• Journal of Trauma and Injury
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• v.27 no.4
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• pp.101-107
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• 2014

Purpose: Recently, the population of elderly people has been increasing rapidly all over the world. The social activities of the aging population have increased, which has also increased the number of elderly patients injured in traffic accidents. Thus, we analyzed the characteristics of elderly patients involved in traffic accidents. Methods: This study was conducted retrospectively from July 2008 to March 2009 among trauma patients involved in traffic accidents who visited Wonju Severance Christian Hospital. Patients under 18 years of age and pregnant patients were excluded. We divided the patients in two groups, a geriatrics group and an adult group on the basis of an age of 65. We compared the types of traffic accidents, the locations of the accidents, the behaviors of the patients at the times of the accidents, the use of seat-belts, and alcohol consumption between the two groups. We calculated the Revised Trauma Score (RTS), Injury Severity Score (ISS), and Trauma and Injury Severity Score (TRISS) for each group. Results: Total number of the included patients was 903, and the number of elderly patients was 181 (mean age: $71.7{\pm}4.9$ years old). There were no significant differences in the initial vital signs, GCS (Glasgow Coma Scale), and RTS between the two groups. There were differences in the types and the locations of the crashes, the behaviors of the patients at the times of the accidents, the use of seat belts, and alcohol consumption between the two groups (p<0.05). The average ISS of the geriatric group was higher than that of the adult group ($9.66{\pm}10.11$ vs. $6.59{\pm}8.99$, p=0.004). The mortality was higher in the geriatric group (n=17,9%) than in the adult group (n=23,2%) (p=0.004). Conclusion: The numbers of mortalities and surgical procedures were greater within the elderly group than the adult group. The average ISS was higher in the geriatric group than in the adult group. The severity of injuries due to traffic accidents was higher in the geriatric group than it was in the adult group.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1123-1130
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• 2020

This study aims to classify the severity in car crashes using five classification learning models. The dataset used in this study contains 21,013 vehicle crashes, obtained from Korea Expressway Corporation, between the year of 2015-2017 and the LightGBM(Light Gradient Boosting Model) performed well with the highest accuracy. LightGBM, the number of involved vehicles, type of accident, incident location, incident lane type, types of accidents, types of vehicles involved in accidents were shown as priority factors. Based on the results of this model, the establishment of a management strategy for response of highway traffic accident should be presented through a consistent prediction process of accident severity level. This study identifies applicability of Machine Learning Models for Predicting of the Severity of Car Traffic Accidents on a Highway and suggests that various machine learning techniques based on big data that can be used in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.1-7
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• 2015

The traffic accidents in Korea have been increasing every year due to various reasons and simultaneously causing socioeconomic cost at the national level. This study has analyzed the correlation between meteorological factors and the traffic accidents in Seoul during 2013. Especially, we have selected season, rain and temperature among the meteorological factors to identify their significance with the traffic accidents. In addition, analysis of variance, t-test and a multiple regression technique is applied. Major findings from the analyses are discussed at the district point of view, including the different effect of weather condition and the interaction effect of rain and temperature in winter. The results of this study would be useful for developing management strategies to reduce car crashes and injury severity in Seoul.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.141-150
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• 2017

A rapid increase in traffic accidents involving senior vehicle occupants has been an issue in Korea because of the aging of the population occurring at one of the fastest rates in the world; unfortunately, few studies beyond several looking at the effect of senior occupants on the level of accident injury severity can be found in the literature. A Multinomial logit model was estimated with Newton-Raphson algorithm to perform bias-reducing penalized likelihood optimization. Model covariates integral to developing the model were included, but the main focus was on the interaction of seating position and injury to senior vehicle occupants. It was found that the likelihood of an accident resulting in a fatality increased: 2.2 times for the driver seat, 2.7 times for the front passenger seat, and even 6.7 times for the rear seat. A mandatory seatbelt law to be extended to the rear seat needs to pass the assembly as soon as possible, and government, industry, and safety groups should be encouraged to join forces to strongly carry out targeted campaigns for the wearing of seatbelts in all vehicle seats to enhance the safety of senior occupants as well as other occupants who are vulnerable to road traffic accidents.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.143-155
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• 2016

