• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.711-720
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• 2012

In this paper, we introduce the implementation of driver fatigue monitering system and its result. Input video device is selected commercially available web-cam camera. Haar transform is used to face detection and adopted illumination normalization is used for arbitrary illumination conditions. Facial image through illumination normalization is extracted using Haar face features easily. Eye candidate area through illumination normalization can be reduced by anthropometric measurement and eye detection is performed by PCA and Circle Mask mixture model. This methods achieve robust eye detection on arbitrary illumination changing conditions. Drowsiness state is determined by the level on illumination normalize eye images by a simple calculation. Our system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. Our algorithm is implemented with low computation complexity and high recognition rate. We achieve 97% of correct detection rate through in-car environment experiments.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1994.05a
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• pp.64-77
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• 1994

현재 건설중인 3톤/일 규모의 석탄가스화기 운전제어를 위한 콘트롤시스템은 각종 하드웨어와 소프트웨어로 구성된다. 하드웨어는 운전자가 접하게되는 컴퓨터 화면(Operator Console), 운전 제어용 판넬(Hardwired Console), 본 시스템의 핵심인 콘트롤러(PLC; Programmable Logic Controller), 폭발성가스와 분진이 있는 환경하에서의 안전운전을 위한 본질안전 장벽(Intrinsic Safety Barrier) 및 운전정보 수집과 운전 제어를 위한 각종 전/계장품(Field Instrument) 등으로 구성된다. 본 시스템에 포함되는 소프트웨어에는 운전자와 콘트롤러간의 통신을 위한 운전제어화면(GUI;Graphical User Interface), 전체적인 제어를 위한 콘트롤로직(Control Logic)등이있다. 한편 각종 펌프 및 보일러 등 보조설비로의 전기공급을 위한 MCC(Motor Control Center)도 하나의 구성원이 된다. 본 논문은 석탄가스화 반응기의 운전에 관한 전반적인 검토와 콘트롤시스템을 구성하는 각 요소와 각각의 특징 및 그 개발 현황에 대한 검토를 그 내용으로 한다. 본 연구과제를 통해 제작, 설치될 석탄가스화기는 차세대 발전 시스템으로 주목을 받고있는 석탄가스화 복합발전시스템의 핵심부분으로, 본 반응장치의 제어에 관한 경험은 상용 규모의 석탄가스화 반응기에도 유사하게 적용될 것으로 기대된다.

• Journal of Auto-vehicle Safety Association
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• v.12 no.3
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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.

• Journal of the Korean Society for Railway
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• v.16 no.4
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• pp.241-245
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• 2013

In the case of the existing train control system, the driver monitors the condition of the vehicle through a composite controller device that displays various information on a screen in the vehicle. However, when problems arise such as car trouble, it is difficult for the drivers to take action immediately. In addition, maintenance personnel have to manually save data one by one after storing the vehicle to analyze control information of the main devices such as the brake controller and auxiliary power. To improve these points, a system that sends and receives all information in real time should be established by installing a sensor communication network and a surveillance system. This study attempts to improve the safety and maintenance of rail vehicles by suggesting a standardized method for train control and surveillance system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.157-163
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• 2020

Recently, fine dust has been known to cause cardiovascular diseases here, raising interest in ways to reduce emissions by efficiently using fuel from cars that cause air pollution. Accordingly, a driving assistance system was developed to save fuel by eco-driving and improve the driver's bad driving habits. The system was developed using raspberry pi, arduino and Android. Using RPM, speed, fuel injection information obtained from OBD-II, and gyro-sensor values, Fuel-Cut is induced to create an optimal inertial driving environment. It also provides various information system such as weather, driving environment, and preventing drowsy driving through GUI and voice recognition functions. It is possible to check driving records and vehicle fault information using Android application and has low overhead for message transmission using MQTT protocol optimized for IoT environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.57-64
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• 2020

The leading technologies of the ADAS (Advanced Driver Assist System) are ACC (Advanced Cruise Control), LKAS (Lane Keeping Assist System), and AEB (Autonomous Emergency Braking). LKAS is a system that uses cameras and infrared sensors to control steering and return to its running lane in the event of unintentional deviations. The actual test is performed for a safety evaluation and verification of the system. On the other hand, research on the system evaluation method is insufficient when an additional steering angle is applied. In this study, a model using Prescan was developed and simulated for the scenarios proposed in the preceding study. Comparative analyses of the simulation and the actual test were performed. As a result, the modeling validity was verified. A difference between the front wheels and the lane occurred due to the return velocity. The results revealed a maximum error of 0.56 m. The error occurred because the lateral velocity of the car was relatively small. On the other hand, the distance from wheels to the lanes displayed a tendency of approximately 0.5 m. This can be verified reliably.

• Journal of IKEEE
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• v.23 no.3
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• pp.844-851
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• 2019

As wearable technology is becoming more common and a part of our lives, there have been many efforts to offer various smart services with wearable devices, such as motion recognition, safety of driving, and so on. In this paper, we present a method that exploits the 9-axis inertial sensors embedded in a smartwatch to identify whether the user is a vehicle driver or not and to estimate the steering wheel turning direction in the vehicle. The system consists of three components: (i) position recognition, (ii) driver recognition, and (iii) steering-wheel turning detection components. We have developed a prototype system for detecting user's motion with Arduino boards and IMU sensors. Our experiments show high accuracy in recognizing the driver and in estimating the wheel rotation angle. The average experimental error was $11.77^{\circ}$ which is small enough to perceiver the turning direction of steering-wheel.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1624-1633
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• 2009

Brake system in railway train operates to reduce the speed of the train or to stop the train via changing the kinematic energy into heat energy for emission and so brake system makes an important rule to transport passenger and cargo for safety operation. Recently operators have a matter of grave concern for the verification of performance in brake system. To verify the exact performance of brake system, most of brake test has been carried out on real operating track condition. Therefore we will determine the braked weight of indirect brake system applied in Iran DMU(Diesel Multiple Unit) in accordance with mc leaflet 544-1, which is to enable Iran DMU to achieve the required braking distances in defined situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.962-970
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• 2021

The cause of the majority of vehicle accidents is a safety issue due to the driver's inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for safety. The algorithm computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.65-69
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• 1998

고속 주행중인 자동차 환경에서 운전자의 안전 및 편의성을 위하여, 음성인식 기술을 이용한 각종 차량 편의장치를 제어하는 것으로, 운전자와 자동차와의 Man Machine Interface 구조로 구성되었다. 이 시스템은 주행중인 자동차 환경에서 보조적인 스위치의 조작없이 상시 음성의 입, 출력이 가능하도록 하며, band pass filter를 이용하여 잡음 환경에 강인한 모델을 선택하도록 하였으며, 음성의 특징 파라미터와 인식 알고리즘은 perceptual linear predictive 13차와 one-stage dynamic programming을 사용하였다. off-line 실험 결과 고속 주행중인 자동차 환경에서 자주 사용하는 차량제어 명령 33개에 대하여 화자독립 82.47%(중부고속도로), 화자종속 94.44%의 인식율을 구하였다. 또한 고속 주행중인 차량에서 kvhs, 핸드폰 사용으로 인한 사고를 줄이기 위하여 음성으로 전화를 걸 수 있도록 하는 Voice Dialing기능도 구현하였다.