2024년 기준으로 서울특별시의 자전거 이용률과 자전거 도로 인프라가 모두 증가하는 경향을 보이고 있는 반면 자전거 사고건수 및 자전거 사고로 인한 사망자수와 중상자수는 매년 감소하고 있는 추세를 보이고 있어 현행 자전거 관련 안전 정책이 어느 정도 실효성 이 있음을 시사한다. 그러나 중상 및 사망사고는 여전히 지속적으로 발생하고 있어 이에 대한 효과적인 정책이 필요한 상황이지만 현 재 국내 자전거 안전 정책은 사고 예방에만 집중되어 있어 사고의 특성을 종합적으로 반영하지 못한다는 큰 문제점이 있다. 이에 본 연구는 서울특별시 자전거 사고 데이터를 기반으로 자전거 도로 유형별로 서로 다른 값의 가중치를 부여하여 자전거 도로 자체의 특 성을 반영한 사고 심각도를 산출하고, 사고 심각도와 사고 건수를 각각 표준화하여 단위를 통일한 후 이를 통합한 종합적 사고 위험 도 점수를 도출하는 방법론을 사용하였다. 본 연구의 목적은 실제 서울특별시의 공유자전거 사고데이터를 활용하여 자전거 도로 유형 에 따라 사고 심각도와 사고 건수를 종합적으로 고려한 사고 위험도 지표를 개발하는 방법론을 제안하고, 이를 자전거 위험도 분석 및 도로 유형별 맞춤형 안전 대책 마련을 위한 정책적 근거로 제공할 수 있도록 그 기준을 검토하는 것이다. 데이터수집의 경우, 2021 년~2023년 3년간 서울특별시에서 발생한 자전거 교통사고 데이터와 자전거 교통사고가 발생하는 지점의 도로 유형, 경사, 노면상태 등 자전거 도로 인프라 자체적 특성과 자전거 사고 발생 시 기상상황 등 환경적 특성이 포함된 자전거 사고 발생 도로환경요인 데이터를 확보하였다 분석방법론의 경우, 자전거 교통사고에 영향을 미치는 다양한 요인들을 계층적으로 고려하기 위한 방법론인 Hierarchical Modeling을 적용하였으며, 3개의 계층으로 구성된 프레임워크를 구축하여 사고 심각도, 자전거 도로 유형별 사고 심각도를 반영한 공 간 위험도, 종합적 사고 위험도 점수를 체계적으로 도출하였다. Level 1에서는 사고 데이터를 기반으로 사고 심각도를 정량화하고, 도 로 유형에 따른 가중치를 적용하여 사고 심각도를 평가하였다. Level 2에서는 MCAR(Model for Conditional Autoregressive Effects) 모델 을 활용하여 시공간적 상관성을 반영하고, 이를 바탕으로 도로 유형별 사고 심각도를 조정하였다. Level 3에서는 Level 2에서 도출된 도로 유형별 사고 심각도 점수에 사고 발생 빈도를 반영하여 최종적인 종합 사고 위험도 점수를 산출하고, 안전 정책 적용이 시급한 지점을 도출하였다. 향후에는 머신러닝 기반의 예측 모델을 활용하여 도출된 종합적 사고 위험도 점수와 비교 분석할 예정이다.

In this study, we aim to classify personal mobility (PM)-related traffic crash data into four categories: PM-to-vehicle, PM-to-pedestrian, PM-single, and vehicle-to-PM crashes, and analyze the factors influencing the severity of each crash type. To overcome the limitations of existing studies in explaining the impact of independent variables on ordinal dependent variables, a random forest model was combined with the Shapley additive explanation technique. This approach visualizes the influence of independent variables on a dependent variable, providing clearer insights and enhancing interpretability. The analysis of PM traffic accidents, categorized into at-fault, single-vehicle, and victim accidents, revealed distinct key factors for each type. The main contributors to the severity of crashes caused by PM are traffic violations by teenagers and collisions with elderly pedestrians. Single-vehicle accidents were predominantly caused by overturn incidents, with inadequate driving skills among PM users aged 40 years and older, and significantly increasing severity. Victim accidents primarily occur at intersections, where the behavior of the at-fault driver and age of the PM user are critical factors influencing the severity. We identified various factors influencing the severity of PM crashes by type, highlighting the need for tailored policy measures. Proposed policies include physically separating bicycle–pedestrian shared spaces and strictly regulating illegal PM sidewalk riding, introducing PM licenses for teenagers to ensure compliance with traffic rules, and implementing regular safety education programs for all age groups. Although this study applied a new analytical technique, it relied on limited crash data, thus limiting the results to estimates.

