• 제목/요약/키워드: Lane keeping

검색결과 57건 처리시간 0.028초

EVALUATION OF FOUR-WHEEL-STEERING SYSTEM FROM THE VIEWPOINT OF LANE-KEEPING CONTROL

  • Raksincharoensak, P.;Mouri, H.I;Nagai, M.I
    • International Journal of Automotive Technology
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    • 제5권2호
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    • pp.69-76
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    • 2004
  • 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.

차선유지지원장치 작동 메커니즘 평가에 관한 연구 (A Study for Driving Mechanism Evaluation of the Lane Keeping Assistance System)

  • 정승환;김종민;권성진;이봉현
    • 자동차안전학회지
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    • 제5권1호
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    • pp.69-74
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    • 2013
  • LKAS(Lane Keeping Assistance System) main function is to support the driver in keeping the vehicle within the current lane. Therefore, this system is able to reduce the driver workload with assisting the driver during driving. In this paper, we presented on study for test procedures and evaluation methods of the LKAS. The vehicle test conducted on straight road, left curve, right curve and four different types of lane under various vehicle speeds. This study proposed the LKAS system test procedures and methods that we are able to identify LKAS driving mechanism and performance.

도로주행환경을 고려한 차선유지지원장치 성능 평가 (Performance Evaluation of Lane Keeping Assistance System)

  • 우현구;용부중;김경진
    • 자동차안전학회지
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    • 제6권2호
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    • pp.29-35
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    • 2014
  • Lane Keeping Assistance System(LKAS) is a kind of Advanced Driver Assistance Systems(ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in international committees such as ISO(the International Organization for Standardization). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP(Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System(LDWS). Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

비전 및 IMU 센서의 정보융합을 이용한 자율주행 자동차의 횡방향 제어시스템 개발 및 실차 실험 (Development of a Lateral Control System for Autonomous Vehicles Using Data Fusion of Vision and IMU Sensors with Field Tests)

  • 박은성;유창호;최재원
    • 제어로봇시스템학회논문지
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    • 제21권3호
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    • pp.179-186
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    • 2015
  • In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

A Study On a Lane Keeping Control in a Curved Road and Lane Changing Method to Avoid Collision of a Vehicle

  • Lee, seungchul;Kwangsuck Boo;Jeonghoon Song
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.107.2-107
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    • 2002
  • The objective of this study is to propose a lane changing and keeping method on a curved road for an automatic guidance of a vehicle. It is well known that the speed control of a vehicle in a curved road is essential in terms of vehicle stability and passenger safety because centrifugal force makes a vehicle to be on out of lane. And it is also natural to avoid the collision with other cars or obstructions with keeping the stability and drivability. 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 in which not only the state variables, but also the corresponding uncer...

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Implementation of Low-cost Autonomous Car for Lane Recognition and Keeping based on Deep Neural Network model

  • Song, Mi-Hwa
    • International Journal of Internet, Broadcasting and Communication
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    • 제13권1호
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    • pp.210-218
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    • 2021
  • CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping.

승용자동차 차로유지지원장치의 주행 성능 평가 (Road Test Scenario and Performance Assessments of Lane Keeping Assistance System for Passenger Vehicles)

  • 우현구;용부중;김경진;임재환
    • 한국자동차공학회논문집
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    • 제24권2호
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    • pp.255-263
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    • 2016
  • Lane Keeping Assistance System (LKAS) is a kind of Advanced Driver Assistance Systems (ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in the international committees such as ISO (the International Organization for Standardization) and UNECE (United Nations Economic Commission for Europe). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP (Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed and proposed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System (LDWS). And then, to evaluate the validity of the proposed test procedures, a series of experiments were conducted using commercially available two vehicles equipped with LKAS. Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

횡풍하의 차량 외란 추정을 이용한 차선 유지 조향 보조 제어기 설계 (Design of Lane Keeping Steering Assist Controller Using Vehicle Lateral Disturbance Estimation under Cross Wind)

  • 임형호;좌은혁;이경수
    • 자동차안전학회지
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    • 제12권3호
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    • pp.13-19
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    • 2020
  • This paper presents steering controller for unintended lane departure avoidance under crosswind using vehicle lateral disturbance estimation. Vehicles exposed to crosswind are more likely to deviate from lane, which can lead to accidents. To prevent this, a lateral disturbance estimator and steering controller for compensating disturbance have been proposed. The disturbance affecting lateral motion of the vehicle is estimated using Kalman filter, which is on the basis of the 2-DOF bicycle model and Electric Power Steering (EPS) module. A sliding mode controller is designed to avoid unintended the lane departure using the estimated disturbance. The controller is based on the 2-DOF bicycle model and the vision-based error dynamic model. A torque controller is used to provide appropriate assist torque to driver. The performance of proposed estimator and controller is evaluated via computer simulation using Matlab/Simulink.

차선이탈경보를 위한 차량용 GPS/DR 통합항법시스템 기반의 모니터링 프로그램 개발 (Development of Monitoring Program Based an Automotive GPS/DR Integrated Navigation System for Lane Departure Warning)

  • 박순철;천세범;김정원;허문범
    • 한국항행학회논문지
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    • 제14권6호
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    • pp.791-799
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    • 2010
  • 본 논문에서는 높은 정확도를 요구하는 육상교통분야에 활용할 수 있는 통합항법 알고리즘을 설계하고 차선이탈경보를 위한 모니터링 프로그램을 개발하였다. 차선이탈경보를 위해서는 차선 구분이 가능한 정확도 높은 위치정보가 필요하므로 GPS와 DR기반의 위치정보를 융합한 위치결정 알고리즘을 설계하였다. 설계한 통합항법 알고리즘의 검증을 위해서 실제 차량을 이용하여 데이터를 수집하고, 후처리한 결과를 모니터링 프로그램으로 확인하였다. 모니터링 프로그램은 주행동영상과 항공사진을 통해서 차로유지 및 차선이탈 유무를 확인할 수 있도록 제작하였다.

비젼 기반 자율주행을 위한 다중비율 예측기 설계와 모델예측 기반 능동조향 제어 (MPC-based Active Steering Control using Multi-rate Kalman Filter for Autonomous Vehicle Systems with Vision)

  • 김보아;이영옥;이승희;정정주
    • 전기학회논문지
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    • 제61권5호
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    • pp.735-743
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    • 2012
  • In this paper, we present model predictive control (MPC) applied to lane keeping system (LKS) based on a vision module. Due to a slow sampling rate of the vision system, the conventional LKS using single rate control may result in uncomfortable steering control rate in a high vehicle speed. By applying MPC using multi-rate Kalman filter to active steering control, the proposed MPC-based active steering control system prevents undesirable saturated steering control command. The effectiveness of the MPC is validated by simulations for the LKS equipped with a camera module having a slow sampling rate on the curved lane with the minimum radius of 250[m] at a vehicle speed of 30[m/s].