• 한국자동차공학회논문집
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• 제17권3호
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• pp.54-61
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• 2009

Lane keeping assistant system (LKAS) could save thousands of lives each year by maintaining lane position and is regarded as a promising active safety system. The LKAS is expected to reduce the driver workload and to assist the driver during driving. This paper proposes a model based predictive controller for the LKAS which requires cooperative driving between the driver and the assistance system. A Hardware-In-the-Loop-Simulator (HILS) is constructed for its evaluation and includes Carsim, Matlab Simulink and a lane detection algorithm. The single camera is mounted with the HILS to acquire the monitor images and to detect the lane markers. The simulation is conducted to validate the LKAS control performance in various road scenario.

• 자동차안전학회지
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• 제10권4호
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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 information and communication convergence engineering
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• 제15권3호
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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.

• 한국통신학회논문지
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• 제41권10호
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• pp.1247-1255
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• 2016

소형드론의 상용화를 위해서는 안전성과 자율운행기능의 확보가 필수적이다. 최근 드론제작이 상당히 용이해졌으나, 여전히 안정적인 드론의 제작은 쉽지 않다. 따라서 자체드론제작 필요성은 영상이나 자율이동 등 상위 알고리즘의 연구에 큰 장애요소로 존재한다. 본 연구에서는 상용드론과 Raspberry PI, 및 오픈소스를 활용하여, 쿼드로터 드론의 자율운행기술 개발 중 영상기반 자율운행을 설계해볼 수 있는 지상원격제어시스템(GCS)을 설계하고 구현하였다. 설계한 시스템은 모듈화된 구성으로 통신, UI 및 영상처리 모듈로 구성하였고, 특히 주행선유지 알고리즘을 구현하여 기능 및 성능 실험을 하였다. 설계한 주행선유지 알고리즘은 Hough 변환에 의하여 검출된 차선을 소실점 검출과 자제적인 라인트래킹 알고리즘을 개발하여 사용하여 인식오류를 줄였으며, 주행선과 드론의 진행방향을 계산하고 방향 (전진, 정지, 좌우회전)제어하였다. 구현된 시스템은 현재 100m육상트랙의 직선과 완만한 곡선을 2-3 m/s로 주행할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.257-257
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• 2000

The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative vehicle control. A predictive control method is proposed to control the steering wheel of the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in forward and backward direction in such a way to satisfy the given constraint condition, maintain consistency, reduce the uncertainties, and guarantee robustness. A series of experiments was conducted to evaluate the control performance, in which a car Like robot was utilized to quit unwanted safety problem. As the results, the robot was keeping very well a given lane with arbitrary shape at moderate speed.

• 한국자동차공학회논문집
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• 제17권1호
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• pp.50-57
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• 2009

Lane Keeping Assistant Systems (LKAS) require the cooperative operation between drivers and active steering angle/torque controllers. An LKAS is proposed in this study such that the desired reference path generation (DRPG) system generates the desired path to minimize the trajectory overshoot. Based on the reference path from the DRPG system, an optimal controller is designed to minimize the cost function. A HIL (Hardware In the Loop) simulator is constructed to evaluate the proposed LKAS system. The single camera is mounted on the simulator and acquires the monitor images to detect lane markers. The performance of the proposed system is evaluated by HIL system using the Carsim and the Matlab Simulink.

• 제어로봇시스템학회논문지
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• 제4권6호
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• pp.759-764
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• 1998

We propose a novel algorithm capable of recognizing the road lane by image processing. Considering the fact that the direction and location of road lane are maintained similarly in successive images we formulate a function to represent the property. However, as noises play the role of making a lot of similar patterns appear and disappear in the road image, keeping of robustness in the lane detection has been known a difficult work. To overcome this problem, we introduce the following three ideas: 1) design of a function based on an edge direction and magnitude, 2) construction of a recursive filter to estimate the function recursively for successive images, 3) principal axis-based line fitting. These concepts enhance the adaptability to cope with the random environment of traffic scene and eventually lead to the reliable detection of a road lane.

• 한국인터넷방송통신학회논문지
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• 제13권5호
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• pp.1-8
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• 2013

본 논문에서는, 차량 섀시 제어시스템 중 ACC(Adaptive Cruise Control)와 LKS(Lane Keeping System)를 통합하여 차량용 OS인 OSEK OS 기반으로 구현하고 실험을 통하여 그 성능을 분석한다. 최근 자동차의 안전성을 향상시키기 위해 능동 안전 및 운전자 지원 시스템이 논의 되고 있다. 그 중 차량의 종방향에 대한 가감속 제어를 수행하는 ACC와 차량이 차선을 유지할 수 있도록 보조해주는 LKS를 통합하여 차량 내 제어시스템을 구현한다. 구현한 제어시스템은 차량용 소프트웨어의 재사용성과 안전성 및 응용 소프트웨어의 하드웨어 의존성 제거 등을 목표로 표준 제안된 OSEK/VDX를 적용한다. OSEK/VDX에서 지원하는 OSEK OS를 기반으로 재설계한 제어시스템은 실시간 태스크 관리와 인터럽트 처리 및 공유자원 관리가 가능하다. EILS(ECU-In-the-Loop Simulation) 수행 결과에 의해 OSEK OS 기반의 ACC/LKS 통합제어기와 기존 일체형 펌웨어로 구현한 ACC/LKS 통합제어기가 대등함을 입증한다.

• 드라이브 ㆍ 컨트롤
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• 제17권1호
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• pp.13-20
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• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• 한국자동차공학회논문집
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• 제7권6호
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• pp.222-230
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• 1999

A fixed type driving simulator is constructed with a car body, beam projector, operation software , driving scenario, and audio equipments. With the simulator, the cognitive effects of fatigue due to two hour continuous driving of a straight road is investigated . The effects of alcohol on driving performance is also studied. The braking operation and lane keeping performance due to fatigue and alcohol are investigated. Changes of vehicle motion due to these effects are verified by computer simulation.