Background: Hallux valgus (HV) is a common foot deformity in which the great toe deviates laterally and the first metatarsal deviates medially, leading to pain, discomfort, and reduced mobility. HV severity is typically assessed using the hallux valgus angle (HVA) and intermetatarsal angle (IMA). Objects: This study aimed to explore how changes in skeletal, muscular, and functional variables correlate with HV severity and to provide evidence for more integrated treatment approaches. Methods: Sixty volunteers with mild to moderate bilateral HV (HVA 15–40 degrees) participated. The measurements included HVA and IMA via radiography, abductor hallucis muscle (AbdH) cross-sectional area (CSA) and tone using ultrasound and Myoton PRO, range of motion (ROM) of the ankle and great toe metatarsophalangeal (MTP) joint with a goniometer, and plantar pressure during gait with a Zebris FDM system. Pearson’s correlation coefficient was used for the statistical analysis. Results: An Increased HVA was associated with a higher IMA (r = 0.858, p < 0.05). The HVA was inversely related to the AbdH CSA (r = –0.337, p < 0.05) and muscle tone (r = –0.889, p < 0.01). With increasing HVA, dorsiflexion ROM of the ankle (r = –0.307, p < 0.01) and both flexion (r = –0.197, p < 0.05) and extension (r=-0.182, p<0.05) ROM of the great toe MTP joint decreased. Conversely, ankle plantar flexion ROM increased with the HVA (r = 0.312, p < 0.01). Additionally, plantar pressure increased in the second metatarsal areas (r = 0.457, p < 0.05) a with higher HVA. Conclusion: This study demonstrates significant correlations between HV severity and various biomechanical factors, highlighting the need for comprehensive treatment strategies. While stretching the adductor hallucis muscle and strengthening the AbdH have been widely recognized interventions for HV, our findings provide evidence that ROM exercises for the ankle and the MTP joint of the great toe are also critical components of a physical therapy program for managing HV. Longitudinal studies are required to assess the effectiveness of these approaches.

This study aimed to investigate the factors affecting the severity of taxi traffic accidents at intersections in Busan and propose measures to improve traffic safety. This study collected data on taxi traffic accidents that occurred at intersections in the Metropolitan City of Busan during the past 3 years (2020–2022) from Traffic Accident Analysis System(TAAS) and road views, and analyzed factors affecting their severity by employing an ordered probit model. The severity of taxi traffic accidents worsened with violations of (among others) traffic signals and pedestrian protection during January, April, and September. In addition, when a major street was operated with a permissive left turn, the severity of taxi traffic accidents worsened. Measures to improve traffic safety suggested in this study included safety education that focused on particular violations for taxi drivers, mandatory education for transport employees in an experiential format, support of video storage devices for driving records, policy establishment for the promotion and certification of good and bad driving videos, time adjustment of joint safety management inspection, and left-turn signal operation with an unprotected system and P-turn guidance.

PURPOSES : This study aimed to investigate the factors affecting the severity of traffic crashes caused by personal mobility (PM) devices compared with those involving victims. METHODS : Traffic crashes involving PM devices were used to build a non-parametric statistical model using a classification tree. Based on the results, the factors influencing both at-fault and victim-related crashes caused by PM devices were analyzed. The factors affecting accident severity were also compared. RESULTS : Common factors affecting the severity of traffic crashes involving both perpetrators and victims using PM devices include occurrences at intersections, crosswalks at intersections, single roads, and inside tunnels. Traffic law violations by PM device users (perpetrators) influence the severity of crashes. Meanwhile, factors such as the behavior of perpetrators using other modes of transportation, rear-end collisions, road geometry, and weather conditions affect the severity of crashes where PM device users are the victims. CONCLUSIONS : To reduce the severity of traffic crashes involving PM devices, it is essential to extend the length of physically separated shared paths for cyclists and pedestrians, actively enforce laws to prevent violations by PM device users, and provide systematic and regular educational programs to ensure safe driving practices among PM device users.

