• 제목/요약/키워드: Intelligent vehicle vision system

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Vision 시스템의 차량 인식률 향상에 관한 연구 (A Study on the Improvement of Vehicle Recognition Rate of Vision System)

  • 오주택;이상용;이상민;김영삼
    • 한국ITS학회 논문지
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    • 제10권3호
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    • pp.16-24
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    • 2011
  • 차량의 전자제어 시스템은 운전자의 안전을 확보하려는 법률적, 사회적 요구에 발맞추어 빠르게 발달하고 있으며, 하드웨어의 가격하락과 센서 및 프로세서의 고성능화에 따라 레이더, 카메라, 레이저와 같은 다양한 센서를 적용한 다양한 운전자 지원 시스템 (Driver Assistance System)이 실용화되고 있다. 이에 본 연구의 선행연구에서는 CCD 카메라로부터 취득되는 영상을 이용하여 실험차량의 주행 차선 및 주변에 위치 하거나 접근하는 차량을 인식하여 운전자의 위험운전에 대한 원인 및 결과를 분석 할 수 있는 Vision 시스템 기반 위험운전 분석 프로그램을 개발하였다. 그러나 선행 연구에서 개발된 Vision 시스템은 터널, 일출, 일몰과 같이 태양광이 충분치 않은 곳에서는 차선 및 차량의 인식율이 매우 떨어지는 것으로 나타났다. 이에 본 연구에서는 밝기 대응 알고리즘을 개발하여 Vision 시스템에 탑재함으로서 언제, 어느 곳에서라도 차선 및 차량에 대한 인식율을 향상시켜 운전자의 위험운전에 대한 원인을 명확하게 분석하고자 한다.

자율주행차량을 위한 비젼 기반의 횡방향 제어 시스템 개발 (Development of Vision-based Lateral Control System for an Autonomous Navigation Vehicle)

  • 노광현
    • 한국자동차공학회논문집
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    • 제13권4호
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    • pp.19-25
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    • 2005
  • This paper presents a lateral control system for the autonomous navigation vehicle that was developed and tested by Robotics Centre of Ecole des Mines do Paris in France. A robust lane detection algorithm was developed for detecting different types of lane marker in the images taken by a CCD camera mounted on the vehicle. $^{RT}Maps$ that is a software framework far developing vision and data fusion applications, especially in a car was used for implementing lane detection and lateral control. The lateral control has been tested on the urban road in Paris and the demonstration has been shown to the public during IEEE Intelligent Vehicle Symposium 2002. Over 100 people experienced the automatic lateral control. The demo vehicle could run at a speed of 130km1h in the straight road and 50km/h in high curvature road stably.

Development of Vision Based Steering System for Unmanned Vehicle Using Robust Control

  • Jeong, Seung-Gweon;Lee, Chun-Han;Park, Gun-Hong;Shin, Taek-Young;Kim, Ji-Han;Lee, Man-Hyung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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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.

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Lateral Control of Autonomous Vehicle by Yaw Rate Feedback

  • Yoo, Wan-Suk;Park, Ju-Yong;Hong, Seong-Jae;Park, Kyoung-Taik;Lee, Man-Hyung
    • Journal of Mechanical Science and Technology
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    • 제16권3호
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    • pp.338-343
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    • 2002
  • In the autonomous vehicle, the reference lane is continually detected by machine vision system. And then the vehicle is steered to follow the reference yaw rates which are generated by the deviations of lateral distance and the yaw angle between a vehicle and the reference lane. To cope with the steering delay and the side-slip of vehicle, PI controller is introduced by yaw rate feedback and tuned from the simulation where the vehicle is modeled as 2 DOF and 79 DOF and verified by the results of an actual vehicle test. The lateral control algorithm by yaw rate feedback has good performances of lane tracking and passenger comfort.

Implementation of a Stereo Vision Using Saliency Map Method

  • Choi, Hyeung-Sik;Kim, Hwan-Sung;Shin, Hee-Young;Lee, Min-Ho
    • Journal of Advanced Marine Engineering and Technology
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    • 제36권5호
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    • pp.674-682
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    • 2012
  • A new intelligent stereo vision sensor system was studied for the motion and depth control of unmanned vehicles. A new bottom-up saliency map model for the human-like active stereo vision system based on biological visual process was developed to select a target object. If the left and right cameras successfully find the same target object, the implemented active vision system with two cameras focuses on a landmark and can detect the depth and the direction information. By using this information, the unmanned vehicle can approach to the target autonomously. A number of tests for the proposed bottom-up saliency map were performed, and their results were presented.

