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.

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.

PURPOSES : This study drew factors affecting motorcycle accidents in Seoul by severity using an ordered probit model and aimed to analyze and verify the drawn influence factors. METHODS: As the severity of the accidents could be classified into three types (fatal injury, serious injury and minor injury), this study drew the factors affecting accidents by a comparative analysis employing an ordered probit model, removed the variables that would not secure significance sequentially to construct a model with high explanatory power regarding the factors affecting the severity of motorcycle accidents, and calculated the marginal effect of each factor to understand the degree of each factor’s impact on the severity. First, Model 1 put in all variables; Model 2 was constructed by removing the variables of the road surface conditions that could not meet the level of significance (p=0.608); Model 3 was constructed by removing gender variable (p=0.423); and Model 4 was constructed finally by removing age variable (p=0.320). RESULTS : As a result of an analysis, statistically significant variables were time of occurrence, type of accident, road alignment and motorcycle displacement, and it turned out that the impacts on the severity were in the following order: a road alignment of left downhill, the type of motorcycle-to-vehicle accidents and a road alignment of a flatland on the left. The significance of the models was tested using the likelihood ratio, the level of significance and suitability statistics about them, and as a result of the test, the significance level and suitability of the constructed models were all excellent. In addition, the model accuracy indicating the accuracy of a predicted value compared to that of the value actually observed was 70.3% for minor injury; 70.1% for serious injury; and 68.6% for fatal injury, and the overall accuracy was 70.2%, which was very high. CONCLUSIONS: As a result of an analysis of motorcycle accidents in Seoul through the ordered probit model and the marginal effect, it turned out that their severity increased in nighttime accidents as compared to daytime ones and gradually increased in the order of motorcycleto- vehicle accidents, motorcycle-to-person ones and the ones involving motorcycle only. As a result of an analysis, the severity of accidents in road alignments of left downhill, left flatland and straight downhill increased as compared to those in a road alignment of straight flatland and that the severity of accidents of motorcycles with a displacement larger than 50cc was higher than that of those with a displacement smaller than 50cc.

PURPOSES: The purposes are to analyze the pedestrian accident severity and to develop the accident models by arterial road function. METHODS: To analyze the accident, count data and ordered logit models are utilized in this study. In pursuing the above, this study uses pedestrian accident data from 2007 to 2011 in Cheongju. RESULTS : The main results are as follows. First, daytime, Tue.Wed.Thu., over-speeding, male pedestrian over 65 old are selected as the independent variables to increase pedestrian accident severity. Second, as the accident models of main and minor arterial roads, the negative binomial models are developed, which are analyzed to be statistically significant. Third, such the main variables related to pedestrian accidents as traffic and pedestrian volume, road width, number of exit/entry are adopted in the models. Finally, Such the policy guidelines as the installation of pedestrian fence, speed hump and crosswalks with pedestrian refuge area, designated pedestrian zone, and others are suggested for accident reduction. CONCLUSIONS: This study analyzed the pedestrian accident severity, and developed the negative binomial accident models. The results of this study expected to give some implications to the pedestrian safety improvement in Cheongju.

