다양한 통계 기법을 활용한 안전성능함수 개발 및 비교 연구 : 트럼펫형 램프를 중심으로 Development and Exploration of Safety Performance Functions Using Multiple Modeling Techniques : Trumpet Ramps원문보기
최근 고속도로 본선구간에서 발생한 교통사고에 대한 연구가 다수 수행되고 있으나, 램프와 같이 본선 외 구간에 대한 교통안전을 다루는 연구는 미미한 실정이다. 최근 5년(2015년~2019년)동안 램프에서 발생한 사고는 총 6,717건으로 이는 전체 고속도로 사고의 약 15%를 차지한다. 본 연구에서는 고속도로 램프구간에 대해 보다 정확한 사고 예측 모형을 제공하기 위해 포아송 감마(PG)와 포아송 역가우스(PIG)와 같은 다양한 통계 분포를 비롯하여 랜덤효과와 같은 기법을 적용하여 Simple 및 Full SPF를 구축하고 비교하였다. 교통 및 도로 기하구조 데이터는 로드뷰와 같은 다양한 시스템에서 수집되었다. 분석 결과, PIG 모형은 일반적으로 더 정확한 사고 예측을 제시하며, Simpe SPF와 Full SPF 모두에서 임의효과 모형이 더욱 우수한 성능을 나타내었다. 본 연구결과는 교통실무자들에게 정확한 사고 예측 모형을 기반으로 램프구간 교통안전을 증대시키고 이해할 수 있는 참고자료로써 활용될 수 있다.
최근 고속도로 본선구간에서 발생한 교통사고에 대한 연구가 다수 수행되고 있으나, 램프와 같이 본선 외 구간에 대한 교통안전을 다루는 연구는 미미한 실정이다. 최근 5년(2015년~2019년)동안 램프에서 발생한 사고는 총 6,717건으로 이는 전체 고속도로 사고의 약 15%를 차지한다. 본 연구에서는 고속도로 램프구간에 대해 보다 정확한 사고 예측 모형을 제공하기 위해 포아송 감마(PG)와 포아송 역가우스(PIG)와 같은 다양한 통계 분포를 비롯하여 랜덤효과와 같은 기법을 적용하여 Simple 및 Full SPF를 구축하고 비교하였다. 교통 및 도로 기하구조 데이터는 로드뷰와 같은 다양한 시스템에서 수집되었다. 분석 결과, PIG 모형은 일반적으로 더 정확한 사고 예측을 제시하며, Simpe SPF와 Full SPF 모두에서 임의효과 모형이 더욱 우수한 성능을 나타내었다. 본 연구결과는 교통실무자들에게 정확한 사고 예측 모형을 기반으로 램프구간 교통안전을 증대시키고 이해할 수 있는 참고자료로써 활용될 수 있다.
In recent times, several studies have been conducted focusing on crashes occurring on the main segment of the highway. However, there is a dearth of research dealing with traffic safety relating to other highway facilities, especially ramp areas. According to the Korea Expressway Corporation's Expre...
In recent times, several studies have been conducted focusing on crashes occurring on the main segment of the highway. However, there is a dearth of research dealing with traffic safety relating to other highway facilities, especially ramp areas. According to the Korea Expressway Corporation's Expressway Information Service, 6,717 crashes have occurred on ramps in the five years from 2015~2019, which accounts for about 15% of all highway accidents. In this study, the simple and full safety performance functions (SPFs) were evaluated and explored using different statistical distributions (i.e., Poisson Gamma (PG) and Poisson Inverse Gaussian (PIG)) and techniques (i.e., fixed effects (FE) and random effects (RE)) to provide more accurate crash prediction models for highway ramp sections. Data on the geometric characteristics of traffic and roadways were collected from various systems and with extensive efforts using a street-view application. The results showed that the PIG models present more accurate crash predictions in general. The results also indicated that the RE models performed better than FE models for simple and full SPFs. The findings from this study offer transportation practitioners using the Korea Expressway Corporation's Expressway a dependable reference to enhance and understand traffic safety in ramp areas based on accurate crash prediction models and empirical evidence.
In recent times, several studies have been conducted focusing on crashes occurring on the main segment of the highway. However, there is a dearth of research dealing with traffic safety relating to other highway facilities, especially ramp areas. According to the Korea Expressway Corporation's Expressway Information Service, 6,717 crashes have occurred on ramps in the five years from 2015~2019, which accounts for about 15% of all highway accidents. In this study, the simple and full safety performance functions (SPFs) were evaluated and explored using different statistical distributions (i.e., Poisson Gamma (PG) and Poisson Inverse Gaussian (PIG)) and techniques (i.e., fixed effects (FE) and random effects (RE)) to provide more accurate crash prediction models for highway ramp sections. Data on the geometric characteristics of traffic and roadways were collected from various systems and with extensive efforts using a street-view application. The results showed that the PIG models present more accurate crash predictions in general. The results also indicated that the RE models performed better than FE models for simple and full SPFs. The findings from this study offer transportation practitioners using the Korea Expressway Corporation's Expressway a dependable reference to enhance and understand traffic safety in ramp areas based on accurate crash prediction models and empirical evidence.
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