PURPOSES : This study aimed to derive the factors that contribute to crash severity in mixed traffic situations and suggest policy implications for enhancing traffic safety related to these contributing factors. METHODS : California autonomous vehicle (AV) accident reports and Google Maps based on accident location were used to identify potential accident severity-contributing factors. A decision tree analysis was adopted to derive the crash severity analyses. The 24 candidate variables that affected crash severity were used as the decision tree input variables, with the output being the crash severity categorized as high, medium, and low. RESULTS : The crash severity contributing factor results showed that the number of lanes, speed limit, bus stop, AV traveling straight, AV turning left, rightmost dedicated lane, and nighttime conditions are variables that affect crash severity. In particular, the speed limit was found to be a factor that caused serious crashes, suggesting that the AV driving speed is closely related to crash severity. Therefore, a speed management strategy for mixed traffic situations is proposed to decrease crash severity and enhance traffic safety. CONCLUSIONS : This paper presents policy implications for reducing accidents caused by autonomous and manual vehicle interactions in terms of engineering, education, enforcement, and governance. The findings of this study are expected to serve as a basis for preparing preventive measures against AV-related accidents.

The Occupational Safety and Health Act (OSHA) aims to maintain and promote the safety and health of workers. Additionally, violations of the act can result in imprisonment or fines, depending on the severity of the offense. This study examines whether the severity of OSHA violations is proportional to the size of the fines imposed. There are 120 items subject to fines, with penalties ranging from a minimum of 50,000 won to a maximum of 30 million won. To assess the severity of these items, pairwise comparisons were conducted, and the results were expressed numerically. In summary, no significant correlation was found between the severity of violations and the amount of the fines. Therefore, this study proposes calculating fines based on the severity of violations. In many small companies, resources (e.g., budget and manpower) are limited. Thus, greater attentions tend to be directed toward addressing items with higher fines. Consequently, aligning the severity of legal violations with the size of the fines may contribute to improving the industrial safety.

This study aims to enhance the accuracy of severity classification by examining the usage patterns and characteristics of emergency department visits. It focuses on adult and elderly patients who visited a public hospital in Seoul. This descriptive study retrospectively reviewed the electronic medical records of patients who visited the emergency department of a public hospital between November and December 2023. The total number of participants was 1,033, with 46.4% (n=479) being elderly and 53.6% (n=554) being adults. The chief complaints of the participants were as follows: for the elderly, nervous system symptoms at 8.2% (n=85) and digestive symptoms at 7.5% (n=77) were the most common, while for adults, gastrointestinal symptoms at 11.0% (n=114) and trauma at 8.6% (n=89) were more prevalent. In the case of the elderly, patients classified as urgent accounted for the highest percentage at 23.9% (n=247), while for adults, non-emergency were more prevalent at 32.2% (n=333). The initial severity classification error rate for elderly patients in the urgent was 3.8%, indicating that the suitability of KTAS for elderly patients with high severity was low. To minimize severity classification errors and enhance KTAS accuracy, it's essential to address its current limitation of only classifying adults and children separately by developing a KTAS classification system that reflects the diverse characteristics of elderly patients.

지형적인 이질성이 심한 강원도, 경상북도에 집중되고 있는 대형 산불을 관리하기 위해서는 위성 영상을 활용하여 효율적이고 신속한 피해 평가를 통한 의사 결정 과정이 필수적이다. 이에 본 연구는 2022년 3월 5일에 강원도 강릉 및 동해에서 발화하여 3월 8일 19시경 진화된 대형 산불을 대상으로, dNBR을 활용한 산불 심각도 산정과 등급에 영향을 미치는 환경요인을 도출하고자 하였다. 환경요인으로는 식생 또는 연료 유형을 대표하는 정규식생지수, 수종을 구분한 임상도, 수분함양을 나타내는 정규수분지수, 지형과 관련해서는 DEM 등을 수치화한 후 산불 심각도와의 상관 관계를 분석하였다. 산불 심각도는 산불 피해 없음(Unbured)이 52.4%로 가장 넓었고, 심각도 낮음 42.9%, 심각도 보통-낮음 4.3%, 심각도 보통-높음 0.4% 순이었다. 환경요인의 경우 dNDVI, dNDWI와는 음의 상관관계를, 경사도와 는 양의 상관관계를 나타내었다. 식생과 관련해서는 산불 심각도에 영향을 미치는 것으로 분석된 dNDVI, dNDWI, 경사도 모두에서 침엽수, 활엽수, 기타의 집단간 차이가 p-value < 2.2e-16로 유의미한 것으로 분석되었다. 특히, 침엽수 와 활엽수의 차이가 명확하였는데, 강원도 지역에서 우점종인 소나무를 비롯하여 잣나무, 리기다소나무, 곰솔 등의 산불 심각도가 높아 침엽수가 활엽수에 비해 피해를 받는 것이 확인되었다.

