• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2483-2491
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• 2013

In order to identify and understand the crucial factors to induce traffic accident, causal relationships between diverse factors and traffic accident occurrence have been investigated continuously. It is one of most important issues all over the world to reduce the number of traffic accidents and deaths by them. Korea government is also stepping up their effort to reduce the number of traffic accidents and mitigate the severity of the accidents by establishing various traffic safety strategies. By introducing the five-day work week and increasing concern of leisure activities, the differences of trip characteristics between weekday and weekend is getting greater. According to this, the patterns and crucial factors of traffic accident occurrence in weekend appear differently from those in weekday. This study aims to understand major different factors affecting accident severity between weekday and weekend using 12,042 incident data occurred on freeways of Korea from 2006 to 2011. The model developed in this study estimated relationships among various exogenous factors of traffic accident by each type using SEM(Structural Equation Model). The result provides that road factors are related to the accident severity for weekday model, while environment factors affects on accident severity for weekend.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.1-12
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• 2017

Traffic accidents are caused by a combination of human factors, vehicle factors, and environmental factors. In the case of traffic accidents where rental cars are involved, the possibility and the severity of traffic accidents are expected to be different from those of other traffic accidents due to the unfamiliar environment of the driver. In this study, we developed a model to forecast the severity of rental car accidents by using Naive Bayes classifier for Busan, Gangneung, and Jeju city. In addition, we compared the prediction accuracy performance of two models where one model uses the variables of which statistical significance were verified in a prior study and another model uses the entire available variables. As a result of the comparison, it is shown that the prediction accuracy is higher when using the variables with statistical significance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.577-585
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• 2010

Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.89-100
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• 2008

The purpose of this paper is to analyze the differences between the severity of punishments for traffic laws related offenders and the choice of policy measures with a view to reducing traffic accidents. To this end, government data on the drivers given a sentence of license suspension or revocation were collected and analyzed in terms of sex, age, type of driver's license, driving career, number of traffic laws violations, and number of traffic accidents generated. The statistics of analysis of covariance and tests of significance were used and conducted to compare the effectiveness of punishment for the penalty and the incentive groups. The results showed that the incentive policy measure on the drivers who violate traffic regulations repeatedly is more effective to reduce the number of traffic offenders and traffic accidents.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.26-33
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• 2015

This study suggests systematic procedures to improve safety policies on prevention of industrial accidents associated with industrial machines and devices. Specifically, new method of cause analysis of industrial accidents associated with industrial machines and devices is suggested and the related accident data are re-analyzed. Effectiveness of direct safety regulations such as safety certification, self-declaration of conformity, safety device regulation and safety inspection of industrial machines and devices are also analyzed. Based on those analysis results, transition from the current user-oriented safety device regulation to more balanced direct regulations on both manufacturer and user is suggested. Together with severity and frequency of industrial accidents, unit severity and unit frequency need to be taken into account to further assess the risk associated with a particular industrial machine or device. Balance between safety regulations will be realized by proper adjustment of lists of safety certification and inspection, and certification and inspection standards. This will also guarantee the maximum benefit over cost in such safety regulations.

• The Korean Journal of Emergency Medical Services
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• v.20 no.3
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• pp.7-19
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• 2016

Purpose: The purpose of the study was to investigate the correlation between injury and injury severity score (ISS) in geriatric traffic accident patients transported by 119 emergency medical technicians (EMTs). Methods: The subjects were 240 traffic accident patients over 65 years old transported by 119 rescue services emergency departments in Busan from January 1, 2014 to August 31, 2015. Results: ISS increased in motorcycle traffic accidents (p=.026), truck injuries (p=.005), and head and neck injury (p<.001). Vital signs were evaluated by 119 rescue EMT. ISS increased in cases of unresponsive unconsciousness (p<.001), hypotension (p=.001), and bradycardia (p<.001). The need for bleeding control and dressing by the EMTs increased ISS significantly (p=.022). Conclusion: In the initial evaluation of geriatric traffic patients, ISS can increase in motor cycle accidents and truck injuries. Due to high ISS, patients with head and neck injury, chest injury, hypotension, or tachycardia should be transferred to advanced level hospitals.

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.137-142
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• 2012

Objective: The aim of this study is to investigate the characteristics of industrial accidents in shipbuilding industry. Background: As the accident frequency in shipbuilding industry is higher than those of other industries, it is important to grasp the accident characteristics of shipbuilding industry to reduce the accidents. Method: This paper aggregated some important accident report of the shipbuilding industry including industrial accident analysis of Korean government and drew some important accident characteristics of shipbuilding industry. Results: Accidents in Shipbuilding industry was reviewed in respect of accidents rate, accidents distribution by age, accidents by employed period, accidents severity, accidents type, accidents type by process, accidents caused by object, and hazards in process. Conclusion: Accident related indexes in shipbuilding were much higher than those of whole industry. Application: These results can be used to provide base information for more effective accident preventions in shipbuilding industry.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.13-29
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• 2020

Automobiles have long been an essential part of daily life, but the social costs of car traffic accidents exceed 9% of the national budget of Korea. Hence, it is necessary to establish prevention and response system for car traffic accidents. In order to present a model that can classify and predict the degree of injury in car traffic accidents, we used big data analysis techniques of K-nearest neighbor, logistic regression analysis, naive bayes classifier, decision tree, and ensemble algorithm. The performances of the models were analyzed by using the data on the nationwide traffic accidents over the past three years. In particular, considering the difference in the number of data among the respective injury severity levels, we used down-sampling methods for the group with a large number of samples to enhance the accuracy of the classification of the models and then verified the statistical significance of the models using ANOVA.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.103-114
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• 2011

In this study, we discuss a fatal accident severity model obtained from the analysis of 112 crash sites collected since 2000, and the resulting relationship between fatal accidents and roadway geometry design. From the 720 times computer simulations for improving driving safety, we then reached the following conclusions:. First, the result of cross and frequency-analyses on the car accident sites showed that 43.7% of the accidents occurred on the curved roads, 60.7% on the vertical curve section, 57.2% on the roadways with radius of curvature of 0 to 24m, 83.9% on the roads with superelevation of 0.1 to 2.0% and 49.1% on the one-way 2-lane roads; vehicle types involved are passenger vehicles (33.0%), trucks (20.5%) and buses (14.3%) in order of frequency. The results also show that the superelevation is the most influencing factor for the fatal accidents. Second, employing the Ordered Probit Model (OPM), we developed a severity model for fatal accidents being a function of on various road conditions so as to the damages can be predicted. The proposed model possibly assists the practitioners to predict dangerous roadway segments, and to take appropriate measures in advance. Third, computer simulation runs show that providing adequate superelevation on the segment where a fatal accident occurred could reduce similar fatal accidents by at least 85%. This result indicates that the regulations specified in the Rule for Road Structure and Facility Standard (description and guidelines) should be enhanced to include more specific requirement for providing the superelevation.

• Journal of the Korean Society for Railway
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• v.12 no.2
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• pp.260-266
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• 2009

The theory of risk is applied frequently in analysis of railway accidents. The aim of risk analysis is to search potential causes and contribution factors of accidents by checking the total system of construction field. This paper analyze a pattern and a cause of accident occupied in construction field, calculate risk index considering accident frequency and severity, and then provide the relative risk assessment. Based on this, this paper will provide the methodology of qualitative risk assessment guiding to reach a consistency of risk index with risk assessment.