우리나라의 2012년 교통사고 건수 및 부상자 수는 2011년에 비해 각각 75.1%, 76%의 감소세를 보이고 있으나 사망자 수는 3.1%의 증가세를 보이고 있다. 충북 또한 큰 감소세를 보이고 있는 발생건수 및 부상자 수에 비해 사망자 수는 오히려 5.66%가 증가세를 보이고 있다. 그러나 청주의 경우 사망자 수는 9.26%의 감소세를 보여 전국 및 충북에 비해 양호한 수치를 보이고 있다. 이러한 교통사고의 특성을 파악하고, 그 원인을 분석하여 사고를 예방하기 위한 정책수립에 필요한 다 양한 교통사고모형의 개발이 요구되고 있다. 그러나 개발된 모형의 결과와 실제 사고 자료와의 차이가 있 음에도 불구하고 이의를 제기하거나 원인을 분석한 연구는 매우 부족한 실정이다. 이에 이 연구는 청주시 주간선도로 및 보조간선도로를 대상으로 순서형 로짓 모형을 개발하고, 실제 사고건수가 많이 발생하는 요인별 사고 심각도를 분석하는데 그 목적이 있다. 이 연구는 청주시 주간선 및 보조간선도로의 교통사고자료를 바탕으로 사고특성을 분석하고, 순서형 로짓 모형을 이용하여 사고요인을 분석하여 결과를 도출하는 방식으로 진행되며 변수는 크게 도로환경 요 인, 인적 요인 및 사고유형 요인으로 분류된다. 현재 예상되는 결과는 도로환경 요인 중 야간시간에 비가 오는 날의 사고 심각도가 높을 것으로 예상되며, 인적요인으로는 젊은 남자의 사고 심각도가 높을 것으로 예상된다.

PURPOSES: Because expressway ramps are very complex segments where diverse roadway design elements dynamically change within relatively short length, drivers on ramps are required to drive their cars carefully for safety. Especially, ramps on expressways are designed to guarantee driving at high speed so that the risk and severity of traffic accidents on expressway ramps may be higher and more deadly than other facilities on expressways. Safe deceleration maneuvers are required on off-ramps, whereas safe acceleration maneuvers are necessary on onramps. This difference in required maneuvers may contribute to dissimilar patterns and severity of traffic accidents by ramp types. Therefore, this study was aimed at developing prediction models of the severity of traffic accidents on expressway on- and off-ramps separately in order to consider dissimilar patterns and severity of traffic accidents according to types of ramps. METHODS: Four-year-long traffic accident data between 2007 and 2010 were utilized to distinguish contributing design elements in conjunction with AADT and ramp length. The prediction models were built using the negative binomial regression model consisting of the severity of traffic accident as a dependent variable and contributing design elements as in independent variables. RESULTS: The developed regression models were evaluated using the traffic accident data of the ramps which was not used in building the models by comparing actual and estimated severity of traffic accidents. Conclusively, the average prediction error rates of on-ramps and offramps were 30.5% and 30.8% respectively. CONCLUSIONS: The prediction models for the severity of traffic accidents on expressway on- and off-ramps will be useful in enhancing the safety on expressway ramps as well as developing design guidelines for expressway ramps.

교통사고발생시 사고 심각도에 영향을 미치는 요인과 그 관계를 이해하는 것은 기하구조나 환경 측면에서 교통사고 발생을 예방하고 운전자와 사고 차량의 특성을 이해하는데 도움을 준다. 본 연구에서는 계층 이항 로지스틱모형에 의해 고속도로 교통사고 심각도에 영향을 미치는 요인을 파악하고 영향변수 간 차이를 나타내는 비교위험도(odds ratio)를 도출하였다. 사고 심각도는 인명피해와 차량피해로 구분하여 사망사고모형과 차량완파사고모형을 구축하였다, 종속변수는 사망자 발생과 완파차량 발생 여부이며, 각각 사고-탑승자, 사고-차량의 2수준 계층구조를 적용하였다. 추정 결과 설명변수의 고정효과는 두 모형이 유사한 결과를 보이나 종속변수의 속성에 따라 차별화된 결과를 나타내기도 하였다. 본선과 진출입부에서의 사고가 가장 위험하며, 중앙선 침범과 통행위반, 과속 사고의 상해나 차량 파손 위험도가 높고, 충돌사고와 추돌사고, 화재 사고의 피해가 크다. 사고 심각도는 노면 상태나 시야 조건 등 외부환경에 영향을 받으나 기하구조 조건은 관련이 없다.

