• 대한산업공학회지
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• 제26권4호
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• pp.354-362
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• 2000

Increasing amount of road tragic in 90's has drawn much attention in Korea due to its influence on safety problems. Various types of data analyses are done in order to analyze the relationship between the severity of road traffic accident and driving conditions based on traffic accident records. Accurate results of such accident data analysis can provide crucial information for road accident prevention policy. In this paper, we apply several data fusion, ensemble and clustering algorithms in an effort to increase the accuracy of individual classifiers for the accident severity. An empirical study results indicated that clustering works best for road traffic accident classification in Korea.

• 한국안전학회지
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• 제32권6호
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• pp.143-149
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• 2017

According to traffic accidents statistics, the number of fatalities, injuries and the rate of increase of traffic accidents have been decreasing over last 5-years. The fatality rate is 1.9 for total accidents but the fatality rate for single vehicle accidents shows a 7.9, which is 4 times greater than the average for all accidents. Single vehicle accidents, usually occur as a vehicle impacts a fixed objects on the roadside as the vehicle runs-off from the road. However, few researches have been conducted considering the accident severity of single vehicle accidents which impact to the fixed objects on the road. The single vehicle accident is directly related to the composition of road cross section, (since it is the required the minimum width of a road for all run-off-the-road vehicles to recover or come to a safe stop). Therefore, this study analyzes the influence of road cross section on traffic accidents to find out the severity of single vehicle accident. To analyze the road elements which are related to the accident severity, the Ordered Probit Model was used. As variables, the element of road cross section such as the radius(m), vertical curve(%), cross sectional grade(%), road width(m). number of climbing lane, median, and curb, were used (as was the 3-years of accidents data). This study found out that cross slope(%), road width(m), and the number of climbing lane are related to the severity of accident. The result of this study could be expected to improve the road safety and to be used as the base data for further road safety research.

• 한국산업융합학회 논문집
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• 제9권4호
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• pp.285-291
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• 2006

A traffic accident is occurred by unbalance of reciprocal action of driver, vehicle and road conditions. To prevent the traffic accident, rapid and perfect road improvement is needed. But most of road improvement plans have insufficient budget. So decision maker has to determine the priority to invest. A model in this study, analyzing the effect of road conditions to the traffic accident, helps to decide the priority in road improvement. This study considered five danger indices ; 1) traffic volume, 2) speed variance, 3) vehicle mixing rate, 4) curved line radius, and 5) difference between design speed and running speed. Danger rate composed by five indices can be a scale of priority of improvement. The model in this study didn't consider all of factors about traffic accident. But this study can propose the methodology for traffic safety policy. For deriving the model, this study used data from highways in Korea and United States. Therefore the model has to apply the highways only.

• 한국ITS학회 논문지
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• 제11권6호
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• pp.133-144
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• 2012

본 연구는 교통사고자료를 이용하여 고령자 집단과 비고령자 집단 간의 교통사고요인을 파악하여 각 요인들이 교통사고 심각도에 미치는 영향의 크기를 분석하였다. 나이에 의해 구분된 고령자와 비고령자 집단을 교통사고자료를 이용한 통계학적 방법에 의해 재분류하였으며, 교통사고 심각도에 미치는 영향요인을 분석하기 위해 심각도를 종속변수로 두고, 교통시설, 도로환경, 개인별특성에서 17개 독립변수로 정하여 순서형 로짓모형으로 분석하였다. 고령자 집단과 비고령자 집단의 교통사고 영향요인을 분석하여 비교한 결과, 사고 당사자의 연령뿐만 아니라, 사고유형이나 운전자 개인의 특성, 도로환경도 교통사고에 영향을 미치고 있음이 나타났다. 또한 고령자 집단과 비고령자 집단은 교통사고 심각도에 미치는 영향변수의 종류와 크기가 각각 다른 것으로 나타났다. 이는 각 집단의 개인적 특성에 적합한 교통시설이 개선된다면 교통사고의 심각도를 줄일 수 있음을 의미하는 것이라 할 수 있다.

• 산업경영시스템학회지
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• 제45권2호
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• pp.20-29
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• 2022

This study intends to present a traffic node-based and link-based accident prediction models using XGBoost which is very excellent in performance among machine learning models, and to develop those models with sustainability and scalability. Also, we intend to present those models which predict the number of annual traffic accidents based on road types, weather conditions, and traffic information using XGBoost. To this end, data sets were constructed by collecting and preprocessing traffic accident information, road information, weather information, and traffic information. The SHAP method was used to identify the variables affecting the number of traffic accidents. The five main variables of the traffic node-based accident prediction model were snow cover, precipitation, the number of entering lanes and connected links, and slow speed. Otherwise, those of the traffic link-based accident prediction model were snow cover, precipitation, the number of lanes, road length, and slow speed. As the evaluation results of those models, the RMSE values of those models were each 0.2035 and 0.2107. In this study, only data from Sejong City were used to our models, but ours can be applied to all regions where traffic nodes and links are constructed. Therefore, our prediction models can be extended to a wider range.

