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.

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.

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.

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.

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.

PURPOSES: This study aims to contribute to a better road environment, which can result in accident reduction from two-wheeled vehicles, by analyzing factors affecting the two-wheeled vehicles’ accident severities in Incheon Metropolitan City. METHODS: In this study, the two-wheeled vehicles’ accident severity was classified into four categories (fatal injury, serious injury, minor injury, and injury report) as a dependent variable, and 97 independent variables out of 14 categories were considered to construct an ordered probit model. To determine the factors affecting accident severity, the statistical package LIMDEP was used. RESULTS: Among the variables used in the analysis, variables related to accident occurrence date (first quarter), region (8-district), accident type (passing the edge of the road of the vehicle for a pedestrian accident, fixed object collision, and overturn of vehicle-only accident), violation type (unobtained safety distance, failure to perform safe driving, violation of intersection driving, and violation of others), the type of road (at the intersection, near the intersection, at the crosswalk, near the crosswalk, etc.), gender of assailant (male), vehicle of victim (pedestrian and motorcycle), and age of victim (under 20) were found to have a statistically significant effect on the severity of the accident. CONCLUSIONS: The variables related to accident type (fixed object collision and overturn of vehicle-only accident), gender of assailant (male), and vehicle of victim (pedestrian and motorcycle) have turned out increasing the accident severity. In addition, accident occurrence for two-wheeled vehicles is more diverse and vulnerable to damage than automobile accidents. Therefore, it is time to recognize the seriousness of two-wheeled vehicle accidents and to improve the environment and systems for safe driving.

OBJECTIVES : Fixed roadside objects are a threat to drivers when their vehicles deviate from the road. Therefore, such roadside objects need to be suitably dealt with to decrease accidents. This study determines the factors affecting the severity of accidents because of fixed roadside objects. METHODS : This study analyzed the crash severity impact of fixed roadside objects by using ordered probit regression as the analysis methodology. In this research, data from 896 traffic accidents reported in the last three years were used. These accidents consisted of sole-car accidents, fixed roadside object accidents, and lane-departure accidents on the national highway of Korea. The accident severity was classified as light injury, severe injury, and death. The factors relating to the road and the driver were collected as independent variables. RESULTS: The result of the analysis showed that the variables of the crash severity impact are the collision location (left side), gender of the driver (female), alcohol use, collision facility (roadside trees, traffic signals, telephone poles), and type of road (rural segments). Additionally, the collision location (left side), gender of the driver (female), alcohol use, collision facility (street trees, traffic signals, telephone poles), and type of road (rural segments), in order of influence, were found to be the factors affecting the crash severity in accidents due to fixed roadside objects. CONCLUSIONS: An alternative solution is urgently required to reduce the crash severity in accidents due to fixed roadside objects. Such a solution can consider the appropriate places to install breakaway devices and energy-absorbing systems.

PURPOSES: The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS: Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

PURPOSES: The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS: To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS: This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including , GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS: Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

오늘날 대 산업분야는 과학 기술의 진보에 따라 비약적인 기술발달을 이루었다. 따 라서, 고객이 요구(Needs)하는 다양한 기능을 구현하기 위해 상당수 부분을 소프트웨 어 중심으로 달성하고 있다. 이렇듯, 과거의 하드웨어 중심의 자동차와 달리 소프트웨 어 중심의 기능 구현이 이행되고 있는 실정이다. 이렇다 보니, 시스템이 보다 복잡해 짐에 따라 시스템을 설계하고 제어하는데 있어서 상당한 어려움이 따르고 있다. 따라 서, 유럽에서는 자동차 분야의 전자제어 장비로 인한 기능안전을 달성하기 위해 ISO26262라는 국제표준을 제정하였다. 국제표준의 제정에 따라 국내 자동차 산업은 차량 시스템을 설계하는데 있어서의 노력, 뿐만 아니라, 기능안전이라는 안전부분을 대비해야하는 상황에 직면하게 되었다. 본 연구에서는 자동차 시스템의 상위 수준의 설계인 개념설계 단계에서 FMEA를 통한 안전성 활동 반영을 통한 하나의 단일화된 개발 방법론을 본 연구를 통해 제시하고자 한다. 따라서, 본 연구를 기반으로 향후 추가 연구를 수행한다면, 국내 자동차 산업, 뿐만 아니라, 대형복합 안전 중시 시스템 으로 확대하여 설계단계에서 안전성을 동시 고려한 시스템 설계 신뢰성 확보를 위해 도움이 될 것으로 기대 된다.

