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Design of Fuzzy Logic Based Automated Lane Keeping System
Sang-Jin Ko,Ju-Jang Lee 한국자동차공학회 2007 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-
Lane departures are the number one cause of fatal accident. A lane keeping system automatically controls the steering to keep the vehicle in its land and also to follow the lane as it curves around, so a lane keeping system prevents fatal car accident. This paper proposes automated lane keeping system based on fuzzy logic. To design an automated lane keeping system, lateral error dynamics of a vehicle is derived. Fuzzy controllers are expert systems based on if - then rules. If the fuzzy rules are set properly, the fuzzy controller can control the objective system satisfactorily. Lateral distance error, derivative of lateral distance error, rotational error and derivative of rotational error get into the automated lane keeping system as inputs. And the output of the proposed lane keeping system is steering angle, which is a control input of the vehicle. The proposed lane keeping system is evaluated by SIMULINK in MATLAB. The simulation results show that the proposed lane keeping system works satisfactorily for keeping the vehicle in its land and following the lane.
자동차 전용 도로 환경에서의 차선 검출과 Pure Pursuit 알고리즘을 이용한 차선 유지 시스템
허승회(Seunghoi Heo),백선우(Sunwoo Baek),김정하(Jungha Kim) 한국자동차공학회 2018 한국자동차공학회 부문종합 학술대회 Vol.2018 No.6
This study demonstrates how to detect lanes on automobile road and to track (keep the lanes) the lane using detected lane information. First, I converted the input image of the camera into a gray image. Then, by using the Inverse Perspective Mapping, the perspective of the image was removed and the information of the lane with the constant thickness was strengthened by using the LDA (Line Difference Accumulation) method. Next, the position of the left and right lanes was confirmed by hough transformation clustering to identify the position of the left and right lane. In addition, to detect lane points, the lane points classified after template matching were approximated using the RANSAC(Random Sample Consensus) algorithm. Based on the above procedure, coordinate transformation was performed to find the position of the target point according to the speed of the vehicle and to use it for tracking the path. Finally, the final steering angle was obtained by applying the Pursuit method using the converted target point. The lane keeping test was performed based on the obtained steering angle, and the steering angle obtained from the vehicle OBD II and the difference (lateral distance error) between the center of the lane and the center of the vehicle was measured and presented.
Lateral Control for Autonomous Lane Keeping System on Highways
Chang Mook Kang,Jeehyung Lee,Sung Gu Yi,Soo Jung Jeon,Young Seop Son,Wonhee Kim,Seung-Hi Lee,Chung Choo Chung 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
In this paper, we propose a lateral control scheme for autonomous lane keeping system on highways. Three main techniques are proposed, to improve the lane-keeping performance and and to reduce the ripple in the yaw rate on highways. First, we propose a virtual lane prediction method to cope with the momentary failure of lane detection. Second, we innovate an approach to steering wheel angle control based on torque overlay for the EPS of the LKS. Finally, the multi-rate lane-keeping control scheme is proposed to improve the lane-keeping performance and to reduce the ripple in the yaw rate. The performance of the proposed method was evaluated via experiments.
SILS를 이용한 Lane Keeping Control 시스템의 성능평가
백승환(Seunghwan Baek),부광석(Kwangsuck Boo),김흥섭(Heungseob Kim),정재업(Jaeop Jung) 한국자동차공학회 2013 한국자동차공학회 부문종합 학술대회 Vol.2013 No.5
This study propose an Perception-Action Network (PAN) to estimate the vehicle pose parameters and control the vehicle motion for keeping the vehicle within given lane. 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. The objective of the lane keeping control is to reduce a predicted tracking error of the vehicle, while the vehicle is traveling along the given lane. In this study, we calculated a required steering angle at the auction module of PAN. A series of experiments was conducted to evaluate the control performance, in which commercial software was utilized to quit unwanted safety problem.
김근우,김윤겸,홍준기,우수호,최재환,이순걸 제어·로봇·시스템학회 2023 제어·로봇·시스템학회 논문지 Vol.29 No.1
A lane keeping assistant (LKA) is a control system that maintains marked lanes for driving safety. This paper shows an LKA system based on a time to lane crossing (TLC). A TLC can be calculated by dividing the distance to the lane crossing by the vehicle velocity and represents the time in which a vehicle will cross the lane. Instead of using a complicated TLC calculation for both straight and curved roads, a lightweight TLC (LTLC) method as a simplified one is proposed to reduce the computing time. By approximating the curved road to two straight roads, based on look-ahead points, the TLC computation of time can be reduced. The LKA system pre-calculates the vehicle's LTLC and turns the steering wheel in the opposite direction when the remaining time is running out. To verify the proposed algorithm, an IPG's CarMaker simulation with Matlab/Simulink was executed. The simulation results show it was possible to show stable driving results. Moreover, the calculation time was compared with that of the existing TLC.
