• 전자통신동향분석
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• 제38권6호
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• pp.31-40
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• 2023

Given recent accidents involving autonomous vehicles, driver monitoring technology related to the transition of control in autonomous vehicles is gaining prominence. Driver status monitoring systems recognize the driver's level of alertness and identify possible impairments in the driving ability owing to conditions including drowsiness and distraction. In autonomous vehicles, predictive factors for the transition to manual driving should also be included. During traditional human driving, monitoring the driver's status is relatively straightforward owing to the consistency of crucial cues, such as the driver's location, head orientation, gaze direction, and hand placement. However, monitoring becomes more challenging during autonomous driving because of the absence of direct manual control and the driver's engagement in other activities, which may obscure the accurate assessment of the driver's readiness to intervene. Hence, safety-ensuring technology must be balanced with user experience in autonomous driving. We explore relevant global and domestic regulations, the new car assessment program, and related standards to extract requirements for driver status monitoring. This kind of monitoring can both enhance the autonomous driving performance and contribute to the overall safety of autonomous vehicles on the road.

• 센서학회지
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• 제23권2호
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• pp.142-147
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• 2014

Real time driver's respiration monitoring method for detecting driver's drowsiness is investigated. The sensor to obtain driver's respiration signal was a piezoelectric pressure sensor attached at the abdominal region of the seat belt. The resistance of the pressure sensor was changed according to the pressure applied to the seat belt due to the driver's respiration. Monitoring driver's respiration was carried out by driving on the virtual road in a driving simulator from Cheonan to Seoul and monitoring results were compared to the PELCLOS. Experiment results show that the driver's respiration signal can be used for detecting driver's drowsiness.

• 자동차안전학회지
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• 제13권1호
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• pp.38-44
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the real-world driving study, 52 drivers drove approximately 11.0 km of rural road (about 20 min), 7.9 km of urban road (about 25 min), and 20.8 km of highway (about 20 min). The results suggested that the appropriate number of blinks during the last 60 seconds was 4 times, and the head movement interval was 35 seconds. The results from drowsy driving data will be presented in another paper - part 2.

• 자동차안전학회지
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• 제13권1호
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• pp.45-50
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the drowsy driving study, 10 drivers drove approximately 37 km of a monotonous highway (about 22 min) twice. The results suggested that the appropriate duration of eyes continuously closed was 4 seconds. The results from real-world driving data were presented in the other paper - part 1.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.33-35
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• 2004

In this paper, web based monitoring systems are implemented for multi-axis force control systems of an intelligent robot. Linux operating systems are ported to an embedded system which Include a Xscale processor to implement a web based monitoring system. A device driver is developed to receive data from multi-axis force sensors of intelligent robots. To control this device driver, a socket program for Labview is also developed.

• 자동차안전학회지
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• 제12권1호
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• pp.52-61
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• 2020

In recent years, the increasing interest in health-care requires the industrial products to be well-designed ergonomically. In the commercial vehicle industry, several researchers have demonstrated the driver's posture has great effect on the orthopedic desease such as fatigue, back pain, scoliosis, and so on. However, the existing sensor systems developed for measuring the driver posture in real time have suffered from inaccuracy and low reliability issues. Here, we suggest our smart vehicle seat system capable of real-time driver posture monitoring by using the air bag sensor package with high sensitivity and reliability. The ergonomic numerical model which can evaluate a driver's posture has been developed on the basis of the human body segmentation method followed by simulation-based validation. Our experimental analysis of obtained pressure distribution of a vehicle seat under the different driver's postures revealed our smart vehicle system successfully achieved the driver's real-time posture data in great agreement with our numerical model.

• International Journal of Internet, Broadcasting and Communication
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• 제14권2호
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• pp.119-128
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• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.

• 대한인간공학회지
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• 제29권1호
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• pp.17-24
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• 2010

There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the ROad Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

• 한국정보통신학회논문지
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• 제14권5호
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• pp.1303-1310
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• 2010

최근 운전자의 건강상태 모니터링 및 졸음운전 방지를 위한 자동차용 부품관련 센서개발 및 시스템 연구들이 국내외에서 활발히 진행되고 있다. 본 논문은 이러한 운전자의 건강 상태 및 졸음운전을 점검하기 위해 체스트벨트 심전도 (ECG)와 손목착용형 산소포화도 (SpO2) 센서를 제작하여 생체신호를 측정하였으며, 측정된 심전도, 산소 포화도, 그리고 심장박동수 신호는 무선센서네트워크를 통해 수집, 전송 및 모니터링 등의 처리를 가능하게 하여 운전자에게 안전운행을 위한 정보를 제공하도록 하였다. 원격지인 서버 PC와 연결된 베이스스테이션으로 수집된 심전도와 용적맥파 신호에서 HRV (Heart Rate Variability, 심박변이도) 신호를 검출하였으며, 검출된 HRV 신호를 시간 영역과 주파수 영역에서의 해석을 통하여 운전자의 스트레스 지수 및 졸음 상태의 실시간 모니터링 및 졸음상태의 운전자에게 주의를 제공하기 위하여 알람을 제공하는 형태의 지능형 모니터링 시스템을 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1675-1678
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• 2004

In this paper, web based monitoring systems are implemented for multi-axis force control systems of an intelligence robot. A brief review about the principle of multi-axis force sensors and a method that can reduce the effect of noise signal to sensor performance is presented. A web based monitoring system is implemented by porting Linux at embedded systems which include Xscale processors. A device driver is developed to receive data from multi-axis force sensors in Linux operation systems. To control this device driver, a socket program for web browser is also developed. The experiments are performed to investigate the effectiveness of proposed methods. The experimental results show that the values of force sensors can be monitored by remote PCs.