• Korean Journal of Culture and Social Issue
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• v.17 no.3
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• pp.305-320
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• 2011

The objectives of the present research are twofold. First, this research aims to compare the effect of trait characteristics(sensation seeking, social resistance and type-A behavior) with that of driving specific characteristics(driving anger and type-A driving) on problematic driving behavior. Second, the role of life stress as a mediator in the relationships between general trait characteristics and traffic safety index was examined. 1158 licensed commercial vehicle drivers were surveyed and their accident-related records were obtained in this research. Results showed that driving specific characteristics were significant indicators of traffic safety and life stress mediated the relationships between general trait characteristics and traffic safety index. These findings implicate that understanding drivers' driving specific characteristics and their levels of life stress is important to reduce problematic driving behaviors and enhance traffic safety.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.187-198
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• 2011

Researches on children's traffic behavior have only focused on traffic accidents and the number of accidents, and therefore it's been impossible to deal with more broad field of study. In this research we can review the possibility of traffic accidents of children and provide them with traffic education. The goal of this research is to develop a device for measuring possibility of children in terms of traffic behavior. Around 600 elementary students of two schools involved in the pretest with 259 questions and about 3,500 students(junior level 53 questions & senior level 72 questions) involved in practical test. At the result of the research, junior level extracted 4 factors(Lack of behavioral control, Aggressive, Self-regulation, Impulsive Instinct) and 44 questions, and senior level extracted 4 factors(Lack of behavioral control, Depression, Sense-oriented, Aggressive) and 69 questions. We take the gender consideration in separate the groups whether the group has traffic behavioral problem or not. In these series of research, we got the standard score such as junior male student, 63 & female student, 50 and senior male student, 110 & female student, 99.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.213-222
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• 2018

This study was conducted to derive the traffic accident risk index through the recognition of the elderly driver's driving pattern to reduce the traffic accident rate of elderly drivers and to reflect them in the renewal and return policy of driver's license accordingly. First, the traffic accident risk index is defined by analyzing the behavioral characteristics of older drivers to derive the major factors that lead to traffic accidents. Second, we present a method to measure the traffic accident risk index from the driving pattern of the elderly through the smart-phone, the camera and the distance sensor attached to the car. Finally, we derive three thresholds by computer simulation and determine the accident risk from the measured traffic accident risk index as four steps and suggest ways to ensure safe driving of older drivers. It is required to objectively assess the driving ability of an aged driver in accordance with the proposed method, and to induce the driver to reset the driver's license renewal cycle and voluntarily return the driver's license to minimize social costs due to increased traffic accidents.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.723-728
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• 2022

This study is a method for evaluating and quantifying driver's dangerous driving behavior. The quantification method calculates various driving information in real time after starting the vehicle operation such as the time that the vehicle has been continuously driven without a break, overspeed, rapid acceleration, and overspeed driving time. These quantified risk of driving behavior values can be individually provided as a safe driving index, or can be used to objectify the evaluation of a group of drivers on roads, or vehicle groups such as cargo/bus/passenger vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.152-166
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• 2022

This study analyzed the causal relationship among operating characteristics of commercial freight vehicles, dangerous driving behaviors, and traffic accident risk. The study applied the existing accident cause and prevention theory to arrive at this relationship. Data related to working characteristics of driver, driving experience, driving ability, driving psychology, vehicle characteristics (size), dangerous driving behavior, and traffic accidents were collected from 303 commercial freight vehicle drivers. Working characteristics and dangerous driving behavior data are based on the driver's digital driving record. The traffic accident data is based on the insurance accident data reflecting actual traffic accidents. First, a structural equation model was built and verified using the model fitness index. Then, the developed model was used to analyze the causal relationship between multiple independent and dependent variables simultaneously. Four dangerous driving behaviors (sudden deceleration, sudden acceleration, sudden passing, and sudden stop) were found to be highly related to traffic accidents. The results further indicate that it is necessary to establish a safety management policy and intensive management for small-sized freight vehicles, drivers with insufficient driving ability, and drivers with dangerous driving behaviors. Such policy and management are expected to reduce traffic accidents effectively.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.39-50
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• 2007

