• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.159-169
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• 2015

Speeding has been the most common traffic violation which increases the risk of accidents. The purpose of this study is to examine drivers' behaviors on the speeding intention and speeding action and to identify the relationship between those causes and effects. Effects of behaviors and human characters of drivers on speeding are analyzed through a Driver Behavior Questionnaire and the cause and effect among behavior characters, speeding intention and speeding behavior are validated through the structural equation model. In order to validate the hypothesis of the study, a path analysis is conducted through structural equation model. As the result, Driver Behavior Questionnaire property that influences the speeding is revealed to be the violation while Driver Behavior Questionnaire properties that influences the speeding behavior are lapse, mistake, and violation. And the speeding intention influences the speeding behavior. The study results are compared with previous studies to reveal that Driver Behavior Questionnaire properties influencing the speeding behavior are in the order of violation, mistake and lapse. Three properties of Driver Behavior Questionnaire, lapse, mistake and violation, are behavior scales in agreement with previous studies. The results of this study based on a Driver Behavior Questionnaire are expected to be utilized as a way to predict and validate driving behaviors.

• 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 the Korea Safety Management & Science
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• v.10 no.4
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• pp.65-72
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• 2008

The Manchester Driver Behavior Questionnaire (DBQ) is the most commonly used frameworks for investigating the relationship between self-reported driving behavior and accident involvement. After Reason et al. introduced DBQ, there were many studies replicating the research of Reason et al. in many countries. There was, however, no study replication of the Reason's research in Korea. The aim of this study is to replicate the distinction among errors, lapses and violations, and to evaluate the relationship of these behaviors with road traffic accidents on Korean drivers. 223 Korean drivers completed the Korean version of original DBQ with questions regarding background information, such as age, gender, annual mileage and accident involvement. Participants answered self-assessment questions, also. Factor analysis revealed three factors like Reason et al. The three factors were dangerous errors, violations and relatively harmless errors.

• Journal of the Ergonomics Society of Korea
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• v.25 no.4
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• pp.137-144
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• 2006

The goal of this study is to find out correlation between Driver's Unsafe acts(errors and violations) and Personality types. The experiment was performed on 180 subjects, men and women between 20's and 60's having experience in driving for 6 months at least. Personality types of the subjects were classified by MBTI(Myers-Briggs Type Indicator) GS type and Driver's unsafe acts were measured by KDBQ(Korean Driver Behavior Questionnaire) based on Reason's DBQ(Driver Behavior Questionnaire). The result of experiment showed several facts about the relation. The first is that the drivers of P (Perceiving) type commit more violations and slips than drivers of J(Judging) type. The second is that in the comparison among attitude indexes(EP, EJ, IP, IJ) the drivers of EP(Extroversions - Perceiving) commit more violations than other type drivers. Finally, only men of P(Perceiving) type commits more violations than men of J(Judging). Based on these facts, it is possible to use Personality types as a device to prevent unsafe acts in various fields for driver selection and accident prevention training classified by Personality types etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.5
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• pp.13-22
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• 2015

These days, human behavior (human factor), the main cause of traffic accidents, has drawn more attention. Research on driving behavior based on DBQ(Driver Behavior Questionnaire), the analysis tool of driving behavior, has been conducted actively. In domestic previous studies, their analysis subjects were limited to researchers or military officials, and their analysis methods were based on factor analysis and regression analysis. Therefore, this study tries to find the factors of general drivers' driving behavior that influence risk driving, and to analyze their influential relationship. Regarding study scope, general drivers with driving career were asked to answer DBQ questionnaire, and 300 effective samples were analyzed. In addition, previous studies were investigated to draw the three measurable attributes of DBQ-'Lapse, Mistake, and Violation'-as main factors of traffic accidents, and structural equation model was applied to design risk driving behavior model. To identify the difference between risk driving groups, this study made use of multiple group analysis. The analysis came to the following results: First, according to the examination of the hypothesis that 'Lapse, Mistake, and Violation factors will influence risk driving behavior', all factors were found to be statistically significant. Regarding their level of influence on risk driving behavior, Violation was 0.464, Lapse 0.383, and Mistake 0.158, and thus Violation was analyzed to be the most influential. Secondly, according to the examination of the hypothesis that 'the influence of Lapse, Mistake, and Violation factors on risk driving behavior will be different by risk group', the influence of Lapse on risk driving behavior was found to be different by risk group. It is expected that the study results will be used as a fundamental program to introduce traffic accident prevention program and education that takes violation and lapse into consideration.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.361-370
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• 2017

In this paper, correlation analysis was performed between questionnaire and machine learning based aggressive tendency measurements. this study is part of a aggressive driver detection using machine learning and questionnaire. To collect two types tendency from questionnaire and measurements system, we constructed experiments environments and acquired the data from 30 drivers. In experiment, the machine learning based aggressive tendency measurements system was designed using a driver behavior detection model. And the model was constructed using accelerate and brake position data and hidden markov model method through supervised learning. We performed a correlation analysis between two types tendency using Pearson method. The result was represented to high correlation. The results will be utilize for fusing questionnaire and machine learning. Furthermore, It is verified that the machine learning based aggressive tendency is unique to each driver. The aggressive tendency of driver will be utilized as measurements for advanced driver assistance system such as attention assist, driver identification and anti-theft system.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.603-608
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• 2006

