• 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.

• 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.

• 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.

• 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 Biomedical Engineering Research
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• v.18 no.3
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• pp.315-323
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• 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.

• Safety and Health at Work
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• v.7 no.1
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• pp.38-42
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• 2016

Background: Truck driving is known as one of the occupations with the highest accident rate. This study investigates the characteristics of traffic collisions according to road types (expressway and rural road). Methods: Classifying 267 accidents into expressway and rural road, we analyzed them based on driver characteristics (age, working experience, size of employment), time characteristics (day of accident, time, weather), and accident characteristics (accident causes, accident locations, accident types, driving conditions). Results: When we compared the accidents by road conditions, no differences were found between the driver characteristics. However, from the accident characteristics, the injured person distributions were different by the road conditions. In particular, driving while drowsy is shown to be highly related with the accident characteristics. Conclusion: This study can be used as a guideline and a base line to develop a plan of action to prevent traffic accidents. It can also help to prepare formal regulations about a truck driver's vehicle maintenance and driving attitude for a precaution on road accidents.

• Korean Journal of Clinical Laboratory Science
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• v.47 no.4
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• pp.216-224
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• 2015

This study aims to identify the prevalence of sleep related disease in those who experienced car accidents caused by drowsy driving. To this end, a survey of usual sleep habits, polysomnography, and multiple sleep latency tests were conducted in 34 persons who experienced an accident after normal sleep (Group 1), 22 persons who experienced an accident after abnormal sleep (Group 2), and 17 persons who was proven to be normal as a result of polysomnography and had no accident (Group 3). In all, 192 persons responded to the preliminary survey and the results were compared and analyzed. Crossover analysis was conducted to test the homogeneity of statistical characteristics, and the physical characteristics by age were analyzed. In the survey of sleeping habits, there was a significance between groups in how often they woke up while asleep (p<0.01), how difficult it was to go back to sleep again after waking up from sleep (p<0.05), how early they woke up in the morning (p<0.05), how difficult it was to get up in the morning (p<0.05), how sleepy they felt in the daytime (p<0.01), and how tired they felt in the daytime (p<0.01). Furthermore, among 56 subjects who had an accident during drowsy driving, 94.6% (53 persons) were found to have sleep related diseases. This suggests that car accidents during drowsy driving is not simply caused by temporary lack of sleep but by sleep related diseases even when sleep is adequate, leading to car accidents. Therefore, this study is significant identifying the association between car accidents during drowsy driving and sleep related disorders. Furthermore, the data would be considered basic to prepare social measures against drowsy driving related to such sleep related disorders.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.142-148
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• 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
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• v.17 no.6
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• pp.85-95
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• 2015

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

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