• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.187-192
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• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1700-1705
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• 2003

In this paper, the automatic steering system for unmanned vehicle was developed. The vision system is used for the lane detection system. This paper defines two modes for detecting lanes on a road. First is searching mode and the other is recognition mode. We use inverse perspective transform and a linear approximation filter for accurate lane detections. The PD control theory is used for the design of the controller to compare with $H_{\infty}$ control theory. The $H_{\infty}$ control theory is used for the design of the controller to reduce the disturbance. The performance of the PD controller and $H_{\infty}$ controller is compared in simulations and tests. The PD controller is easy to tune in the test site. The $H_{\infty}$ controller is robust for the disturbances in the test results.

• Journal of Auto-vehicle Safety Association
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• v.10 no.4
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• pp.33-39
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• 2018

Recently, the automobile industry has developed ADAS (Advanced Driver Assistance System) to prevent traffic accidents and reduce driver's driving burden. Among the ADAS, the LKAS (Lane Keeping Assistance System) is a support system for the convenience and safety of the driver, and the main function is to maintain the driving lane of the vehicle. LKAS is a system that uses radar sensor and camera sensor to collect information about the position of the vehicle in the lane and to support keeping the lane through control if necessary. In many countries, LKAS has already been commercialized and the convenience and safety of drivers have been improved. The international LKAS evaluation test procedure is being developed and discussed by standardization committees such as the ISO (International Organization for Standardization) and the Euro NCAP (New Car Assessment Program). In Korean, the LKAS test method is specified in the KNCAP (Korean New Car Assessment Program), but the evaluation method is not defined. Therefore, the LKAS test procedure that meets international standards and is suitable for domestic road environment is necessary. In this paper, development of LKAS test evaluation scenarios that meets international standards and considering domestic road environment, and the formula that can evaluate the result value after control as the relative distance of lane and the front wheel are suggested. And a comparative analysis was conducted to verify the validity of the suggested scenario and formula. The test evaluation was conducted using the vehicle equipped with the LKAS.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1029-1035
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• 2013

This paper proposes a real time lane detection algorithm using LRF (Laser Range Finder) for autonomous navigation of a mobile robot. There are many technologies for safety of the vehicles such as airbags, ABS, EPS etc. The real time lane detection is a fundamental requirement for an automobile system that utilizes outside information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. By the vision-based system, recognition of environment for three dimensional space becomes excellent only in good conditions for capturing images. However there are so many unexpected barriers such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement. In this paper, we introduce a three dimensional lane detection algorithm using LRF, which is very robust against the illumination. For the three dimensional lane detections, the laser reflection difference between the asphalt and lane according to the color and distance has been utilized with the extraction of feature points. Also a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been verified through the real experiments.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.54-58
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• 2013

In recent days, vehicles have become equipped with electric systems that assist and help drivers driving safe by reducing possible accidents. LDWS(Lane Departure Warning System) and LKAS(Lane Keeping Assistant System) are involved in assist systems, especially for lateral motion of vehicles. Sudden and inattentive lateral motion of vehicles due to drivers' fatigue, illness, inattention, and drowsiness are major causes of accidents in highway. LDWS and LKAS provide drivers with warnings or assisting power to reduce any possibilities of accidents. In order to prevent or minimize the possibilities of accidents, lateral motion control of vehicles has been introduced in this research. DGPS/RTK(Differential Global Positioning System/Real Time Kinematics) and GIS(Geographic Information System) have been used to obtain the current position of vehicles and decide when activate controlling lateral motion of vehicles. The presented lateral motion control has been validated with actual vehicle tests.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.107-116
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• 2014

This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and RSM (Road Surface Marking) detection. The lane marking detection provides ROIs (Region of Interest) that are highly likely to contain RSM. The RSM detection generates candidates in the regions and classifies their types. The proposed system focuses on detecting RSM without false detections and performing real time operation. In order to ensure real time operation, the gating varies for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Also, a single template matching is used to extract features for both lane marking detection and RSM detection, and it is efficiently implemented by horizontal integral image. Further, multiple step verification is performed to minimize false detections.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.609-618
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• 2006

This paper presents the lateral control of an autonomous vehicle by using a look-ahead sensing system. In look-ahead sensing by an absolute positioning system, a reference lane, constructed by straight lanes or circular lanes, was switched by a segment switching algorithm. To cope with sensor noise and modeling uncertainty, a robust LMI-based $H_{\infty}$ lateral controller was designed by the feedback of lateral offset and yaw angle error at the vehicle look-ahead. In order to verify the safety and the performance of lateral control, a scaled-down vehicle was developed and the location of the vehicle was detected by using an ultrasonic local positioning system. In the mechatronic scaled-down vehicle, the lateral model and parameters are verified and estimated by a J-turn test. For the lane change and reference lane tracking, the lateral controllers are used experimentally. The experimental results show that the $H_{\infty}$ controller is robust and has better performance compared with look-down sensing.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.719-726
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• 2000

A real-time precise positioning is possible with GPS carrier phase measurements with efficient integer ambiguity resolution techniques. It is known that more reliable and fast integer ambiguity resolution is possi-ble as the number of measurements increases. Most precise positioning systems use dual frequency measurements and the wide-lnae technique to resolve integer ambiguity. The wide-lane technique magnifies the measurement noise while it reduces the number of candidates to be examined. In this paper a new integer ambiguity resolution method using dual frequency is proposed The proposed method utilizes the relationship between the wide-lane single frequency and the narrow-lane ambiguities to resolve narrow-lane integer ambiguity after fixing the wide-lane integer ambiguity. Experiments with real data show that the proposed method gives fast and reliable results.