As an important and relatively easy to implement technology for realizing Intelligent Transportation Systems(ITS), Adaptive Cruise Control(ACC) automatically adjusts vehicle speed and distance to a preceding vehicle, thus enhancing driver comfort and safety. One of the key issues associated with ACC development is usability and user acceptance. Control parameters in ACC should be optimized in such a way that the system does not conflict with driving behavior of the driver and further that the driver feels comfortable with ACC. A driving simulator is a comprehensive research tool that can be applied to various human factor studies and vehicle system development in a safe and controlled environment. This study investigated driving behavior with ACC for drivers with different driving styles using the driving simulator. The ACC simulation system was implemented on the simulator and its performance was evaluated first. The Driving Style Questionnaire(DSQ) was used to classify the driving styles of the drivers in the simulator experiment. The experiment results show that, when driving with ACC, preferred headway-time was 1.5 seconds regardless of the driving styles, implying consistency in driving speed and safe distance. However, the lane keeping ability reduced, showing the larger deviation in vehicle lateral position and larger head and eye movement. It is suggested that integration of ACC and lateral control can enhance driver safety and comfort even further.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.161-167
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• 2021

This study was conducted to identify the relationship between the dual task performance and driving behavior of the elderly driver in order to identify whether the dual task can be utilized as a test to screen the driving ability of the elderly driver. We surveyed general information and driving-related information for 32 normal elderly drivers, and evaluated Y-DuCog(Yonsei-Dual task Cognitive screening) and the K-DBQ (Korean-Driving Behavior Questionnaire). As a result of the study, the performance of the dual task using the pegboard task and the animal name speaking showed a significant correlation with the score of the violation domain of K-DBQ. With this study, it was possible to confirm the possibility as a test for discrimination of driving ability.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.83-92
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• 2015

PURPOSES : Traffic accidents and damage due to speeding should be recognized as a problem which harms society and the economy as well as the parties to the accidents. It is time to seek more detailed and concrete customized alternatives than the existing policies for the prevention of traffic accidents. METHODS: In this study, we identified the characteristics driver behavior and psychological factors that lead to speeding, and a study was carried out to verify the causality models developed from the factors we identified. RESULTS : Driving behavior variables have a significant effect on speeding behaviors in order of Lapse, Violation, and Mistake. And the violation which is defined as intentional violation showed the result which supports the research hypothesis as it has the significant effect on speeding intention and behaviors. CONCLUSIONS: The result of this study can be utilized to develop educational problems concerning speeding and previous response with the main objective of eliminating speeding driver behavior.

• Korean Journal of Culture and Social Issue
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• v.12 no.5_spc
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• pp.149-167
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• 2006

Korean society is rapidly changing to aging society comparing the other industrialized countries, however, the studies of elderly driver's driving behavior and accidents are not enough in Korea for elderly driver's accident prevention. This study focused on the elderly driver's psychological effects on elderly driver's driving behavior and traffic accidents; carefulness and aberrant driving behavior. - Elderly driver's traffic accidents The high percentage of elderly driver's accidents occurs in intersections and when turning left. There was a significant difference of the opponent vehicle's speed when left turn, between elderly driver and young driver; the elderly driver choose the higher speed of opponent vehicle than young driver when left turning. This result means that elderly driver has some problems with deciding the vehicle's speed and gap acceptance(Sunyeol Lee, Soonchul Lee, and Inseok Kim, 2006)(Table 1). - Carefulness and driving confidence In order to understand elderly driver's carefulness, this study compared the elderly driver's driving confidence. Driving confidence was consisted of 4 factors; environment of traffic condition, safe driving, driving ability and attention. Elderly driver's confidence was lower than young driver's. Elderly driver in high driving confidence group, showed longer driving history and they were tend to commit violations more frequently than elerly driver in low driving confidence group. Young driver, whose driving confidence level was high answered more driving history, annual mileage, the frequency of committing traffic violation and the experience of accident within lats 5 years(Soonchul Lee, Juseok Oh, Sunjin Park, Soonyeol Lee and Inseok Kim, 2006)(Table 2). This study examined the total time required until deciding to turn left in the no traffic signal intersection between elderly driver and young driver. The result showed that the time of elderly driver was significant longer than young driver(Sunyeol Lee et al, 2006)(Table 3). - Elderly driver's aberrant behavior Driver behavior Questionnaire(DBQ) was measured to understand the aberrant behavior; violation, error and lapse. The tend of aberrant behavior was observed by aging(Sunjin Park, Soonchul Lee, Jonghoi, Kim and Inseok Kim, 2006). Elderly driver's DBQ score was lower than young driver's(Table 4). Elderly and young driver showing longer driving history were in low DBQ score group. Elderly driver had high error score and young driver had high violation score. Young driver's aberrant driving behaviour was associated with annual mileage and the frequency of committing traffic violation. Elderly driver's aberrant driving behaviour was associated with annual mileage and experience of accident. Especially elderly driver whose violation, error and lapse score was high answered more committing experience of accident within last 5 years.