This study investigated how drivers' cognitive characteristics, such as perception-motor skills and safety-seeking motivation; personal characteristics, such as sensation-seeking disposition coping with physical and social dangers; their self-perceived driving ability; and their normal driving behaviors influence the number of driving violations. 352 drivers participated in the study. MANOVA was performed in order to test the differences in their driving behaviors according to their level of sensation-seeking disposition and driving ability, and Structural Equation Modeling was used to examine the causal relationships among their demographic characteristics, sensation-seeking dispositions, driving ability, driving behaviors and the number of violations. The results indicated that drivers who had higher perception-motor skills seemed to be careful with pedestrians. From the results, drivers who had somewhat higher safety-seeking motivation tended to violate fewer traffic regulations intentionally or accidentally and showed more positive driving behaviors. Furthermore, drivers who had higher perception-motor skills, higher sensation-seeking disposition, and lower safety-seeking motivation had a tendency to violate intentionally more traffic regulations. The older drivers showed driving behaviors that were careful of pedestrians. The drivers who had higher sensation-seeking disposition and longer driving careers violated more traffic regulations, both intentionally and accidentally. Results from LISREL indicated that the predictive variables directly or indirectly influenced on drivers' violation numbers ($x^2$=341.62(p=.00), GFI=.94. RMR=.10).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.291-303
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• 2012

In order to lead safe driving, it is better to provide dynamic and detailed information on how the driver using the relevant road should behave as concerning movements of individual car rather than providing monotone and static information of reducing of speed to unspecified drivers. Assuming road and communication of highway where real-time collection and transfer of information on vehicles and road traffic status is possible, the purpose of this study was to provide real-time safe distance by considering road traffic condition such as road condition and driving condition, travel speed and distance between preceding/following vehicles. We intended to provide basic information about dangerous situation by defining different values of condition based column ($C_{condition}$) in accordance with the road surface condition, based on which Real-time Safety Distance Index(RSDI) is to be calculated comprehensively reflecting speed of preceding and following vehicles, distance between vehicles, vertical alignment and road surface condition on the scope of expression column ($C_n$). We intended to enable the driver to secure safety by providing the calculated Real-time Safety Distance Index (RSDI) so that the driver can intuitively sense and sufficiently cope with a dangerous situation where collision of vehicles may occur. The calculated RSDI value is comprised of 30 unit columns and will be provided to the driver being divided into risk evaluation grades of 3 predetermined steps, 'warning', 'dangerous' and 'normal'.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.160-168
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• 2017

In the past 10 years, the accidents caused by drowsy driving have occupied about 23% of all traffic accidents in Korea expressway network and this rate is the highest one among all accident causes. Unlike other types of accidents caused by speeding and distraction to the road, the accidents by drowsy driving should be managed differently because the drowsiness might not be controlled by human's will. To reduce the number of accidents caused by drowsy driving, researchers previously focused on the spot based analysis. However, what we actually need is a segment (link) and occurring time based analysis, rather than spot based analysis. Hence, this research performs initial effort by adapting link concept in terms of drowsy driving on highway. First of all, we analyze the accidents caused by drowsy in historical accident data along with their road environments. Then, links associate with driving time are analyzed using digital tachograph (DTG) data. To carry this out, negative binomial regression models, which are broadly used in the field, including highway safety manual, are used to define the relationship between the number of traffic accidents on expressway and drivers' behavior derived from DTG. From the results, empirical Bayes (EB) and potential for safety improvement (PSI) analysis are performed for potential risk segments of accident caused by drowsy driving on the future. As the result of traffic accidents caused by drowsy driving, the number of the traffic accidents increases with increase in annual average daily traffic (AADT), the proportion of trucks, the amount of DTG data, the average proportion of speeding over 20km/h, the average proportion of deceleration, and the average proportion of sudden lane-changing.