Recently, a massive loss of life and property is occurring in Korea due to traffic accidents, with the rapid increase in cars. For improvement of traffic safety, the Korea Transportation Safety Authority intensively analyzes accident data in local governments with low traffic safety index, performs a field investigation to extract problems and offers local governments improvements for problems, by conducting the 'Special Survey of Actual Conditions of Traffic Safety' each year, starting 2008. But local governments cannot strongly push forward the improvement projects due to the limited budget and the uncertainty of the improvement plan effects. Therefore, this study suggested a model which applied the Utility concept to the AHP theory, in order to efficiently decide a priority of the improvement plans in accident black spots in consideration of the limited budget of local governments. The number of accidents in each spot for improvement and accident severity, traffic volume, pedestrian volume, the improvement project cost and the accident reduction effect were chosen as evaluation factors for deciding a priority, and data about the improvement plan costs and the accident reduction effects, traffic accidents and traffic volume in the spots to undergo the special research on the real condition of traffic accident in the past were collected from the existing studies. Then, regression analysis was carried out and the Utility Curve of each evaluation factor was computed. Based on the AHP analysis findings, this study devised a priority decision method which calculated the weight and the utility function of each evaluation factor and compared the total utility values. The AHP analysis findings showed that among the evaluation factors, accident severity had the biggest importance and it was followed by the improvement plan cost, the number of accidents, the improvement effect, traffic volume and pedestrian volume. The calculated utility function shows a rise in utility, as the variables of the 5 evaluation factors; the number of accidents, accident severity, the improvement plan effect, traffic volume and pedestrian volume increase and a fall in utility, as the variables of the improvement plan cost increase, since the improvement plan cost is included in the budget spent by a local government.

• Journal of Trauma and Injury
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• v.32 no.3
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• pp.143-149
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• 2019

Purpose: No previous study has assessed elderly pedestrian traffic accidents based on a nationwide database. This study aimed to help primary physicians who examine patients in emergency departments to determine and make prompt and accurate treatment decisions. Methods: This study used data from the Emergency Department-based Injury Indepth Surveillance from 2013 to 2017, managed by the Korea Centers for Disease Control and Prevention. Pedestrians aged ${\geq}65years$ were included, and using multivariate logistic regression multiple factors were analyzed to determine their relationship with injury severity. Results: Of 227,695 subjects, 6,498 were included, of whom 2,065 (31.8%) were severely injured. There were more female than male patients in all severity groups. Most accidents occurred in the afternoon and on general roads. In the multivariate analysis, the odds ratio (OR) of injury severity for male pedestrians was 1.165 (95% confidence interval: 1.034-1.313, p=0.012). Older age of patients and the use of ambulances were associated with greater injury severity. The accident time affected the degree of injury severity; i.e., compared to dawn, injury severity increased in the morning (OR: 1.246, p=0.047) and decreased at night (OR: 0.678, p<0.001). A significant difference was noted in the correlation between the type of vehicle causing the accident and the accident severity; i.e., motorcycle accidents had lower severity than bicycle accidents (OR: 0.582, p=0.047). Conclusions: Injury severity was correlated with sex, age, transportation to the ED, TA onset time, and type of vehicle. The study results suggest that injury severity may be positively reflected in initial assessments and overall integrated treatments by physicians and in the related policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.53-73
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• 2023

Although it is mandatory to wear a seat belt that can minimize human injury when traffic accident occurs, the number of traffic accident casualties not wearing seat belts still accounts for a significant proportion.The seat belt wearing detection system for all seats is a system that identifies whether all seat passengers wear a seat belt and encourages their usage, also it can be a useful technical countermeasure. Firstly, this study established the viability of system implementation by assessing the factors influencing the severity of injuries in traffic accidents through the development of an ordered probit model. Analysis results showed that the use of seat belts has statistically significant effects on the severity of traffic accidents, reducing the probability of death or serious injury by 0.054 times in the event of a traffic accident. Secondly, a meta-analysis was conducted based on prior research related to seat belts and injuries in traffic accidents to estimate the expected reduction in accident severity upon the implementation of the system.The analysis of the effect of accident severity reduction revealed that wearing seat belts would lead to a 63.3% decrease in fatal accidents, with the front seats showing a reduction of 75.7% and the rear seats showing a reduction of 58.1% in fatal accidents. Lastly, Using the results of the meta-analysis and traffic accident statistics, the expected decrease in the number of traffic accident casualties with the implementation of the system was derived to analyze the traffic safety effects of the proposed detection system. The analysis demonstrated that with an increase in the adoption rate of the system, the number of casualties in accidents where seat belts were not worn decreased. Specifically, at a system adoption rate of 60%, it is anticipated that the number of fatalities would decrease by more than three times compared to the current scenario. Based on the analysis results, operational strategies for the system were proposed to increase seat belt usage rates and reduce accident severity.