최근 도로교통공단의 교통사고분석시스템의 자료에 의하면, 2014년 교통사고 사망자는 4762명으로 2013년 5092명에서 크게 감소한 것으로 분석되었다. 이는 1978년 이후 가장 낮은 수준으로, 자동차 등록 대수 2천만 시대에 유의미한 성과라고 판단된다. 그러나 우리나라 교통안전 수준은 OECD 최하위 수준으 로 아직 미흡한 실정이다. 2012년 기준 자동차 1만대당 사망자 수는 2.4명으로 OECD 평균 1.1명(영국 0.5명, 미국 1.3명, 일본 0.7명, 독일 0.7명)의 2배가 넘는 수준이다. 사망사고는 총돌 속도와 유의미한 관계가 있을 것으로 판단된다. 2012년 발생한 교통사고를 살펴보면, 사고 직전의 속도가 높을 수록치사율이 증가하는 것으로 분석된다. 또한 제한속도 초과 사망자 수 1,137 명으로 전체 교통사고 사망자 수(5,392명)의 21.1% 차지하는 것으로 분석되며, 도로의 제한속도를 초과 한 경우 일반 사고에 비해 높은 치사율을 나타내고 있다. 하지만 이러한 사고 심각도와 속도와의 관계를 분석한 국내 연구는 미흡한 실정이다. 이에 이 연구의 목적은 합리적인 모형의 정립을 통해 속도와 교통사고 심각도와의 관계를 분석하는데 있다. 또한 도로의 설계 속도를 기준으로 그룹을 분류하여 도로의 설계 속도별로 속도 위반 정도가 사망 사고에 미치는 영향을 분석하고, 나아가 사고 심각도에 영향을 미치는 다른 변수들을 분석하고자 한다. 연구의 목적을 달성하기 위한 분석 모형은 random parameter ordered logit model을 활용하였으며, 분 석에 활용한 자료는 2012년 특별․광역시의 사고 자료 중 단일로에서 발생한 사고 중 속도가 확인 가능한 자료 26,582건이다. 연구의 흐름은 다음과 같다. 첫째, 문헌연구를 통하여 관련 연구 및 분석방법론을 검토한다. 둘째, 설 계 속도에 따라 60km 이하, 60~90km, 100km 이상의 세 그룹을 분류하고, 그룹별 사고 심각도를 분석 한다. 마지막으로 연구의 결과를 정리하고 향후 과제를 제시한다. 연구의 결과, 도로의 설계 속도가 높을수록 제한 속도 위반이 사고 심각도에 높은 영향을 미치는 것으 로 분석되었으며, 2당의 과속 여부보다는 1당의 과속여부가 사고 심각도에 미치는 영향이 큰 것으로 분석 되었다.

Modern systems development becomes more and more complicated due to the need on the ever-increasing capability of the systems. In addition to the complexity issue, safety concern is also increasing since the malfunctions of the systems under development may result in the accidents in both the test and evaluation phase and the operation phase. Those accidents can cause disastrous damages if explosiveness gets involved therein such as in weapon systems development. The subject of this paper is on how to incorporate safety requirements in the design of safety-critical systems. As an approach, a useful system structure using the method of design structure matrix (DSM) is studied while reflecting the need on systems safety. Specifically, the effects of system components failure are analyzed and numerically modeled first. Also, the system components are identified and their interfaces are represented using a component DSM. Combining the results of the failure analysis and the component DSM leads to a modified DSM. By rearranging the resultant DSM, a modular structure is derived with safety requirements incorporated. As a case study, application of the approach is also discussed in the development of a military UAV plane.