avoidance system is composed of two subsystems; lane sensing algorithm and active-steering controller. In this paper, the road image is obtained by vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active-steering controller is designed to prevent the lane departure. The developed active-steering controller can be realized by steer-by-wire actuator. The lane-sensing algorithm and active-steering controller are implemented into the steering HILS(Hardware-In-the-Loop Simulation) and their performance is evaluated with a human driver in the loop.

• 대한기계학회논문집A
• /
• 제26권8호
• /
• pp.1666-1671
• /
• 2002

A lane sensing algorithm using vision sensors is developed based on lane geometry models. The parameters of the lane geometry models are estimated by a Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from image plane to global coordinate assumes earth to be flat, but roll and pitch motions of a vehicle are considered from the perspective of the lane sensing. The proposed algorithm shows robust lane sensing performance compared to the conventional algorithms.

• Journal of information and communication convergence engineering
• /
• 제15권3호
• /
• pp.187-192
• /
• 2017

Autonomous driving vehicle research demands complex road and lane understanding such as lane departure warning, adaptive cruise control, lane keeping and centering, lane change and turn assist, and driving under complex road conditions. A fast and robust road lane detection subsystem is a basic but important building block for this type of research. In this paper, we propose a method that performs road lane detection from black box input. The proposed system applies Random Sample Consensus to find the best model of road lanes passing through divided regions of the input image under HSV color model. HSV color model is chosen since it explicitly separates chromaticity and luminosity and the narrower hue distribution greatly assists in later segmentation of the frames by limiting color saturation. The implemented method was successful in lane detection on real world on-board testing, exhibiting 86.21% accuracy with 4.3% standard deviation in real time.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
• /
• pp.222-224
• /
• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.

• 한국멀티미디어학회논문지
• /
• 제20권2호
• /
• pp.144-152
• /
• 2017

Among the technologies for implementing autonomous vehicles, advanced driver assistance system is a key technology to support driver's safe driving. In the technology using the vision sensor having a high utility, various preprocessing methods are used prior to feature extraction for lane detection. However, in the existing methods, the unnecessary lane candidates such as cars, lawns, and road separator in the road area are false positive. In addition, there are cases where the lane candidate itself can not be extracted in the area under the overpass, the lane within the dark shadow, the center lane of yellow, and weak lane. In this paper, we propose an efficient preprocessing method using k-means clustering for image division and the HSV color model. When the proposed preprocessing method is applied, the true positive region is maximally maintained during the lane detection and many false positive regions are removed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권12호
• /
• pp.4489-4501
• /
• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• 한국항행학회논문지
• /
• 제15권3호
• /
• pp.432-440
• /
• 2011

본 논문에서는 위성항법 기반 교통인프라에서 제공되는 정보를 이용하여 차로 구분에 적용할 때 차로 구분 성능을 향상시키기 위한 차로 제한 조건을 제시하고 시뮬레이션을 통하여 성능을 검증하였다. 차로 제한 조건은 차량의 진행 방향과 차량이 위치하고 있는 차로의 관계를 이용하여 1차로와 마지막 차로의 차로 구분 임계치를 크게 설정하여 차로 구분 성공률을 향상시키는 기법이다. 시뮬레이션 결과 차로 제한 조건을 사용할 경우 4차로에서는 40%, 6차로에서는 25%, 8차로에서는 15%의 성능차로 구분 성능이 향상됨을 확인하였다.

• 한국자동차공학회논문집
• /
• 제24권6호
• /
• pp.627-634
• /
• 2016

In this paper, an augmented video generation method to evaluate the performance of lane departure warning system is proposed. In our system, the input is a video which have road scene with general clean lane, and the content of output video is the same but the lane is synthesized with contamination image. In order to synthesize the contamination lane image, two approaches were used. One is example-based image synthesis, and the other is background-based image synthesis. Example-based image synthesis is generated in the assumption of the situation that contamination is applied to the lane, and background-based image synthesis is for the situation that the lane is erased due to aging. In this paper, a new contamination pattern generation method using Gaussian function is also proposed in order to produce contamination with various shape and size. The contamination lane video can be generated by shifting synthesized image as lane movement amount obtained empirically. Our experiment showed that the similarity between the generated contamination lane image and real lane image is over 90 %. Futhermore, we can verify the reliability of the video generated from the proposed method through the analysis of the change of lane recognition rate. In other words, the recognition rate based on the video generated from the proposed method is very similar to that of the real contamination lane video.