• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.16-24
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• 2011

The vehicle electronic control system is being developed as the legal and social demand for ensuring driver's safety is rising. The various Driver Assistance Systems with various sensors such as radars, camera, and lasers are in practical use because of the falling price of hardware and the high performance of sensor and processer. In the preceding study of this research, the program was developed to recognize the experiment vehicle's driving lane and the cars nearby or approaching the experiment vehicle throughout the images taken by CCD camera. In addition, the 'dangerous driving analysis program' which is Vision System basis was developed to analyze the cause and consequence of dangerous driving. However, the Vision system developed in the previous studyhad poor recognition rate of lane and vehicles at the time of passing a tunnel, sunrise, or sunset. Therefore, through mounting the brightness response algorithm to the Vision System, the present study is aimed to analyze the causes of driver's dangerous driving clearly by improving the recognition rate of lane and vehicle, regardless of when and where it is.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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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.

• 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 Mechanical Science and Technology
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• v.16 no.3
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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.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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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.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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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.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.149-161
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• 2009

Electronic control systems of vehicle are rapidly developed to keep balance of a driver`s safety and the legal, social needs. The driver assistance systems are putted into practical use according to the cost drop in hardware and highly efficient sensor, etc. This study has developed a lane and vehicle detection program using CCD camera. The Risky Driving Analysis Program based on vision systems is developed by combining a risky driving detection algorithm formed in previous study with lane and vehicle detection program suggested in this study. Risky driving detection programs developed in this study with information coming from the vehicle moving data and lane data are useful in efficiently analyzing the cause and effect of risky driving behavior.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.622-626
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• 2005

This paper presents an active vision system for ITS(intelligent transportation system : ITS). We have described a novel method to provide high quality imaging signals to a system that will perform passenger detection and counting in the roadway. The method calls for two co-registered near-infrared cameras with spectral sensitivity above (upper-band) and below (lower-band) the quality of the signal remains. We propose a novel system based on fusion of near-infrared imaging signals and we demonstrate its adequacy with theoretical and experimental arguments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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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.