• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.103-107
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• 2013

In this paper, A real-time lane tracking algorithm is proposed for lane departure warning system. To eliminate perspective effect, input image is converted into Bird's View by inverse perspective mapping. Next, suitable features are extracted for lane detection. Lane feature that correspond to area of interest and RANSAC are used to detect lane candidates. And driving lane is decided by clustering of lane candidates. Finally, detected lane is tracked using the Kalman filter. Experimental results show that the proposed algorithm can be processed within 30ms and its detection rate is approximately 90% on the highway in a variety of environments such as day and night.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.64-73
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• 2011

This paper presents an algorithm for tracking lanes on the road based on corner detection techniques. The proposed algorithm shows high accuracy regardless of lane divider types, eg, solid line, dashed line, etc, and thus is of advantage to city streets and local roads where various types of lane dividers are used. A set of experiments was conducted on real roads with various types of lane dividers and results show an extract ratio over 87% in average.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2492-2498
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• 2013

In this paper, A lane tracking algoritm is proposed for lane departure warning system. To eliminate perspective effect, input image is converted into Bird's View by inverse perspective mapping. Next, suitable features are extracted for lane detection. Using clustering and lane similarity function with noise suppression features are extracted. Finally, lane model is calculated using RANSAC and lane model is tracked using Kalman Filter. Experimental results show that the proposed algorithm can be processed within 20ms and its detection rate approximately 90% on the highway in a variety of environments.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.325-328
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• 2019

자율주행 자동차는 운전자가 개입하지 않고 차량에 부착된 다양한 센서를 통해 얻은 데이터를 기반으로 차량을 스스로 제어하며 설정한 목적지까지 주행한다. 본 논문에서는 단일 카메라와 영상을 사용한 차선 검출하고 추적하는 방법을 제안한다. 영상의 하단 부분만 분리하여 차선을 검출하기 위하여 외곽선 검출 과정을 거친 후 허프 변환을 통해 양 차선의 중심을 구한다. 이 값을 바탕으로 PID 제어로 차량의 차선을 유지한다. 모형 차량과 모형 트랙에서 차선 인식 후 차선을 추적하여 주행하는 동작을 시험하였다. PID 제어를 위헌 적정 각 항의 값을 구하였다. 시험 결과 차선 검출 알고리즘은 성공적으로 동작함을 확인할 수 있었다.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.619-623
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• 2008

A lane detection system is one of the major components of intelligent vehicle systems. Difficulties in lane detection mainly come from not only various weather conditions but also a variety of special environment. This paper describes a simple and stable method for the broken lane tracking in various environments. Probabilistic Hough Transform (PHT) and the Least-square method (LSM) are used to track and correct the lane orientation. For the efficiency of the proposed method, two regions of interest (ROIs) are placed in the lower part of each image, where lane marking areas usually appear with less intervention in our system view. By testing in both a set of static images and video sequences, the experiments showed that the proposed approach yielded robust and reliable results.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.359-370
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• 2007

Lane tracking and obstacle avoidance are considered two of the key technologies on an unmanned ground vehicle system. In this paper, we propose a method of lane tracking and obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. First, obstacle avoidance consists of two parts: a longitudinal control system for acceleration and deceleration and a lateral control system for steering control. Each system is used for unmanned ground vehicle control, which notes the vehicle's location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacle and perform obstacle avoidance on the road, which involves vehicle velocity. Second, we explain a method of lane tracking by means of a vision system, which consists of two parts: First, vehicle control is included in the road model through lateral and longitudinal control. Second, the image processing method deals with the lane tracking method, the image processing algorithm, and the filtering method. Finally, in this paper, we propose a method for vehicle control, modeling, lane tracking, and obstacle avoidance, which are confirmed through vehicles tests.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.21-30
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• 2005

In this paper, we propose lane detection and trackinB algerian using B-Snake as robust algorithm. One of chief virtues of Lane detection algorithm using B-Snake is that it is possible to specify a wider range of lane structure because B-Spline conform an arbitrary shape by control point set and that it doesn't use any camera parameter. Using a robust algorithm called CHVEP, we find the vanishing point, width of lane and mid-line of lane because of the perspective parallel line and then we can detect the both side of lane mark using B-snake. To demonstrate that this algorithm is robust against noise, shadow and illumination variations in road image, we tested this algorithm about various image divided by weather-fine, rainy and cloudy day. The percentage of correct lane detection is over 95$\%$.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.29-39
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• 2019

As mobile robot applications increase in real life, the need of low cost autonomous driving are gradually increasing. We propose a novel vision-based real-time lane detection and tracking system that supports autonomous driving of mobile robots in constrained tracks which are designed considering indoor driving conditions of mobile robots. Considering the processing of lanes with various shapes and the pre-adjustment of operation parameters, the system structure with multi-operation modes are designed. In parameter tuning mode, thresholds of the color filter is dynamically adjusted based on the geometric property of the lane thickness. And in the unstable input mode of curved tracks and the stable input mode of straight tracks, lane feature pixels are adaptively extracted based on the geometric and temporal characteristics of the lanes and the lane model is fitted using the least-squared method. The track centerline is calculated using lane models and the motion model is simplified and tracked by a linear Kalman filter. In the driving experiments, it was confirmed that even in low-performance robot configurations, real-time processing produces the accurate autonomous driving in the constrained track.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.331-334
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• 2013

본 논문에서는 차량에 부착된 4대의 어안렌즈 카메라 영상을 이용하여 차량 주위 전방향의 주변 정보를 포함하는 정합 영상을 생성하고, 생성된 정합 영상에서 차선을 검출하는 알고리즘을 제안한다. 기존의 전방 카메라만을 이용하여 차선을 검출하는 방법들은 안개와 같이 기상 환경이 안 좋은 경우 가시거리가 짧아져 정상적인 차선 검출이 어려운 문제가 있다. 이에 반해 4대의 어안렌즈 카메라로 차량의 주변을 촬영한 영상은 기상 환경에 영향을 적게 받아 안정적인 차선 검출에 용이하다. 어안렌즈 카메라로 촬영한 영상은 왜곡이 심하기 때문에 왜곡 보정을 수행한 후 차량 위에서 아래로 내려다본 시점으로 투영 변환하여 하나의 영상으로 정합한다. 정합영상에서 관심영역을 설정한 후 차선 후보 영역을 검출하고, 검출된 후보 영역들로 차선을 직선으로 모델링한다. 점선 차선 구간이나 차량 흔들림에 대응하기 위해 직선으로 모델링된 차선 정보의 차선 각도와 차량으로부터 거리 정보를 칼만 필터 기반 추적 및 보정하여 안정적으로 차선 검출을 수행한다. 실험 결과 제안하는 방법은 실선구간에서 99.57%, 점선구간에서는 90.48%의 검출 정확도를 가진다.

• Journal of Sensor Science and Technology
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• v.9 no.5
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• pp.373-379
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• 2000

In this paper, an estimation system of vehicle position and orientation on magnetic lane, which is a parameter of the steering controller for automated lane following is described. To verify that the magnetic dipole model could be applied to a magnetic unit paved in roadway, the analysis of the model is compared with the data of 3-axis magnetic field measured experimentally. The sensor location could be estimated by analysis of the model based on experimental data. For the magnetic lane model merged magnetic unit, the relation of sensor location and magnetic field is acquired experimentally. The proposed estimation of vehicle position and orientation is adopted to automated lane following by computer simulation.