• 한국도로학회논문집
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• 제17권6호
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• pp.75-83
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• 2015

PURPOSES : This study deals with the traffic accidents classified by the traffic analysis zone. The purpose is to develop the accident density models by using zonal traffic and socioeconomic data. METHODS : The traffic accident density models are developed through multiple linear regression analysis. In this study, three multiple linear models were developed. The dependent variable was traffic accident density, which is a measure of the relative distribution of traffic accidents. The independent variables were various traffic and socioeconomic variables. CONCLUSIONS : Three traffic accident density models were developed, and all models were statistically significant. Road length, trip production volume, intersections, van ratio, and number of vehicles per person in the transportation-based model were analyzed to be positive to the accident. Residential and commercial area ratio and transportation vulnerability ratio obtained using the socioeconomic-based model were found to affect the accident. The major arterial road ratio, trip production volume, intersection, van ratio, commercial ratio, and number of companies in the integrated model were also found to be related to the accident.

• 한국안전학회지
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• 제32권5호
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• pp.129-134
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• 2017

This study aims to develop the traffic accident models by circular intersection type using count data model. The number of accident, the number of fatal and injured persons(FSI), and EPDO are calculated from the traffic accident data of TAAS. The circular intersection accident models are developed through Poisson and negative binomial regression analysis. The main results of this study are as follows. First, the null hypotheses that there are differences in the number of traffic accidents, FSI and EPDO by type of circular intersections are rejected. Second, the scale of intersection(median, large), number of approach road, mean width and length of exit road, area of the circulating roadway and central island are selected as factors influencing the number of traffic accidents, FSI and EPDO in rotary. Third, the scale of intersection(median), guide signs(limited speed, direction, roundabout), number of approach road, entry angle, area of the intersection and central island are adopted as factors influencing the number of traffic accidents, FSI and EPDO in roundabout. Finally, transferring from rotary to roundabout could be expected to make the accident decrease.

• 산업공학
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• 제15권4호
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• pp.426-431
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• 2002

In many cases, the result of a road traffic accident can be described with more than one response variables. Nonetheless, most of the existing road accident data analysis deal with only one response variable and try to explain why it occurs. In this paper, we train association rules for a set of more than two response variables conditional on personal, environmental and vehicular/behavioral aspects of accident. Association rules are derived at 8% support and 70% confidence from the 1996 data of three police stations in Korea. We expect that these rules can contribute to effective safety practice in Korea.

• 대한교통학회지
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• 제23권3호
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• pp.125-136
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• 2005

현재 도로사업의 타당성 조사 시 사용하는 교통사고 감소편익 산정시 도로등급별로 사고율을 일률적으로 적용하고 있고, 도로특성 및 V/C에 따른 특성이 고려되고 있지 못하고 있다. 이와 같은 문제점을 해결하기 위해 본 논문에서는 도로유형별 V/C 및 교통 특성을 반영하여 사고를 예측할 수 있는 모형을 개발하여 도로의 신설 및 개량에서 그 도로의 안전성을 평가할 수 있는 방법론을 제시하였다. 본 연구에서는 초기 단계로서 도시지역 도로를 대상으로 하여 모형을 개발하였다. 우선 도로유형별로 사고에 영향을 미치는 요인을 선정하였다. 이 때 선정 기준은 도로설계단계에서 획득할 수 있는 자료를 위주로 선정하였으며. 교통량, 중앙분리대의 유 무, 교차점수. 연결로수, 횡단신호등수 그리고 차로수를 선정하였다. 각 요인과 사고와의 관계를 분석해 본 결과 모두 통계적으로 유의한 수준에서 상관성이 있는 것으로 나타났다. 본 연구에서는 도로의 등급 및 V/C에 따라 4가지 유형으로 분류하고, 각각에 대하여 포아송 선형회귀식을 통하여 사고예측모형을 도출하였으며, 실제 자료를 이용하여 검증하였다. 검증결과 모형식의 결과가 실제 사고 자료에 대해 비교적 양호하게 추정력을 보이는 것으로 나타났다. 본 연구에서는 V/C에 따른 도로유형별 사고예측모형을 개발함으로써 도로의 물리적인 특성으로 인한 교통사고예측이 가능하고, 이 결과를 도로의 신설 및 개량에 대한 타당성 조사시 사고비용을 추정하는데 활용할 수 있을 것이라 판단된다. 본 연구에서 이용한 자료가 전라북도 한 지역으로 한정되어있어 전국적인 대표성을 지니는 데에는 한계가 있을 수 있다는 사실을 밝히고자한다.

• 대한교통학회지
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• 제23권7호
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• pp.77-86
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• 2005

현재 우리나라 간선도로의 서비스수준(LOS)은 차량의 평균통행속도를 기준으로 평가되어지고 있다. 이는 도로의 혼잡도 만을 기준으로 적용한 것으로 교통안전측면이 고려되지 않은 것이 현실이다. 합리적인 도로 설계와 운영을 위한 평가 지표라면 도로 이용자에게 영향을 미치는 제반 인자들을 보다 포괄적으로 포함할 수 있어야 한다. 교통안전과 소통측면을 총괄할 수 있는 변수로 사용자비용 개념을 적용하여 간선도로 평가방법을 모색하고자 한다. 사용자 비용을 효과척도로 하는 간선도로 평가도 가능하다는 것을 본 연구를 통해 알 수 있었다. 또한, 본 연구의 사용자 비용에 의해 평가된 간선도로 서비스 수준과 도로용량편람의 평균통행속도에 의해 평가된 간선도로 서비스 수준을 비교 분석하여 종합적인 서비스 수준 분석방법 여부를 가릴 수 있을 것이다. 이로서, 안전과 소통 측면을 모두 고려한 간선도로 평가가 가능함을 알 수 있었다.