REDUCTION OF PREVIEW DISTANCE IN LANE-KEEPING CONTROL
Keisuke Kazama,Kohei Nishizaki,Yuta Shirayama,Hiroyuki Furusho,Hiroshi Mouri 한국자동차공학회 2017 International journal of automotive technology Vol.18 No.4
Lane marker detection is indispensable for a lane-keeping-control algorithm. However, it is impossible to detect lane markers when the curvature of the lane the vehicle is travelling on is large or when there is another car in front of the vehicle with short distance. For lane marker detection, it is desirable to set a preview point close to the vehicle. Therefore, by analyzing the block diagram of driver-vehicle system, we propose a method to reduce preview distance without lane tracking performance deterioration by increasing preview points from the conventional one point to two points. Furthermore, it is revealed that driving along a corner with constant curvature without steady-state deviation and arbitrary design of tracking dynamic characteristics become possible by increasing preview points.
박재웅(Jae-Woong Park),김용은(Yong-Eun Kim),김정원(Jeong Won Kim),노형주(Hyeong-Ju Noh) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
LKAS(Lane Keeping Assist system) is designed to help keep vehicle centered in a lane when over a certain speed. However, The LKAS system may work improperly under bad environmental conditions, such as lane is dirty or there is matter on lane. In the specific case, a recognition error can occur or the lane can be unrecognized even if the LKAS has been trained to recognize the lane in various scenario. Therefore, countermeasures need to be prepared by obtaining the front images in the specific case. In this study, we suggests data acquisition system that confirm LKAS operation state, check speed of vehicle from dashboard, collect a photo and video at the time when LKAS turns from ON to OFF, and record GPS in specific position. The system consists of IMC-link which real-time vehicle equipment, GPS, and we made image processing device to acquire vehicle information from dashboard. We verified the system operation by consisting monitoring screen which can be seen instant images and stored GPS data, when the LKAS fails to recognize lane through actual vehicle driving scenario.
정기화(Ki hwa Jung),김순태(Soon Tae Kim) 한국자동차공학회 2011 한국자동차공학회 학술대회 및 전시회 Vol.2011 No.11
LKAS(Lane Keeping Assistant System) is an assistance system that helps maintain the lane through steering wheel operation during drowsy or careless driving or deviating from the lane are expected. Lane-keeping performance characteristics are an important factor in the behavior of the vehicle. In this paper, due to changes in tire pressure and vehicle behavior characteristics were studied. By applying the test results reflected in the controller design by implementing a more robust control results were derived.
EVALUATION OF FOUR-WHEEL-STEERING SYSTEM FROM THE VIEWPOINT OF LANE-KEEPING CONTROL
Raksincharoensak, P.,Mouri, H.I,Nagai, M.I The Korean Society of Automotive Engineers 2004 International journal of automotive technology Vol.5 No.2
This paper evaluates the effectiveness of four-wheel-steering system from the viewpoint of lane-keeping control theory. In this paper, the lane-keeping control system is designed on the basis of the four-wheel-steering automobiles whose desired steering response is realized with the application of model matching control. Two types of desired steering responses are presented in this paper. One is zero-sideslip response, the other one is steering response which realizes zero-phase-delay of lateral acceleration. Using simplified linear two degree-of-freedom bicycle model, simulation study and theoretical analysis are conducted to evaluate the lane-keeping control performance of active four-wheel-steering automobiles which have different desired steering responses. Finally, the evaluation is conducted on straight and curved roadway tracking maneuvers.
고속 자율 주행 차선유지시스템을 위한 DNN 기반 레이더를 이용한 차선 추정
최주영(Joo Young Choi),김진성(Jin Sung Kim),정정주(Chung Choo Chung) 한국자동차공학회 2020 한국자동차공학회 부문종합 학술대회 Vol.2020 No.7
In this paper, we propose a novel Deep Neural Network(DNN)-based lane estimation method with radar for lanekeeping system(LKS) without vision sensors. The vision sensor is widely utilized for detecting the road lane. However, it is well known that the vision sensor has weaknesses about environmental effects such as weather, contaminated lane, and so on. Thus, we exploit the radar sensor, which is robust against environmental effects, to estimate the road lane model for LKS. Scaled Conjugate Gradient(SCG) method is used for optimization of the neural network. We had a comparative study between the proposed system and the camera system which is conventionally used for LKS. The proposed system is expected to improve the performance of LKS by sensor fusion.