PURPOSES: This study aimed to analyze traffic accidents at circular intersections, and discuss accident reduction strategies based on land use and vehicle type. METHODS : Traffic accident data from 2010 to 2014 were collected from the “traffic accident analysis system”(TAAS) data set of the Road Traffic Authority. To develop the accident rate model, a multiple linear regression model was used. Explanatory variables such as geometry and traffic volume were used to develop the models. RESULTS: The main results of the study are as follows. First, it was found that the null hypotheses that land use and vehicle type do not affect the accident rate should be rejected. Second, 16 accident rate models, which are statistically significant (with high R2 values), were developed. Finally, the area of the central island, number of speed humps, entry lane width, circulatory roadway width, bus stops, and pedestrian crossings were analyzed to determine their effect on accidents according to the type of land use and vehicle. CONCLUSIONS: Through the developed accident rate models, it was revealed that the accident factors at circular intersections changed depending on land use and vehicle type. Thus, selecting the appropriate location of bus stops for trucks, widening entry lanes for cars, and installing splitter islands and optimal lighting for motorcycles were determined to be important for reducing the accident rate. Additionally, the evaluation showed that commercial and mixed land use had a weaker effect on accidents than residential land use.

PURPOSES : The purpose of this study is to develop models of accidents occurring at circular intersections related to the time of day and night and driver gender, and to provide countermeasures for safer circular intersections. METHODS: Seventy intersections built before 2008 were surveyed for inclusion in the modeling. Traffic accident data from 2008 to 2014 were collected from the TAAS data set of the Road Traffic Authority. Sixteen variables explaining the accidents including geometry and traffic volume were selected from the literature and seven multiple linear regression models were developed using SPSS 20.0. RESULTS: First, the null hypotheses, that the number of traffic accidents are not related to driver gender or time of day, were rejected at a 5% level of significance. Second, seven statistically significant accident models with R2 value of 0.643-0.890 were developed. Third, in daytime models by gender, when the right-turn-only lane was selected as the common variable, the number of lanes, presence of driveways and speed humps, diagrammatic exit destination sign, and total entering traffic volume were evaluated as specific variables. Finally, in nighttime models by gender, when the diagrammatic exit destination sign was selected as the common variable, total entering traffic volume, presence of right-turnonly lanes, number of circulatory road way lanes, and presence of splitter islands and driveways were identified as specific variables. CONCLUSIONS: This study developed seven accident models and analyzed the common and specific variables by time of day and gender. The results suggest approaches to providing countermeasures for safer circular intersections.

이 연구는 국내 원형교차로에서 발생한 교차로 사고를 다루고 있다. 연구의 목적은 ZAM을 이용하여 원인별 사고모형을 개발하는데 있다. 주요결과는 다음과 같다. 첫째, 교차로 운행방법 위반에서는 ZINB 모형이 적합한 것으로 분석되었다. 둘째, 안전거리 미확보에서도 ZINB 모형이 적합한 것으로 분석되었다. 마지막으로 공통변수로는 교통량과 회전차로 폭이 선정되었다. 교통량이 많을수록 그리고 회전차로 폭이 좁을수록 사고가 많이 발생하는 것으로 분석되었다. 특정변수로는 접근로수와 감속 시설수가 채택되었고, 접근로수가 증가할수록 그리고 감속시설수가 적을수록 사고가 증가하는 것으로 분석되었다. 이 연구는 원형교차로 사고연구에 기여할 것으로 기대된다.

이 논문은 사고유형에 따른 교통사고를 다루고 있다. 연구의 목적은 두 가지 사고유형의 특성을 분석하고, 유형별 모형을 개발하는데 있다. 이를 위해 이 연구는 두 집단 사이의 차이점을 분석하고, 국내 원형교차로 자료를 사용하여 포아송 및 음이항 회귀모형을 개발하는데 그 목적이 있다. 주요 결과는 다음과 같다. 첫째, 차대차 사고가 73.41%로 가장 많은 비중을 차지하는 것으로 분석되었다. 둘째, 차대사람과 차대차 사고건수 및 EPDO를 종속변수로 통계적으로 의미 있는 2개의 포아송 모형과 2개의 음이항 모형이 개발되었다. 셋째, 사고유형별 심각도모형의 공통변수는 교통량, 그리고 특정변수로는 우회전 별도차로 수, 과속방지턱, 진출입구 수 및 횡단보도 수가 채택되었다.