• 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.

• 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.

• Bulletin of the Korean Chemical Society
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• v.18 no.6
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• pp.628-631
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• 1997

The preparation and characterization of $Co(dmppz)_2(3,6-dbq)_2$ (dmppz=1,4-dimethylpiperazine; 3,6-dbq=3,6-di-tert-butyl-1,2-quinone) are established. Temperature-dependent magnetic moments (100-400 K), variable-temperature IR, and electronic spectra are presented to show that the title complex exhibits an equilibrium via a catechol to cobalt intramolecular electron transfer. At temperatures below 350 K, the charge distribution of the complex is $Co^Ⅲ(dmppz)_2(3,6-dbsq)(3,6-dbcat)$ (3,6-dbsq=3,6-di-tert-butyl-1,2-semiquinonato; 3,6-dbcat=3,6-di-tert-butylcatecholato) whereas at the temperature beyond 390 K, the complex is predominantly Co^Ⅱ(dmppz)_2(3,6-dbsq)_2$ form in the solid state. At the temperature range of 350-390 K a mixture of Co(Ⅲ) and Co(Ⅱ) redox isomers exist at equilibrium. The transition temperature (Tc) of Co(Ⅲ)/Co(Ⅱ) in solution is approximately 50° lower than that in the solid state. In particular, thermal analysis on solid sample of the complex discloses that the transition for the Co(Ⅲ)/Co(Ⅱ) is accompanied by the change in heat content of 12.30 kcal/mol.

• 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.

• 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.

• 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.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.32-45
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• 2018

This study aims to compare the mutual perception gap on dangerous driving behavior between male and female drivers in multiple aspects, analyze them, and identify factors that trigger this different perception. To understand the mutual perception gap on dangerous driving behavior, DBQ(Driving Behavior Questionnaire) was applied as a rating scale. By applying results into the Co-oreintation model, this study compared the mutual perception gap between male drivers and female drivers and analyze results. In addition, factors that generate the perception gap between both genders were drawn by analyzing factors. This study suggested that objective consistency identified the perception gap that driving behaviors of others were more dangerous between two genders. In addition, subjective consistency was different as both genders assumed that the counterpart's driving behavior takes more risks than their own actual driving behaviors. In regard to the accuracy, men were aware that female driving behaviors are more dangerous than their behaviors. However, female driving behavior assumed by women was consistent with male perception in all factors, which indicated that women perceive men precisely. In addition, results were compared and analyzed in both perspectives of male drivers and female drivers by combining predictive models. Based on these results, both genders perceived that counterpart's driving behavior is more dangerous among both genders.