• International Journal of Highway Engineering
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• v.10 no.4
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• pp.127-138
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• 2008

Vehicles have recently become one of the main factors affecting our quality of life, and the needs of vehicles are still increasing. As a result, the growth of vehicles generate more crashes every year. One main factor for vehicle crashes is uncareful driving behaviors. Especially, drowsy or fatigue driving behaviors explain about 10-20% of the crashes, and they cause serious results because of the delay of response time and the decrease of object-recognition. Therefore, this research conducted real time image processing tests in order to study how cellular phone usages and drowy(or fatigue) drives affect driving behaviors. A vehicle simulator was used for this research, and the faceLAB 4.5 of Seeing Machines for eye image tracking tests using a small camera was installed in the front of the simulator, and normal and drowsy(or fatigue) driving patterns were analyzed.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.105-115
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• 2009

According to the accident statistics published by the National Police Agency in 2007, the number of commercial vehicle(city, suburb and other buses) accidents consumes 3.5 percent of the total number of traffic accidents in this year. Since the commercial vehicles are responsible for not only the drivers but also the passengers, it leads more serious social and economic problems. There have been various forms of systems such as a digital speedometer or a black box to meet the social requirement for reducing traffic accidents and safe driving. however the system based on the data after accident control the driver by analyze dangerous drive behaviors, so there is a limit to control driver in real-time. Also speedometer currently managed provide the driver warning information in real-time, but using only the speed of vehicle and RPM information regardless of actual dangerous drive behaviors, disappear the effectiveness. In this study performed a simulation for drivers in general using a simulator programed with dangerous driving types we had developed in the previous study and judging the types. It'd be more effective system to provide the drivers warning information using weight valued in this study. However in this study is limited to apply weight as a result of simulation of drivers in general in actual situation should be made up the deficit based on information of driving type of actual commercial vehicles.

• 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.

• Korean Journal of Culture and Social Issue
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• v.13 no.3
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• pp.111-125
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• 2007

This study focused on novice drivers. Novice drivers get involved in more traffic accidents than the other drivers because of less driving experience. The aim of this study is to investigate the relationship between driving confidence levels and speeding, drunken driving, and traffic accidents. 192 drivers responded driving confidence levels questionnaire and driving experience items. 'Circumstance Insensibility', 'Unsafe Driving', 'Incautious Driving', and 'Self-efficacy of Driving' had significant relations with speeding in novice divers group. Especially, 'Circumstance Insensibility' showed a significant relation with speeding, drunken driving and traffic accidents. In the result of path analysis, driving confidence levels explained 22% of the speeding, 12% of the drunken driving and 21% of the traffic accidents in novice drivers group. 'Circumstance Insensibility' was most effective for traffic accidents of novice drivers. We verified that 'Self-efficacy of Driving' affects on traffic accidents via speeding.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.89-98
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• 2007

Nowadays, aggressive driving is a common driving behavior and it is raised as a dangerous factor for both drivers and passengers. However, it is hard to find studies on aggressive driving in Korea, and even the definition of aggressive behavior is not clearly explained. In this study, the term "aggressive behavior" is defined based on previous studies, and the significance of several psycho-social factors which affect aggressive driving were verified with the 'habit' factor from the Theory of Planned Behavior (TPB). In the pilot study, domestic drivers reported that aggressive behaviors included speeding, traffic light signal violation, and improper passing (cutting drivers off when passing). In this study, controlling the demographic characteristics of these three aggressive behaviors, the authors explored the relationship of the behaviors with TPB factors such as the habit factor. Consequently, in the case of drivers' intentions for speeding and traffic light signal violations, subjective norm, perceived behavioral controllability, and habit were significant factors. In the case of intentions for improper passing, only perceived behavioral controllability and habit were significant. In speeding behavior and traffic light signal violations, only habit was significant besides intention; however, in improper passing, both perceived behavioral controllability and habit were significant besides intention. The authors also tested an alternative model including TPB and habit factors for three types of aggressive driving. Finally, there are several implications for a possible intervention program for aggressive driving, though there are some limitations of the study.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.85-95
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• 2009

According to the accident statistics published by the National Police Agency in 2007, the number of commercial vehicle accidents explains 3.5 percent of the total number of traffic accidents of the year. Compared to other types of vehicles commercial vehicles may provide more serious damages to both driver himself and passengers. Thus, they generate more serious social and economic problems. There have been various forms of systems such as a digital speedometer or a black box to meet the social requirement for reducing traffic accidents and improving safe driving. However, since the current systems are based on the data often accidents happened, there are lots of limitations to control drivers in real-time. Also, the current speedometers provide drivers with only speeds of vehicles and RPM information regardless of actual dangerous drive behaviors. Therefor, they lack of the effectiveness in terms of safety. In this research, real-time information systems for improving driver safety based on automatic risky driving behaviors, and thresholds to determine risky driving patterns were studied.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.95-105
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• 2007

Speeding and drunken driving make drivers fail to detect hazards and cope with various driving situations. These behaviors also raise the possibility of being involved in traffic accidents and tend to increase the number of fatalities. The authors compared the driving behavior determinants of a rockless drivers group, consisting of individuals who have committed traffic accidents or offended regulations through drunken driving, with a normal drivers group. In the results, the reckless drivers group showed high scores of 'speeding' and 'drunken driving', and they also stated that they had more experiences of speeding, drunken driving and traffic accidents. In the path analysis study, it was found that the impacts of the rockless drivers group's 'risk sensitivity' and 'situational adaptability' on traffic accidents were stronger than those of normal drivers. This means 'risk sensitivity' and 'situational adaptability' can explain the origins of traffic accidents better in the reckless drivers group than accidents of the normal drivers group.

• 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.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.103-109
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• 2012

Digital speedometer which is supposed to provide the basic data for analyzing human factors of drivers has a limitation for human behavior studies of drivers, because it records limited driving information including GPS velocities. Besides, Black Box, which is currently being actively commercialized in the market, records mostly vehicles' risky patterns rather than drivers' behaviors. As a result, it also shows a limit to analyze dangerous driving patterns. This study performed a risky driving study for human factor analysis. This study conducted before and after comparisons for real time warning study using a risky driving judgment device. The analysis was conducted based on Longitudinal acceleration, Lateral acceleration, and Yaw rate of vehicles.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.207-217
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• 2014

Many a number of policies have been tried to reduce auto accidents so far, but it is obvious that further studies are still needed to find a more fundamental and multi-dimensional preventive measure with effect. The National Mental Health Statistics shows that the most profound forms of negative emotions, that is, depression and anxiety, have been increasing, but studies on such a topic are scarce to find. Therefore, we conducted a structural analysis between the negative emotions, including depression and anxiety, of drivers and their driving behaviors using a Structural Equation Modeling(SEM) technique. The review of past literature and studies indicated that not all of human emotions manifest themselves as the ultimate behaviors because they go through emotion regulation Strategies. For this reason, the purpose of this study was set to analyze the structural model developed in this study reflecting the emotion regulation strategies. The result of our analysis showed that the driver's negative emotion had a more significant influence on dangerous driving behaviors than safe ones, and especially, the expressive suppression strategy was found to be the highest factor. Also, the total effect analysis with the negative emotional factors showed that expressive suppression had more significant influence compared to that of cognitive reappraisal. The implication of this study might provide a better understanding on driving behaviors of the drivers and could be used as a fundamental study for future policy development to reduce traffic accidents.