• Journal of the Ergonomics Society of Korea
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• v.35 no.3
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• pp.135-142
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• 2016

Objective: Objective of this study is to provide characteristics of injury frequency and severity by driving condition in large truck-related traffic collisions. Background: Traffic accidents involving large trucks draw a lot of attention in accident prevention and management policies since they bring about severe human and financial damages. Method: In order to identify the major risk factors of accidents by driving condition, 255 recognized traffic accidents by large truck drivers were analyzed in terms of time of the day, road type, and shape of the road. Results: The driving conditions in the results are represented by the following form of combination, "Road Type (Non-expressway or Express) - Shape of Roads (Straight, Curved, Downhill, or Intersection) - Time of Accidents (Day or Night)". In the analysis of injury frequency, Non-expressway-Straight-Day condition was the most frequent one. Meanwhile, Expressway-Curved-Day, Non-expressway-Curved-Night and Non-expressway-Intersection-Night were evaluated as high level in view of injury severity. Also, Expressway-Straight-Night is the driving condition that is the highest in risk among the conditions that have to be managed as grade "High". Non-expressway-Straight-Night, Non-expressway-Downhill-Day, and Non-expressway-Curved-Day are also categorized as grade "High". Conclusion and Application: Safety managers in the fields require basic information on accident prevention that can be easily understood. The research findings will serve as a practical guideline for establishing preventive measures for traffic accidents.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.89-96
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• 2016

According to the promoting policy for bicycle riding, the bicycle road infrastructure in Korea has been widely established. As the number of bicycle rider increases, bicycle traffic accidents also increase year after year. In this paper, we analyze bicycle traffic accident data from 2007 to 2014 which is provided by Road Traffic Authority and present statistical results of bicycle traffic accidents. And also regression analysis is applied to predict the number of daily traffic accidents in Seoul using ASOS(Automated Synoptic Observing System) climate data observed in the Seoul sector which are provided by Korea Meteorological Administration. In addition, decision tree analysis techniques are used to forecast the level of traffic accidents severity. In the analytic results of this research, we expect that it will be helpful to establish the collective policy of bicycle accident data and protective strategy in order to reduce the number of bicycle accidents.

• Journal of Trauma and Injury
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• v.35 no.4
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• pp.232-239
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• 2022

Purpose: The recent increase in electric scooter (e-scooter) use has been accompanied by an increase in injuries from e-scooter-related accidents. Studies have reported that most such injuries are minor, and physicians may therefore underestimate the severity of such injuries. This study investigated the types and severity of injuries caused by isolated e-scooter accidents (i.e., those that did not involve colliding with other cars or falling from heights). Methods: This prospective observational study was conducted from May to December 2021 at Dankook University Hospital tertiary medical center. The demographic data of patients injured in isolated e-scooter-related accidents were collected. All injuries were categorized by body part. Results: Fifty eligible patients visited our emergency department during the study period. Of these, 76% were categorized as nonemergency, and 62% were discharged after initial evaluation and treatment at the emergency department. Another 10% were admitted to the intensive care unit (ICU) and 18% to the ward, with nine patients receiving at least one operation. The average hospital stays were 2.4 days in the ICU and 9 days in the ward. One death occurred due to traumatic brain injury (overall mortality rate, 2%). Multiple fractures of the left third through ninth ribs combined with lung laceration and fractures of T12 and L4 were noted. Conclusions: Various types and severities of injuries can occur in isolated e-scooter accidents. While most such injuries are minor, some will require ICU admission or surgery, and deaths can occur. Physicians should not underestimate the severity of such injuries.