• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.7
• /
• pp.934-939
• /
• 2018

Recently, there have been a lot of sleepy driving accidents. In this study, we conducted a preliminary study for detecting drowsiness using posture and image processing technology. We used pressure sensors to study posture. We also investigated the possibility of drowsy recognition using histogram. As a result of the experiment, it was possible to distinguish positions through pressure sensors. Also, it was confirmed that the drowsiness phenomenon can be distinguished by using the histogram.

• Journal of Biomedical Engineering Research
• /
• v.18 no.3
• /
• pp.315-323
• /
• 1997

Driving is a complex vigilance task that includes improper lookout, excessive speed and inattention. The primary objective of this research is to detect driver drowsiness so that the driver can be alerted to an impending traffic accident in performance. We developed the automatic detection and warning system during drowsy driving. A drowsiness detection system must be able to monitor driver status and detect the detrimental changes of a driver performance. Eyeblink has been found to be a reliable factor of drowsiness detection in earlier studies. As an additional parameter, we also considered the yawning which often occurs in a low vigilance state and predicts the drowsy state. We used a computer vision method to extract the eyeblink and yawning in the face image sequences. When the drowsy state was detected, the driver was refreshed by alarming device and menthol scent generator after deciding the warning level by fuzzy logic. For the evaluation of our system, we measured the physiological parameters such as EOG and EEG. The results indicated that it is possible to detect and alert the driver drowsiness temporarily or continuously by using our system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.7
• /
• pp.917-922
• /
• 2021

In modern society, deaths and property damage due to drowsiness occur every year enormously. Methods to reduce such damage are being studied a lot in all walks of life, and research on preventing drowsy driving is particularly active in automobiles. In this paper, as an Arduino-based water gun firing system that learns open and closed eyes using YOLO, we propose a drowsy prevention system that fires a water gun when the duration of the closed eye exceeds a certain time. This system can be applied and used in various fields, but especially when applied to a car, it is not necessary to purchase expensive specifications and if you pay a little attention, you can reduce accidents caused by drowsy driving by 100% at a very low cost. In addition, it can be said that it is an independent system that overcomes different specifications for each company.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.4
• /
• pp.142-148
• /
• 2023

In Modern days, Self-driving for modern people is an absolute necessity for transportation and many other reasons. Additionally, after the outbreak of COVID-19, driving by oneself is preferred over other means of transportation for the prevention of infection. However, due to the constant exposure to stressful situations and chronic fatigue one experiences from the work or the traffic to and from it, modern drivers often drive under drowsiness which can lead to serious accidents and fatality. To address this problem, we propose a drowsy driving prevention learning model which detects a driver's state of drowsiness. Furthermore, a method to sound a warning message after drowsiness detection is also presented. This is to use MoveNet to quickly and accurately extract the keypoints of the body of the driver and Dense Neural Network(DNN) to train on real-time driving behaviors, which then immediately warns if an abnormal drowsy posture is detected. With this method, we expect reduction in traffic accident and enhancement in overall traffic safety.

• International Journal of Highway Engineering
• /
• v.18 no.5
• /
• pp.75-82
• /
• 2016

PURPOSES : This study was initiated to estimate the benefits from the campaign to prevent drowsy driving crashes on expressways. The study was conducted by the Korea Expressway Corporation using a contingent valuation method. METHODS : First, a questionnaire was designed for a preliminary survey. From the survey's results, the initial willingness to pay for the campaign was determined by averaging different amounts of payments chosen under virtual scenarios in the survey. The willingness to pay data was used to find a first bid price for the open-ended method used for the second survey. After that, a primary questionnaire was designed and conducted using a single dichotomous choice question (SDBCQ). Drivers at expressway resting areas were asked their willingness to pay for the campaign. Based on statistical analysis using data collected from the second survey, the mean willingness to pay was estimated using a probability utility function. Finally, the benefit from the campaign was calculated using the estimated willingness to pay and accident data on expressways. CONCLUSIONS : Based on the result from the contingent valuation method, the benefit from the campaign to prevent drowsy driving crashes was estimated to be 170.6 won per expressway trip. The benefit is to be paid as an additional toll. In addition, the traffic crash cost estimate is about 2,209,680,000 won less than the cost during the same period in 2014.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.947-950
• /
• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Journal of Korea Multimedia Society
• /
• v.20 no.6
• /
• pp.873-881
• /
• 2017

Prevention of drowsy driving is one of the important issues for safe driving. In this study, the algorithm for detection of drowsy driving has been developed. The algorithm was implemented by applying template matching and line profile, which detects eye blink. The accuracy of eye detection and blink detection was $97.45{\pm}3.67%$ and $98.50{\pm}0.92%$, which was resulted from the verification experiment that 21 subjects participated. Consequently, the algorithm is expected to be used to prevent sleep-deprived driving.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.1
• /
• pp.38-44
• /
• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.9
• /
• pp.4518-4540
• /
• 2019

With the development of IT convergence technology, autonomous driving has gradually developed; however, the vehicle is still operated by the driver, who should always be in good health - but sometimes, this is not the case. It is especially dangerous to drive when drowsy, and unable to fully concentrate on driving, such as when taking certain medicines, or through fatigue. Drowsy driving is at least eight times more dangerous than normal driving, and as dangerous as drunk driving. Previous research has looked at technology to detect drowsiness, in order to wake up drivers when necessary, or to safely stop the vehicle. Furthermore, many studies have been conducted to find out when drowsiness occurs. However, it is more desirable for the driver to take sufficient rest during a break, in order to be able to continue to focus and drive. In other words, it is important to maintain a normal state before drowsiness. In this study, we introduce a sound source to increase driver concentration and prevent drowsiness, another that can improve the quality of sleep, and a system that produces these sound sources. The proposed system has a noise reduction effect of about 15 dB. We have confirmed that the proposed sound induces an EEG of the desired form.

• International Journal of Highway Engineering
• /
• v.20 no.2
• /
• pp.1-8
• /
• 2018

PURPOSES : In this study, design elements of rest areas for drowsy drivers are classified and appropriate criteria for each design element are presented. METHODS : By comparing and analyzing the design criteria for rest areas, the most appropriate installation criteria were suggested by considering the driving patterns of rest area users. RESULTS : As a result of the study, elements influencing the design of rest areas for drowsy drivers are suggested such as installation location and installation type. In addition, proper separation distance between resting areas was suggested considering vehicle flow, users' fatigue and physiological needs. Other criteria for rest areas were also suggested. CONCLUSIONS : Proper safety facilities were not installed in rest areas because appropriate criteria were not established. In this study, design elements were derived and installation criteria were designed so that rest areas could be used safely and conveniently.