• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.371-377
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• 2012

Objective: The aim of this study is to investigate effect of driver's cognitive distraction on driver's physiological state and driving performance, and then to determine parameters appropriate for detecting the cognitive distraction. Background: Driver distraction is a major cause of traffic accidents and poses a serious threat to traffic safety due to ever increasing use of in-vehicle information systems and mobile phones during driving. Cognitive distraction, among four different types of distractions, prevents a driver from processing traffic information correctly and adapting to change in surround vehicle behavior in time. However, the cognitive distraction is more difficult to detect because it normally does not involve significant change in driver behavior. Method: A full-scale driving simulator was used to create virtual driving environment and situations. Participants in the experiment drove the driving simulator in three different conditions: attentive driving with no secondary task, driving and conducting secondary task of adding numbers, and driving and conducting secondary task of conversing with an experimenter. Parameters related with driver's physiological state and driving performance were measured and analyzed for their change. Results: The experiment results show that driver's cognitive distraction, induced by secondary task of addition and conversation during driving, increased driver's cognitive workload, and indeed brought change in driver's physiological state and degraded driving performance. Conclusion: The galvanic skin response, pupil size, steering reversal rate, and driver reaction time are shown to be statistically significant for detecting cognitive distraction. The appropriate combination of these parameters will be used to detect the cognitive distraction and estimate risk of traffic accidents in real-time for a driver distraction warning system.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.699-704
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• 2016

In this paper, we propose a development method for a drowsiness detection system using retinex theory and edge information for vehicle safety. Detection of a drowsy state of a driver is very important because the drowsiness of driver is often the main cause of many car accidents. After acquiring an image of the entire face, we executed the pre-process step using the retinex theory. We then applied a technique for the detection of the white pixels using edge information. Experimental results showed that the proposed method improved the accuracy of detecting drowsiness to nearly 98%, and can be used to prevent a car accident caused by the driver's drowsiness.

• JSTS:Journal of Semiconductor Technology and Science
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• v.4 no.4
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• pp.269-274
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• 2004

Current delivery system, in which the analog current produced by a unique DAC circuit is stored into a current-memory circuit and delivered in a time-divided sequence, shows variation of output current as low as 4% in a current source data-driver IC for AM-OLED driven by a current-programmed method without any fuse repairing after fabrication. This driver IC has 54 outputs and can sink constant current as low as 3 ${\mu}A$ with 6-bit analog levels. Such a low current level without variation can hardly be obtained by an ordinary MOS transistor because the current level is in the sub-threshold region and changes exponentially with threshold voltage variation. Thus we adopted a current mirror circuit composed of bipolar transistors to supply well-controlled current within a nano-ampere range.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.319-320
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• 2006

In this paper, automatic sunvisor system is introduced for driver's safety and convenience. This system has the mechanism which keeps the sun off without obstruction of driver's sight. The mechanism can make the sunvisor move forward or rotate left while remaining inside inner roof. The control system consists of a CPU, a motor driver, light sensors, and the algorithm that can control the movement of sunvisor efficiently. When the light sensors take the sun light, they give the signal to the CPU and the CPU calculates the best position of the sunvisor with the information of driver's eyes height. Then, the CPU gives the signal to motors that can move the sunvisor.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.2
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• pp.75-81
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• 2018

In this paper for developing and implementing the car driver's front lane attention enhancement developed system using the car camera. The developed system automatically alarm the car driver when front cars make the dangerous situation. We use Raspberry Pi camera module V2 as car camera module, Raspberry Pi 3 board as hardware main board of implementing embedded system and develop the application library module which can be operated on the Raspberry situation. The application library module widely consist of two part, front car recognition part and dangerous situation distinguish part. Our developed system satisfy the performance test of the target system at the software test certification laboratory of TTA(Telecommunication Technology Association). We test four items as attentive car recognition ability at day and night, system performance, response time. We get the performance of developed system based on the four goal. The car driver's front lane attention enhancement system in this paper will be widely used at the ADAS(Advanced Driving Assistance System) because of the better performance and function.

• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.588-593
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• 2017

In this paper, we propose a LiDAR driver that virtualizes multiple inexpensive LiDARs (Light Detection and Ranging) with a smaller number of scan channels on an autonomous vehicle to replace a single expensive LiDAR with a larger number of scan channels. As a result, existing SLAM (Simultaneous Localization And Mapping) algorithms can be used with no modifications developed assuming a single LiDAR. In the paper, the proposed driver was implemented on the Robot Operating System and was evaluated with an existing SLAM algorithm. The results show that the proposed driver, combined with a filter to control the density of points in a 3D map, is compatible with the existing algorithm.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.185-190
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• 1996

Navigation system is regarded as the interface border line between the Intelligent Transportation Systems (ITS) and the driver as the prospective information provider of the ATIS (Advanced Traveler Information System). Following theory, if the navigation system appropriately designed and utilized, that can maximize the transport efficiency, contribute to improvements of the environments and road safety. To accomplish these dinds of objectives of the navigation system use, human factors plays an important roles specially focused on the driver's safety, performance and system usability. Because the effectiveness of the system depends on the acceptance of the system, and the extent to which the system conforms to driver physical and cognitive limitations and capabilities. Therefore, the ergonomic design vaniables must be seriously selected and reflected in early design step for more effective and appreciate product design. As the first step of this aim, this study selected and categorized the human factors design variables of the navigation system.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.247-252
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• 2013

An intelligent light emitting diode (LED) dimming system is designed and implemented for energy-saving lighting systems. An LED light bulb is powered by an LED driver controlled by a microcontroller using pulse width modulation (PWM) signals. By changing the duty cycle of the PWM signals, the LED driver generates a driving current of up to 1,000 mA. The current consumption by the LED light bulb exhibits a very linear characteristic that indicates that the level of LED dimming can be finely tuned. Multiple sensors-lighting intensity and ultrasonic range sensors-are combined with the LED dimming system to realize an automatically controllable LED lighting system. The light intensity sensor is capable of sensing ambient light. The ultrasonic range sensor can detect objects from 0.15 to 5.6 m at a resolution of 0.0254 m. The collected information by the light intensity and ultrasonic range sensors is processed by the microcontroller that in turn automatically controls the brightness of the LED light bulb. The algorithm of the software for the LED dimming system is also described.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.425-426
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• 2021

Recently, there have been frequent incidents of talent accidents caused by youth driving without a license. Driving without a license is becoming a hotbed of curiosity and challenge for some young people, and there is a limit to managing smart keys at home to prevent this. Therefore, in this paper, using the facial recognition algorithm, the face of the driver sitting in the driver's seat is compared with the information stored in advance, and the system is designed to control the engine by determining that it is a registered driver. If the registered driver authentication is successful, the matching accuracy and Unlock message are output to the LCD connected to the Raspberry Pi.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.1025-1030
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• 2001

As the pre-stage of making 3D stabilizing systems, at this paper designed 2D stabilizing system. This is composed of two axes stabilizing platform to preserve targeted direction while vehicle is moving. The system maintains stabilization by recovering error using the rate gyro with DSP TMS320F240 as controller, vibratory rate gyro (Tokimec co. TFG -l60D) as gyro scope, SD1015B52-1·SD1004C04-l/DM1015B DM1004C as direct drive driver/motor, PI control as control algorithm. This paper got a comparably good stabilization.