최근 고속도로 사고발생량은 감소하고 있는 반면 치사율은 증가하는 추세임에 따라 고속도로의 교통사고 감소 및 안전성 향상을 위한 많은 노력이 요구된다. 특히, 고속도로의 경우 사고다발지점의 등급별 관리기준을 선정하여 관리하고 있어 이에 대한 등급별 사고 영향 인자를 파악하는 것이 세부적으로 필요하다. 따라서 본 연구에서는 우리나라에서 가장 이용률이 높은 경부고속도로를 대상으로 해당구간 내 사고지점에 대한 등급별 데이터를 기준으로 주변환경 요인 중 교통사고에 영향을 미치는 요인을 검토하고, 사고특성을 분석하여 사고등급을 결정지을 수 있는 사고예측모형을 개발하였다. 사고관련 변수 중 고정변수인 기하구조를 기준으로 종속변수와 독립변수의 특성을 고려한 수량화이론 제2류 기법을 이용하여 모형을 구축한 결과, 사고등급에 영향을 미치는 변수로는 평면선형의 경우 승합차종과 차대 사람이, 종단구배는 트레일러 특수차량과 차대 사람, 방책시설은 주시태만과 흐린 날씨가 공통인자로 분석되었다.

본 연구는 교통사고의 발생 유형과 교통사고 심각도(Severity)와의 관계를 규명함으로써 위험유형을 제시하고, 운전자 특성과 교통사고의 관계를 규명하고자 하였다. 교통사고 유형을 여덟 가지로 세분하고, 결과의 객관성 확보를 위해 안전벨트 착용여부를 추가하여 상해정도와의 관계를 분석하였으며, 위험그룹의 분류를 위한 운전자의 특성은 성별, 차종, 연령 등을 대상으로 하였다. 카테고리 자료의 분석을 위하여 로그-선형 모형 및 로짓 모형을 사용하였다. 분석결과 사고유형과 심각도와의 관계에서는 정면충돌 사고와 앞지르기시, 우회전시 사고가 부상 또는 사망사고에 연루될 가능성이 높았다. 위험그룹 분석에서는 20세 미만의 이륜차 운전자, 41세에서 50세까지의 택시 운전자가 가장 위험한 집단으로 분석되었으며 또한 남자보다는 여자가 승용차와 중형화물 등에 관계되었을 때 더 위험한 것으로 분석되었다. 따라서 교통사고 발생시 인명 피해를 줄이기 위해서는 정면충돌 사고와 앞지르기시, 우회전시 발생하는 사고를 줄일 수 있는 방안이 연구되어야 하고, 교통사고 취약계층으로 분석된 위험그룹에 대한 교통안전 교육 및 단속이 강화되어야 할 것이다.

본 연구에서는 경찰청에서 제공한 2006년 전국 37,589개의 보행자 사고 자료에서 나타난 보행자 사고 심각도를 분석했다. 이를 위해 본 연구에서는 보행자사고 심각도에 영향을 미칠 것으로 예상되는 주요 요인을 미리 선정하여, 그 영향을 순서형 로짓 모형(Ordered Logit Model)을 통해 분석했다. 이모형은 사고 심각도와 같이 종속변수가 순서형으로 표시되는 경우 매우 유용한 결과를 제시하는 것으로 알려져 있어서 본 연구에서 사용했다. 본 연구는 다음과 같은 결과를 나타냈다. 첫째, 우리나라 보행자 사고 심각도는 운전자와 보행자로 나타나는 인적요인에서 성별, 나이, 음주여부에 영향을 많이 받는다. 둘째, 기타 요인에는 차량, 도로기하구조, 날씨, 시간대가 포함된다. 셋째, 보행자 사고 심각도는 계절요인과 무관하다. 끝으로, 보행자 사고 심각도 분석을 위해 순서형 로짓 모형을 적용하면 매우 적절한 분석결과를 얻을 수 있다. 결론적으로 본 연구는 우리나라 보행자 사고 심각도는 사람들이 전통적으로 생각하는 것과 같은 방식인 것으로 확인했다. 이 결론은 본 연구에서 사용한 사고자료에 국한한 것이며, 이 결론을 일반화시키려면 추후 연구가 필요하다.