• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.1-9
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• 2014

This study tried to propose plan to prevent human error of railroad driver among human error of railroad worker which takes great share in railroad accident. For this, in order to maintain correlation between the accident actually occurred after the opening of high-speed railroad and experience of accident that did not happened, survey on respondent was analyzed by conducting survey on KTX captain who is working in driving work of high-speed railroad, and instruction management team manager who manages KTX captain and captain. This thesis classified the factors by human factor, job factor, environment factor, organization factor, and established human error management model by comparing and analyzing how each factors have spatial interrelations with a railroad accident. The purpose of this study is to contribute to make safe railroad, and reliable railroad by preventing human error accident by minimizing human error of high-speed railroad drivers, and improving driving workers to cope accurately and fast with irregularities through various institutional improvement, improvement of driving facilities, improvement of operating room environment, and improvement of education system.

• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.85-94
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• 2006

The purpose of this study is to extract typical body shapes of Korean adults based on the three-dimensional Korean anthropometric data measured through 5th national anthropometric survey and to examine the suitability of the 3-D human shape data for the interior packaging. 36 three-dimensional anthropometric variables related to the design of vehicle interior were considered for the appraisal of typical body shapes. Four major factors were extracted by the factor analysis and factor scores were calculated for all subjects. Typical or standard drivers of Korean adults were selected by the minimum deviation criteria for the four factor scores with respect to 5th, 50th, and 95th percentiles, respectively. Typical drivers of Korean adults were visualized by the CATIA-HUMAN program due to the absence of proper application software for three-dimensionally scanned human body data. There are considerable differences between the anthropometric data of Korean adults and those provided by CATIA-HUMAN program, which shows that the modeling data provided by CATIA-HUMAN should not be directly applied to the ergonomic evaluation for the vehicle design. This suggests the necessity for the development of suitable software for scanned human shape data. It is also expected that the anthropometric data of typical drivers extracted from this study help design package layouts and improve the suitability of ergonomic evaluation for Korean customers.

• Journal of the Korean Society of Safety
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• v.22 no.1 s.79
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• pp.61-66
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• 2007

Car crashes are the leading cause of death for persons of every age. Specially, human-related factor has been known to be the primary causal factor of such crashes than vehicle-and environmental-related factors. There are various studies to analyze driver's behavior and characteristics in driving for reducing the car crashes in many areas of car engineering, psychology, human factor, etc. However, there are almost no studies which analyze mainly the human errors in driving and estimate their probabilities in terms of human reliability analysis. This study estimates the probability of human error in driving, i.e. driver error probability. First, fifty driver errors are investigated through DBQ (Driver Behavior Questionnaire) revision and the error likelihoods in driving are collected which are judged by skillful drivers using revised DBQ. Next, these likelihoods are converted into driver error probabilities using the results that verbal probabilistic expressions are changed into quantitative probabilities. Using these probabilities we can improve the warning effects on drivers by indicating their driving error likelihoods quantitatively. We can also expect the reduction effects of car accident through controlling especially dangerous error groups which have higher probabilities. Like these, the results of this study can be used as the primary materials of safety education on 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.

• International Journal of Highway Engineering
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• v.17 no.3
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• pp.117-124
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• 2015

PURPOSES : The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS : To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS : This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including ${\chi}^2/df$, GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS : Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.19-29
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• 2014

Korean societal concern for the train accidents is fast and widely increasing with an ever-increasing demand and use for KTX. Most of these train accidents are inclined to be caused by human error. Experts used to attribute the causes of human error to the defects in various aspects such as technology, organizational system, practices, corporate culture, and/or human resource itself. Among the diverse causes of human error, an important one, even though it was rarely focused, may be the issue of impact of rule or procedure change on human error. Giving attention to the implicit importance of this issue, this study intends to highlight the theme of frequent procedure change in railway driving manual as a critical factor of human error. To attain this purpose mentioned above, dual methodologies were adopted. One is to qualitatively analyze the real cases of procedure change in relevant manuals followed by the incident case(passing the station scheduled to stop) happened lately. Another is to quantitatively perform statistical analysis based on questionnaires received from 224 train drivers. Results show that frequent changes in internal affairs procedure is or may be an important factor causing stress and human error from train drivers.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.123-131
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• 2002

Simulators have been used to evaluate drivers'reactions to various transportation products. Most researches, however, have been concentrated on their technical performance, thus this paper considers drivers'senses of moving on a vehicle simulator through the analysis of human sensibility ergonomics. A sensibility ergonomic method is proposed in order to improve the faithfulness of vehicle simulators. A simulator of passenger vehicle consists of such three modules as vehicle dynamics, virtual environment, and motion representation modules. To evaluate drivers'feedback, human feelings are categorized into a set verbal expressions collected and investigated to find the most appropriate ones for translational and angular accelerations of the simulator The cutoff frequency of the washout alter ill the representation module is selected as one sensibility factor Sensibility experiments were carried out to find correlation between the expressions and the cut-off frequency of the filter. This study suggests a methodology to obtain an ergonomic database which can be applied to the sensibility evaluation of dynamic simulators.

• Industrial Engineering and Management Systems
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• v.10 no.4
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• pp.288-291
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• 2011

Recommendations for older driver-friendly automobile interior design have been determined by taking into account older people's physical and cognitive characteristics. Twenty three older people (aged from 54 to 78) and five younger people (from 20 to 29) performed several tasks in actual driving conditions, in which their reaction times and performance errors were recorded. Some design factors were found to be related to older drivers' visibility and controllability. Several design recommendations were proposed in terms of cluster color and font, display location, and HVAC control type. Proposed recommendations are expected to satisfy a wider range of older drivers as these will facilitate automobile interior designs which are fitter to older drivers' visual, cognitive, and manual capabilities.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.99-109
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• 2007

Variable message signs (VMS), which are used for providing real-time information on traffic conditions and accident occurrences, are one of the important components of intelligent transportation systems VMS messages need to meet human factor requirements: messages should be readable and understandable while driving. Lab-controlled experiments on VMS messages were conducted to obtain useful data for analyzing drivers' responsive characteristics for VMS messages. Binary logistic regression (BLR) modeling techniques were applied to explore the relationships among drivers' message perceptions, message reading time, and amount of VMS messages. Probabilistic outcomes of the proposed BLR-based perception model could be greatly utilized to design VMS messages considering drivers' legibility performance. The major contribution of this study is to develop invaluable statistical models that can be used in designing VMS messages more effectively from the human factor point of view. The results could be further applied to establish the scheme of VMS message phase and duration.

• Korean Journal of Culture and Social Issue
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• v.18 no.3
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• pp.415-433
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• 2012

This study was conducted in order to explain the effect of driving behavior determinants such as drivers' personality and attitude that may induce risky driving behavior and to develop a valid method for discriminating risky drivers using the determinants. In the results of surveying 534 adult drivers, 5 driving behavior determinants (avoidance of problems, benefit/stimulus seeking, interpersonal anxiety, interpersonal anger, and aggression) were found to have a statistically significant effect on drivers' various risky driving behaviors. Using these factors, drivers were grouped according to risk levels (normal drivers, unintentionally risky drivers, and intentionally risky drivers). This result suggests that drivers' dangerous behavior level can be predicted using psychological factors such as their personality and attitude. Accordingly, if the driving behavior determinant model and the base score system used in this study are improved through further research, they are expected to be useful in predicting drivers' recklessness in advance, identifying problems, and providing differentiated safe driving education services based on the results.