• Sleep Medicine and Psychophysiology
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• v.10 no.2
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• pp.84-87
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• 2003

Drowsy driving is a major cause of automobile crashes and can lead to more serious injuries than other causes of traffic accidents. Factors increasing the risk of drowsy driving and related crashes include sleep loss, late night driving, untreated or unrecognized sleep disorders, use of sedating medications and consumption of alcohol. Young people, especially young males, shift workers, and people with untreated sleep apnea syndrome and narcolepsy are well known as the population groups at highest risk. To prevent drowsy driving and its consequences, getting adequate and quality sleep is both easier and much more successful than any remedial measure. Other helpful behaviors include avoidance of alcoholic beverages and limiting late night driving. Taking a short nap or consuming caffeine can make a short-term difference in driving alertness. In addition, information should be actively provided to the public about the importance of sleep disorders and their consequences. To reduce injuries and death caused by drowsy driving, it is a prerequisite to increase public awareness that drowsy driving can cause serious automobile crashes and has morbidity and mortality rates as high as those of drunk driving.

• Journal of Convergence for Information Technology
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• v.8 no.3
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• pp.193-198
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• 2018

Recently, the casualties of automobile traffic accidents are rapidly increasing, and serious accidents involving serious injury and death are increasing more than those of ordinary people. More than 70% of major accidents occur in drowsy driving. Therefore, in this paper, we studied the drowsiness prevention system to prevent large-scale disasters of traffic accidents. In this paper, we propose a real-time flicker recognition method for drowsy driving detection system and drowsy recognition according to the increase of carbon dioxide. The drowsy driving detection system applied the existing image detection and the deep running, and the carbon dioxide detection was developed based on the IoT. The drowsy prevention system using both of these techniques improved the accuracy compared to the existing products.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.160-168
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• 2017

In the past 10 years, the accidents caused by drowsy driving have occupied about 23% of all traffic accidents in Korea expressway network and this rate is the highest one among all accident causes. Unlike other types of accidents caused by speeding and distraction to the road, the accidents by drowsy driving should be managed differently because the drowsiness might not be controlled by human's will. To reduce the number of accidents caused by drowsy driving, researchers previously focused on the spot based analysis. However, what we actually need is a segment (link) and occurring time based analysis, rather than spot based analysis. Hence, this research performs initial effort by adapting link concept in terms of drowsy driving on highway. First of all, we analyze the accidents caused by drowsy in historical accident data along with their road environments. Then, links associate with driving time are analyzed using digital tachograph (DTG) data. To carry this out, negative binomial regression models, which are broadly used in the field, including highway safety manual, are used to define the relationship between the number of traffic accidents on expressway and drivers' behavior derived from DTG. From the results, empirical Bayes (EB) and potential for safety improvement (PSI) analysis are performed for potential risk segments of accident caused by drowsy driving on the future. As the result of traffic accidents caused by drowsy driving, the number of the traffic accidents increases with increase in annual average daily traffic (AADT), the proportion of trucks, the amount of DTG data, the average proportion of speeding over 20km/h, the average proportion of deceleration, and the average proportion of sudden lane-changing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.577-578
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• 2016

This paper presents a method of vehicle safety system using a pulse sensor which will be able to occurs drowsy driving accident when people driving. The proposed vehicle safety system alarms according to the driver drowsy condition, therefore the driver prevent the direct and $2^{nd}$ accident beforehand cognitive unexpected and dangerous accident using vehicle safety system.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.321-327
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• 2024

Out-of-home (Out-of-Home) advertising can be an effective means of delivering messages for preventing drowsy driving, given that it is exposed at locations and times where vehicle traffic occurs. This study investigated the influence of message framing of drowsy driving prevention OOH advertising and regulatory focus on the intention to drowsy driving prevention behaviors by an experimental study targeting 200 university students. The results showed an interaction effect between message framing and regulatory focus on the intention to drowsy driving prevention behaviors. While no significant differences were observed in the intention to drowsy driving prevention behaviors based on regulatory focus for positively framed messages, for negatively framed messages, a higher intention was observed when the prevention focus group rather than promotion focus group. This study focuses on two key areas: how messages are crafted (message framing) and the characteristics of the people who receive them (regulatory focus). By exploring these aspects, it provides valuable theoretical and practical knowledge. Essentially, it opens doors for creating message strategies that are finely tailored to suit the preferences of the audience. This advancement is vital for researchers and practitioners as it enhances the effectiveness of communication efforts.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.423-433
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• 2017

During recent 5 years, it was recorded that 20% of total accident frequency and 30% of total number of death have been occurred due to drowsy driving. Drowsy driving accident is result from the loss of driving ability due to driver's accumulated fatigue. Continuous driving time can be measured as a surrogate variable to quantify the level of fatigue. The main purpose of this research is to investigate statistical correlation between the proportion of continuous driving vehicle (more than 2 hours) and the number of drowsy accidents. To carry this out, continuous driving time was measured using GPS route-guidance trajectory data. Also, accident frequency, traffic volume and segment length were collected to estimate safety performance function (SPF) for Jungbunearuk expressway in Korea. Through various types of estimated SPFs, statistical correlation was analyzed based on estimated statistical indices. This research can provide theoretical background for enforcement to regulate commercial vehicle driver's continuous driving time. In addition, throughout the trajectory data expansion, it is expected that strategy for anti-drowsy driving facilities installation can be established based on the suggested methodology.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.133-139
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• 2008

In this paper, the feasibility for producing a plastic optical fiber sensor to be used as an anti-drowsy driving sensor is discussed. This sensor consists of a plastic optical fiber wound on the steering wheel covered by soft material. When a driver hold a steering wheel, the gripping force is induced and causes to the bend of the plastic optical fiber which decreases the power of light propagated inside the plastic fiber. The experimental results show that the detected optical power decrease as the gripping force increase and that this sensor can be used as the anti-drowsy driving sensor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.447-450
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• 2013

This paper proposes the way to prevent drowsy driving by recognizing drivers eyes and yawn using a front camera. The method uses the Viola-Jones algorithm to detect eyes area and mouth area from detection face region. In the eyes area, it uses the Hough transform to recognize eye circle in order to distinguish drowsy driving. In the mouth area, it determines whether for the driver to yawn through a sub-window testing by applying a HSV-filter and detecting skin color of the tongue. The test result shows that the recognition rate of yawn reaches up to 90%. It is expected that the method introduced in this paper might contribute to reduce the number of drowsy driving accidents.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.30-39
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• 2012

An effective drowsy driver detection system is needed, because the probability of accident is high for drowsy driving and its severity is high at the time of accident. However, the drowsy driver detection system that uses bio-signals or vision is difficult to be utilized due to high cost. Thus, this paper proposes a drowsy driver detection algorithm by using steering angle sensor, which is attached to the most of vehicles at no additional cost, and vehicle information such as brake switch, throttle position signal, and vehicle speed. The proposed algorithm is based on jerk criterion, which is one of drowsy driver's steering patterns. In this paper, threshold value of each variable is presented and the proposed algorithm is evaluated by using acquired vehicle data from hardware in the loop simulation (HILS) through CAN communication and MATLAB program.