• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.202-217
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• 2021

Following the fatal accident of pedestrians caused by Autonomous Vehicle by Uber, the world's largest ride-hailing company, two people were killed in a self-driving car accident by Tesla in April. There is a need to ensure the safety of road users. Accordingly, in order to secure the safety of Autonomous Vehicle driving, it is necessary to evaluate Autonomous Vehicle driving technologies in various situations based on the road and traffic environment in which the Autonomous vehicle will actually drive. Therefore, this study used UC-win/Road ver.14.0 based on general driver's license test questions to present a virtual reality-based Autonomous Vehicles driving ability evaluation tool among various driving ability test method. Based on this, it was intended to test driving ability for unexpected situations in complex and diverse driving environments, and to confirm its practical applicability as an optimal tool for Autonomous vehicle ability test and evaluation.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.37-46
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• 2012

The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.

• Journal of Preventive Medicine and Public Health
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• v.22 no.3 s.27
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• pp.313-322
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• 1989

The present status of the traffic accident rate in Korea shows that it is the highest in the world with a continuously increasing trend. Human factors account for 90% of the causes of traffic accidents. Therefore, the purpose of this study was to determine some human factors related to traffic accidents by studying the relationship between health status and traffic accidents. To accomplish this purpose, all taxi companies located in the Seoul area were divided in three groups according to the number of taxi possessed, then some companies in each ?roup were randomly selected for study, and a total of 222 drivers in those selected companies were questioned and examined from April 15 to April 22, 1989. Seventy drivers among 222 had experienced a traffic accident. A $x^2$-test was performed on the data, then, factor analysis and discrminant analysis were executed with the following results: 1. The drivers complaining of gastroenteric symptoms numbered 110(49.5%), which was the major symptom among all drivers complaining of poor health. 2. In the primary analysis, variables related to traffic accidents were divided into general, occupational, and health characteristics. Drivers having no traffic accident experience and drivers having that experience were subjected to question about age, educational level, residential status, monthly average income, working hours and days, degree of satisfaction with their profession and homelife, degree of worry about health. degree of fatigue, medication, drunken driving, and illness, but there were no statistical significances. 3. In the factor analysis, the 8 health variables which cause traffic accidents were classified into 3 common factors which were perceived health factor, sleeping and drunken driving, and visual acuity and smoking factor. Perceived health was the factor which contributed most to explaining accidents. 4. In the discriminant analysis, a correct prediction rate of 68.0% was obtained in the factors of all the characteristics. 5. Degree of sttisfaction with their homelife and educational and economic factor in the general characteristics, degree of satisfaction with their profession in the occupational characteristics, and sleeping and drunken driving in the health characteristics were selected as statistically significant factors to discriminant the traffic accident. 6. Among the factors of the general, occupational, and health characteristics, degree of satisfaction with their homelife, driving experience, family factor, perceived factor were selected as the statistically significant factors.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.166-172
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• 2018

The distraction of the driver's attention causes as much traffic accidents as drowsiness driving. Yet though there have been many studies on drowsiness driving, research on distraction driving is insufficient. In this paper, we divide distraction of attention into visual distraction and cognitive distraction and analyze the EEG of subjects while viewing images of distracting situations. The results show that more information is received and processed when distractions occur. It is confirmed that the probability of accident increases when the driver receives overwhelming amount of information that he or she cannot concentrate on driving.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.101-112
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• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2960-2973
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• 2022

Since Fukushima nuclear power plant (NPP) accident in 2011, the importance of research on various severe accident phenomena has been emphasized. Particularly, detailed analysis of combustion risk is necessary following the containment damage caused by combustion in the Fukushima accident. Many studies have been conducted to evaluate the risk of local hydrogen concentration increases and flame propagation using computational code. In particular, the potential for combustion by local hydrogen concentration in specific areas within the containment has been emphasized. In this study, the process of flame propagation generated inside a reactor core to containment during a loss of coolant accident (LOCA) was analyzed using MELCOR 2.1 code. Later in the LOCA scenario, it was expected that hydrogen combustion occurred inside the reactor core owing to oxygen inflow through the cold leg break area. The main driving force of the oxygen intrusion is the elevated containment pressure due to the molten corium-concrete interaction. The thermal and mechanical loads caused by the flame threaten the integrity of the containment. Additionally, the containment spray system effectiveness in this situation was evaluated because changes in pressure gradient and concentrations of flammable gases greatly affect the overall behavior of ignition and subsequent containment integrity.

• Journal of the Korean Society of Safety
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• v.30 no.2
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• pp.56-62
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• 2015

The purpose of this study was to identify the relationship between the index of Electrocardiography(LF/HF) and the occurrence of drowsiness driving while driving in a simulated situation. Participants were 31 undergraduate students with an experience in driving and they participated 30 minutes driving under enough sleep condition and 1 hour under the sleep deprivation condition. The Euro Truck Simulator II was used for driving simulation task and ECG and perceived drowsiness of each participants were measured during two driving conditions. Perceived sleepiness recorded by the checklist every 10 minutes and ECG data extracted before and after 15 seconds of every 10 minutes to verify the relationship between two variables. The results showed that the level of perceived sleepiness under sleep deprivation condition was higher than that under the enough sleep condition, and the level of LF/HF under sleep deprivation condition was lower than that under the enough sleep condition. In addition, the result of analysis of repeated measure ANOVA for ECG indicated that authentic sleepiness revealed in 20 minutes after the start of driving under the sleep deprivation condition. However, the result of perceived drowsiness indicated that authentic sleepiness revealed in 30 minutes after the start of driving. These result suggest that the time difference between biological and perceived response on drowsiness may be exist. Finally, the significant negative correlation between the LF/HF level and perceived drowsiness was observed. These findings suggest that ECG(LF/HF) can be an possible index to measure drowsiness driving.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.95-102
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• 2011

This paper presents a Driving Risk Model (DRM) based on driving speed choices using an Ordered Response Probit (ORP) model. The DRM is conceptualized based on the relation between speed deviation and the occurrence of crashes found by Solomon. The impacts of various driving risk factors are revealed by applying the DRM to evaluate the effectiveness of In-Vehicle Traffic Warning Information (IVTWI) in expressway driving. Regarding driving risk, the results show that: (1) the risk is lower among male drivers, those with more driving experience and those with less accident history, (2) the risk is higher when driving takes place on wet road surface, in the afternoon, and under conditions of low traffic volume, and (3) the risk is also higher on both downgraded and long curve sections. Additionally, the results provide evidence that provision of IVTWI can decrease the driving risk. The proposed DRM provides a solution for assessing the traffic safety impacts of countermeasures on roadways when there is a shortage of traffic accidents data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1321-1328
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• 2015

The automobiles in Korea have approximately 60 years of history and this is relatively short compared to advanced countries. However, considering the traffic accident rate or severity related to automobiles, various efforts are required to reduce traffic accidents. Various problems caused by traffic accidents are not only related to individual damages but also have become social problems. In order to resolve this, it is important to analyze the cause of traffic accidents. This study aims to suggest methods to reduce traffic accidents by analyzing driving behavior, which is one of the reasons for a number of traffic accidents that were collected through traffic accident videos reported using DVRs (Driving Video Recorder) and were aired to the public via a SBS TV program for the past two years and four months. In particular, unlike other existing studies that aim at analyzing the causes of traffic accidents simply using data, this study constructed a database by analyzing every single DVR that stores the situation before and after the accident using relatively high-resolution video information to provide practical plans to reduce traffic accidents through statistical analysis.