PURPOSES : The main purpose of this study is to identify directions for improvement of triangular islands installation warrants through analysis of the characteristics of crashes and severity with and without triangular islands on intersections. METHODS : The data was collected by referring to the literature and analyzed using statistical analysis tools. First, an independence test analyzed whether statistically significant differences existed between crashes depending on the installation of triangular islands. As a result of the analysis, individual prediction models were developed for cases with significant differences. In addition, each crash factor was derived by comparison with each model. RESULTS : Significant differences appeared in the "crash frequency of serious or fatal" and "crash severity" owing to the installation of triangular islands. As a result of comparing crash factors through the individual models, it was derived that the differences were dependent on the installation of the triangular islands. CONCLUSIONS : As a result of reviewing previous studies, it is found that improving the installation warrants of triangular islands is reasonable. Through this study, the need to consider the volume and composition ratio of right-turn vehicles when installing a triangular island was also derived; these results also need to be referred to when improving the triangular island installation warrants.

PURPOSES : In this study, the main factors affecting the severity of traffic accidents among elderly drivers were reviewed, and accident factors with a high accident risk were analyzed. This provided basic data for preparing a traffic safety system for elderly drivers and establishing policies. METHODS : Based on machine learning, the major factors influencing accident severity (from the analysis of traffic accident data for elderly drivers) were analyzed and compared with existing statistical analysis results. The machine learning algorithm used the Scikit-learn library and Python 3.8. A hyperparameter optimization process was performed to improve the safety and accuracy of the model. To establish the optimal state of the model, the hyperparameters were set (K = 5) using K-fold cross-validation. The hyperparameter search applied the most widely utilized grid search method, and the performance evaluation derived the optimal hyperparameter value using neutral squared error indicators. RESULTS : The traffic laws, road sections of traffic accidents, and time zones of accidents were analyzed for accidents involving elderly drivers in Daejeon Metropolitan City, and the importance of the variables was examined. For the analysis, a linear regression model, machine learning-based decision tree, and random forest model were used, and based on the root mean square error, the random forest accuracy performance was found to be the best. Ultimately, 18 variables were analyzed, including traffic violations, accident time zones, and road types. The variables influencing the accident severity were the speed, signal violation, intersection section, late-night driving, and pedestrian protection violation, with the relative importance of the variables in the order of speed (0.3490966), signal violation (0.285967), and late-night driving (0.173108). These can be seen as variables related to the expansion of life damage owing to physical aging and reduced judgment abilities arising from decreases in cognitive function. CONCLUSIONS : Restricting the driving of the elderly on the expressway and at night is reasonable, but specific standards for driving restrictions should be prepared based on individual driving capabilities.

Background: Pronated foot posture (PFP) contributes to excessive dynamic knee valgus (DKV). Although foot orthoses such as medial arch support (MAS) are widely and easily used in clinical practice and sports, few studies have investigated the effect of MAS on the improvement of DKV during stair descent in individuals with a PFP. Moreover, no studies reported the degree of improvement in DKV according to the severity of PFP when MAS was applied. Objects: This study aimed to examine the immediate effect of MAS on DKV during stair descent and determine the correlation between navicular drop distance and changes in DKV when MAS is applied. Methods: Twenty individuals with a PFP (15 males and five females) participated in this study. The navicular drop test was used to measure PFP severity. The frontal plane projection angle (FPPA) was calculated under two conditions, with and without MAS application, using 2-dimensional video analysis. Results: During stair descent, the FPPA with MAS (173.1° ± 4.7°) was significantly greater than that without MAS (164.8° ± 5.8°) (p < 0.05). There was also a significant correlation between the navicular drop distance and improvement in the FPPA when MAS was applied (r = 0.453, p = 0.045). Conclusion: MAS application can affect the decrease in DKV during stair descent. In addition, MAS application should be considered to improve the knee alignment for individuals with greater navicular drop distance.

