• Journal of the Korean Society of Safety
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• v.21 no.2 s.74
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• pp.128-137
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• 2006

Traffic accidents occur due to complex influences of transportation companies, drivers, and road environment. This study found that education and surroundings for transportation companies, driving habits of drivers, and road safety facilities and accessory facilities were main factors that affected strongly traffic accidents. Also, it found that driving habits of drivers could affect accidents heavily more than two other factors. Road safety and accessory facilities were analysed that they affected traffic accidents independently with transportation companies and their own drivers. Therefore, in order to achieve a traffic accident prevention as our main target, those companies need to produce atmosphere that their own drivers can have safety awareness, and related institutions for the above target should run parallel with policy assistance and strict traffic enforcement. In the end, this study suggests that transportation companies should secure manpower wholly being charged with traffic safety and financial resources investing in it.

• Journal of the Korean Society of Safety
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• v.28 no.6
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• pp.84-89
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• 2013

The main causes of traffic accidents can be classified by 3 factors - human error, vehicle deficiency and road environmental problem and most accidents occurs not only 1 factor but combination of 2 or 3-factors. Among these factors, road environmental factor is the most important factor due to influence the behavior of cars and road users and road environmental factor affects 30% of total accidents approximately. The 5 years traffic accidents data analyzed to verify the accidents severity on Korea National Highways. In order to analyze the severity, Ordered Probit Model was used. As a independent variables of this model the number of lane, neighbor road environments, sight distance, vertical grade, lane width, shoulder width and traffic volume were used and as a dependent variables the minor injuries, serious injuries and fatalities were used. Research results shows that sight distance and lane width are identified as significant factors for the traffic accident severity and lesser sight distance and lane width shows greater traffic accident severity.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.35-62
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• 1995

Traffic has a very important function but has caused such social problems as traffic congestion parking and traffic accidents in metropolitan areas. It is difficult to examine the causes of traffic accidents related to human life, which occur by human, vehicle and environmental factors. But human factor is the only measure requlating these factors together an analyzing factors influencing establishment of counterplan of traffic accidents. Consequently , this study employs the principal component analysis and stepwise multiple regression analysis to estimate the characteristics and influential factors of traffic accidents and defines the typical patterns of happening lots of traffic accidents. Accordingly, this study establishes an acknowledgement model of the causes and preference model of the counterplan of traffic accidents using Multi-Dimension Preference(MDPREF) method.

• 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.

• Journal of Korean Society of Transportation
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• v.8 no.1
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• pp.73-88
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• 1990

This study aims to develop a traffic accident forecasting model using the data, which are based on the past accidents in Korea. The regression analysis was used in conjuction with the variables of the traffic accidents and social behaviours. The objectives of this study are as follows; 1. The number of behicles has given a strong affect to increase the traffic accidents in Korea since a factor of vehicles has shown 86% over of total accidents. 2. The forecasting model regarding the traffic accidents, deaths and injuries, which was formulated for this study, proved to be useful in light of the results of the regression diagnostics. 3. It is expected that the traffic accidents in Korea in 1991 may take place as follows on condition that the traffic environment would worsen ; 274,000 cases of accidents with 13,600 deaths and 367,000 injuries, in 1994, 451,000 cases with 24,900 deaths and 71,500 injuries respectively.

• The Korean Journal of Emergency Medical Services
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• v.22 no.1
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• pp.35-47
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• 2018

Purpose: The purpose of this study was to investigate both the occurrence status of emergency vehicles traffic accidents and contents of the experiences of emergency medical technicians (EMTs) in fire station. Methods: A self-reported questionnaire was completed by 451 EMTs in fire stations in 6 cities provinces from February 9, 2017 to February 27, 2017. Results: Of 451 EMTs, 207 (45.9%) had traffic accidents experience. Regarding environment-related features, results indicated hour (12~18 hours), place (national highway), traffic flow (smooth), weather (clear), season (winter), and day (Friday). Regarding correlation analysis of differences in the number of ambulance traffic accidents pursuant to general features of accident-experienced drivers as a human factor, there were no significant differences in recruitment, driving careers of regular cars, driving careers of fire engines, and class but there were significant differences in fire-fighting careers. Accident experience in the group with careers over 6 years and less than 10 years higher than in the other groups. Conclusion: Efforts to expand fire engine driving education programs for the prevention of traffic accidents involving 119 emergency vehicles are required.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.223-236
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• 2015

This study dealt with regional characteristics in car insurance for reduction of traffic accidents. The objective was to establish scientifically the verification procedure in the application of regional auto insurance rate. To specify the objective, this study conducts the correlation analysis between factors which are various in each local traffic environment and the loss ratio in automobile insurance. Also, this provides a correlation and a modal in loss ratio, classifying human factors in locality in major cause result from traffic accident. Based on the results, this brings up the problems with applying a uniform criterion for automobile insurance rate although various factors have effect on traffic accidents in locality. Therefore, what stands out most from this study is that a policy on automobile insurance applied to regional factor should be introduced.

• Journal of the Korean Society of Safety
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• v.27 no.3
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• pp.153-160
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• 2012

Various social problems such as traffic congestion, car accidents and environmental problems(air pollution, noises etc.) have been happening in the Seoul metropolitan area that has the car oriented traffic system providing cars continuously. Along with this, the financial burden caused by current oil price anxiety made paradigm shift from caroriented to public transportation-oriented. Its typical example is an arterial branch bus system changing(bus lane through the center of main road) started in Seoul in July, 2004. But study on safety analysis of bus lane and characteristic of accidents are not sufficient enough to now. The bus lanes are expanded to provide roads for better traffic operation and accidents between buses and pedestrians or ordinary vehicles are considered main problems. This study divided each bus route of median bus lane(bus-only lane through the center of main roads) and bus lane at roadside by intersection and collected and analysed data about influence variables of bus accidents chosen in each section. We constructed a logistic model using collected data. As a result, bus lane at roadside are used by both buses and other kinds of vehicles differently from median bus lane and showed such characteristic in accident influence. Therefore access management to factors causing conflict and improvement of operation management are required. In case of median bus lane, the more buses moving general vehicle lane and traffic volume of section were, the more accidents happened. In case that stop line of center lane is not backward, view blocking of vehicles turning left caused accidents.

• International Journal of Highway Engineering
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• v.17 no.3
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• pp.107-115
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• 2015

PURPOSES : The purposes of this study are to compare the day and night characteristics and to develop the models of traffic accidents. in Rural Signalized Intersections METHODS : To develop day and night traffic accident models using the Negative Binomial Model, which was constructed for 156 signalized intersections of rural areas, through field investigations and casualty data from the National Police Agency. RESULTS : Among a total of 17 variances, the daytime traffic accident estimate models identified a total of 9 influence factors of traffic accidents. In the case of nighttime traffic accident models, 11 influence factors of traffic accidents were identified. CONCLUSIONS : By comparing the two models, it was determined that the number of main roads was an independent factor for daytime accidents. For nighttime accidents, several factors were independently involved, including the number of entrances to sub-roads, whether left turn lanes existed in major roads, the distances of pedestrian crossings to main roads and sub-roads, lighting facilities, and others. It was apparent that if the same situation arises, the probability of an accident occurring at night is higher than during the day because the speed of travel through intersections in rural areas is somewhat higher at night than during the day.