• Journal of IKEEE
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• v.28 no.3
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• pp.296-302
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• 2024

In this paper, we propose a driver condition monitoring system using FMCW in-cabin radar, which is free from wearing inconvenience and privacy issues. Using 77GHz high-precision radar, the system detects changes in eye blinking patterns according to changes in the driving environment and the driver's condition using an adaptive multiple filtering algorithm, and accurately determines drowsy driving by measuring the number of eye blinks and the time it takes to open and close the eyes through the detected data. With the emergence of high-performance radars that are becoming more and more miniaturized, it is possible to embed them in the instrument panel or rearview mirror of the vehicle, and if the driver is judged to be drowsy, it can wake up the driver through an alarm or interlock with the vehicle's driving system to slow down and make an emergency stop to prevent accidents and promote driver safety.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.213-224
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• 2009

This paper presents a new algorithm for estimating a driver's physical condition using real-time vision system and performs experimentation for real facial image data. The system relies on a face recognition to robustly track the center points and sizes of person's two pupils, and two side edge points of the mouth. The face recognition constitutes the color statistics by YUV color space together with geometrical model of a typical face. The system can classify the rotation in all viewing directions, to detect eye/mouth occlusion, eye blinking and eye closure, and to recover the three dimensional gaze of the eyes. These are utilized to determine the carelessness and drowsiness of the driver. Finally, experimental results have demonstrated the validity and the applicability of the proposed method for the estimation of a driver's physical condition.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.457-462
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• 2021

As South Korea is a mountainous topography, installation of tunnel is essential for construction of expressway in straight lines. According to "2019 Road Bridge and Tunnel Status Report", there are 2,682 tunnels in Korea with total length of 2,077km. Tunnels take up 1.9% of total road length and the number of tunnel increased by 94% with 1,300 newly constructed tunnels over the 10 years. According to domestic and foreign researches, a long tunnel over 1km in expressway has dark lightings and monotonous wall design which decrease driver's concentration and make the driver feel bored. This leads to feeling fatigue and drowsiness more easily. In response, Korea Expressway Corporation installed design lighting that increases attentiveness on 10 tunnels with total length over 3km by 2020. To reduce the risks of accident that may happen inside the tunnel, this study conducted a comparative analysis on characteristics of each type of LED landscape lighting installed inside the expressway tunnel. The study aimed on providing the basic material for effective installation of LED landscape lighting for securing driving stability, reducing fatigue, and lowering the risk of drowsiness.

• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.323-329
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• 1999

This paper proposed a method for the cancellation of the moving artifact which was produced during the detection of drowsiness usmg electrodermal activity signal. Two types of wrist electrode were developed to overcome the defect of the steering wheel type electrode which couldn't eliminate the moving artifacts due to driver's movements. Wrist type electrode II which has been modified from electrode type I was most effective for eliminating movmg artifacts compared to wheel type electrode and wrisL type electrode 1. The decIsion criteria(if IRI$\leq$10 and 1.1$\leq$dNz) for detecting moving artifact was determined from the virtual driving experiments. An algorithm which substituted past value of Nz for the current value of Nz whenever an EDA signal satisfied the criteria was developed. The experimental resulls of virtual driving and road test showed that the proposed algorithm had been successfully removed the most of the error due to the moving artifact Therefore, the developed system which use electrode type II and the algorithm might be less influenced by moving artifacts and could measure an accurate arousal state.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.905-910
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• 2022

Drowsy driving requires a lot of social attention because it increases the incidence of traffic accidents and leads to fatal accidents. The number of accidents caused by drowsy driving is increasing every year. Therefore, in order to solve this problem all over the world, research for measuring various biosignals is being conducted. Among them, this paper focuses on non-contact biosignal analysis. Various noises such as engine, tire, and body vibrations are generated in a running vehicle. To measure the driver's heart rate and respiration rate in a driving vehicle with a piezoelectric sensor, a sensor plate that can cushion vehicle vibrations was designed and noise generated from the vehicle was reduced. In addition, we developed a system for classifying whether the driver is sleeping or not by extracting the model using the CNN-LSTM ensemble learning technique based on the signal of the piezoelectric sensor. In order to learn the sleep state, the subject's biosignals were acquired every 30 seconds, and 797 pieces of data were comparatively analyzed.

• Journal of Auto-vehicle Safety Association
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• v.8 no.1
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• pp.13-18
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• 2016

More than 80 percent of traffic accidents related with lane departure believed to be the result of crossing the lane due to either negligence or drowsiness of the driver. Lane-departure related accident in the highway usually involve high fatality. Even though LDWS is believed to prevent accident 25% and reduce fatalities by 15% respectively, its effectiveness in performance is yet to be confirmed in many aspects. In this study, the vehicle lateral locations relative to warning zone envelop (earliest and latest warning zone) defined in ISO standard, ECE and NHTSA regulations are compared with respect to various factors including delays, vehicle speed and vehicle heading angle with respect to the lane. Since LDWS is designed to be activated at the speed over 60 km/h, vehicle speed range for the study is set to be from 60 to 100 km/h. The vehicle heading angle (yaw angle) is set to be up to 5 degree away from the lane (abrupt lane change) considering standard for lane change test using double lane-change test specification. The TLC is calculated using factors like vehicle speed, yaw angle and reaction time. In addition, the effect of vehicle type and reaction time have been considered to assess LDWS safety.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.565-575
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• 2012

In the modern everyday life, cars the largest proportion of smart features that require mounting in a variety of smart devices and smart methods on have been developed. In this paper, the smart car among the main core of the safety management system optional for the control of drinking and drowsiness, as part of system development, will be drinking if you start your car automatically is to develop a system to avoid driving. For this, through image processing to analyze the driver's seat of the driver's facial color how to determine whether or not drinking alcohol is proposed. In particular, the system developed in this paper determines whether or not drinking alcohol before the face images without the need for alcohol after only a unique color change of the face appears to target only way to determine whether drinking and actual alcohol control center of a smart car safety control management system can be applied effectively. The experiment was done in 30 patients after drinking appears face color changes of them. We also perform an analysis on the statistical significance of the experimental results to verify the effectiveness of the proposed method.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.491-498
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• 1997

This paper describes the arousal measurement and control system using fuzzy logic to prevent drowsy driving. Sugeno's method was used for fuzzy inference in this study. Arousal evaluation and control criteria were modified from result of Nz-IRI analysis depending on arousal sate. Membership function and rule base of fuzzy inference were determined from the modified arousal level criteria When lRl (Inter-SIR Interval) was shorter than 60sec, outputs of both methods were changed from small to big, but output of three step warning method was same level until the next warning range. Since output of fuzzy inference tracked well the change of subject's arousal level, problems of three step warning method could be overcome by fuzzy inference method Furthermore, the output of the fuzzy inference was highly correlated with Nz(r = 0.99). Therefore, the fuzzy inference method for evaluation and the control of arousal will be more effective at real driving situation than three step warning method.