The severity of acute pancreatitis (AP) is classified into mild, moderately severe, and severe, considering the presence and duration of organ failure and local complications. Since patients with AP show a large difference in mortality and morbidity according to AP severity, evaluation of the severity of patients with AP in the early stage is important for predicting the prognosis and determining treatment plans including transfer to the intensive care unit or advanced facilities. In order to evaluate the initial severity of AP, it is necessary to confirm the presence of organ failure and objective evaluation using imaging or clinical examinations. In this guideline, it is recommended that evaluation using various severity indices such as bedside index for severity in acute pancreatitis (BISAP), systemic inflammatory response syndrome (SIRS), and acute physiology and chronic health evaluation (APACHE)-II scores be considered.

급성 췌장염은 사망에 이를 수 있는 질환으로, 발병 초기 2주 내 기관부전으로 인한 사망과 이후 몇 주 혹은 몇 달 후 기관부전과 국소 합병증의 문제로 사망하는 두 개의 국면을 보인다. 중증 급성 췌장염을 예측하기 위한 다양한 임상 평가 및 다원적 평가 척도, 영상 검사 및 분자 혈청 검사가 있으나, 현재 가장 우월하게 급성 췌장염의 중증도를 예측하는 척도와 검사가 없고, 사망의 시기를 구분하지 않는 경우가 대부분으로 향후 대규모 연구를 통해 사망의 시기 및 예후를 예측하는 평가 척도의 개발이 필요하다.

PURPOSES : For vehicle-alone accidents with a high mortality rate, it is necessary to analyze the factors influencing the severity of roadside fixed-object traffic accidents. METHODS : A total of 313 roadside fixed obstacle traffic accidents, variables related to fixed obstacles, and variables related to road geometry were collected. The estimation model was constructed with data collected using an ordinal probit regression model. RESULTS : Piers, vertical slopes, and distances between roads and objects were the primary causes of increased accident severity. CONCLUSIONS : Countermeasures, such as object removal, relocation, clear zones, frangibles, breakaway poles, etc., are required for accident-prone or dangerous points.

Service failure of high severity can lead to high recovery satisfaction when recovery efforts are seen very fair. Customers satisfied with recovery efforts and displaying high attachment anxiety will continue to repurchase. Attachment avoidance did not have an impact on the behavioural intentions and neither did the brand authenticity perception.

PURPOSES: The purpose of this study is to investigate factors that affect the severity of children’s traffic accidents using the ordered probit model, and to contribute to a safer road environment for children. METHODS: This study used children’s traffic accident data during the last four years in the Incheon Metropolitan area. At this point, to analyze only the direct damage caused to children, the analysis was made of accidents where the victim was under 13 years old. Data from a total of 1,110 accidents was collected. When the model was constructed, as it was judged that there could be a difference in factors affecting accident occurrence depending on the zone characteristics, the model was divided into school and non-school zones. RESULTS: The accident content (severity) is divided into four stages (fatal injury, serious injury, minor injury and injury report) to construct the order-typed probit model. For the analysis, 65 variables of 17 categories were included in the model. The statistical package STATA 13.1 was used to analyze the variables affecting the accident severity with a confidence level of 90% (α·=0.1). Consequently, a total of 15 variables were found to have a statistically significant effect on accident severity in a school zone. In contrast, a total of 22 variables were found to have a statistically significant effect on accident severity in non-school zones. Four variables (daytime, weekday, victim age, intersection) were significant in both models. CONCLUSIONS: Among the significant variables found in school zones, signal violation and type of vehicle (line bus, rent car, bus, business other vehicles) had a relatively greater effect on the accident severity than the other variables. In non-school zones, eight variables comprising daytime, head-on collision, crossing, over-speed, gender of victim (male), victim age, type of vehicle (construction machinery), driver age (50-59) were found to be significant variables. In conclusion, as well as eliminating factors that can lead to accident reductions, it is necessary to consider zone characteristics to reduce the severity of children’s accidents and promote children’s traffic safety.