지능형 무인자동차 제어시스템 개발 (Development of an Intelligent Unmanned Vehicle Control System)

  • 김윤구;이기동
    • 대한임베디드공학회논문지
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    • 제3권3호
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    • pp.126-135
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    • 2008
  • The development of an unmanned vehicle basically requires the robust and reliable performance of major functions which include global localization, lane detection, obstacle avoidance, path planning, etc. The implementation of major functional subsystems are possible by integrating and fusing data acquired from various sensory systems such as GPS, vision, ultrasonic sensor, encoder, and electric compass. This paper focuses on implementing the functional subsystems, which are designed and developed by a graphical programming tool, NI LabVIEW, and also verifying the autonomous navigation and remote control of the unmanned vehicle.

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자동차 추돌경보 시스템 개발을 위한 컴퓨터 비젼과 레이저 레이다의 응용 (An Application of Computer Vision and Laser Radar to a Collision Warning System)

  • 이준웅
    • 한국자동차공학회논문집
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    • 제7권5호
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    • pp.258-267
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    • 1999
  • An intelligent safety vehicle(ISV) should have an ability to predict the possibility of an accident and help a driver avoid the accident in advance. The basic function of the ISV is to alert the driver by warning when the collision is to occur. For this purpose, the ISV has to function efficiently in sensing the environmental context. While image processing provides lane information, laser radar senses road obstacles including vehicles. By applying a simple clustering algorithm to radar signals, it is possible to obtain the vehicle information. Consequently, we can identify the existence of the vehicle of interest on my lane. The reliability of the sensing algorithm is evaluated by running on the highway with a test vehicle.

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Vision 시스템을 이용한 위험운전 원인 분석 프로그램 개발에 관한 연구 (Development of a Cause Analysis Program to Risky Driving with Vision System)

  • 오주택;이상용
    • 한국ITS학회 논문지
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    • 제8권6호
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    • pp.149-161
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    • 2009
  • 차량의 전자제어 시스템은 운전자의 안전을 확보하려는 법률적, 사회적 요구에 발맞추어 빠르게 발달하고 있으며, 하드웨어의 가격하락과 센서 및 프로세서의 고성능화에 따라 레이더, 카메라, 레이저와 같은 다양한 센서를 적용한 다양한 운전자 지원 시스템 (Driver Assistance System)이 실용화되고 있다. 이에 본 연구에서는 CCD 카메라로부터 취득되는 영상을 이용하여 실험차량의 주행 차선 및 주변에 위치하거나 접근하는 차량을 인식할 수 있는 프로그램을 개발하였으며, 선행 연구에서 개발된 위험운전 판단 알고리즘과 통합하여 위험운전에 대한 원인 및 결과를 분석 할 수 있는 Vision 시스템 기반 위험운전 분석 프로그램을 개발하였다. 본 연구에서 개발한 위험운전 분석 프로그램은 위험운전판단 알고리즘의 판단변수인 차량 거동 데이터와 차선 및 차량인식 프로그램에서 획득된 정보와 융합하여 위험운전 행위의 원인 및 결과를 효과적으로 분석할 수 있을 것으로 판단된다.

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차량 승객 자동탐지를 위한 비젼시스템 (An Vision System for Automatic Detection of Vehicle Passenger)

  • 이영식;배철수
    • 한국정보통신학회논문지
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    • 제9권3호
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    • pp.622-626
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    • 2005
  • 본 논문은 지능형 교통시스템(intelligent transportation system)에 적용될 수 있는 방안으로써, 안정된 영상신호를 제공하여 자동으로 차량안의 승객을 탐지하는 시스템을 제안한다. 제안된 시스템은 높은 대역(upper-band)과 낮은 대역(lowe.-band)의 스펙트럼 강도를 조합하는 근적외선(Near-Infrared) 카메라를 이용하여 안정된 영상신호를 획득할 수 있었으며, 실험결과를 통해 제안된 방법의 효율성을 입증할 수 있었다.

Intelligent Rain Sensing and Fuzzy Wiper Control Algorithm for Vision-based Smart Windshield Wiper System

  • Lee, Kyung-Chang;Kim, Man-Ho;Lee, Suk
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1694-1699
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    • 2003
  • A windshield wiper system plays a key part in assuring the driver's safety during the rainfall. However, because the quantity of rain and snow vary irregularly according to time and the velocity of the automobile, a driver changes wiper speed and interval from time to time to secure enough visual field in the traditional windshield wiper system. Because a manual operation of windshield wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming a direct cause of traffic accidents. Therefore, this paper presents the basic architecture of a vision-based smart windshield wiper system and a rain sensing algorithm that regulates speed and interval of the windshield wiper automatically according to the quantity of rain or snow. This paper also introduces a fuzzy wiper control algorithm based on human's expertise, and evaluates the performance of the suggested algorithm in an experimental simulator.

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