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.