PURPOSES : This study aims to analyze the causes of pedestrian traffic accidents on community roads. METHODS : This study collected variables affecting pedestrian traffic accidents on community roads based on field surveys and analyzed them using negative binomial regression and zero-inflated negative binomial regression models. RESULTS : Model analysis results showed that the negative binomial regression model is more suitable than the zero-inflation negative binomial regression model. Additionally, the segment length (m), pedestrian volume (persons/15 min), traffic volume (numbers/15 min.), the extent of illegal parking, pedestrian-vehicle conflict ratio, and one-way traffic (one: residential, two: commercial) were found to influence pedestrian traffic accidents on community roads. Model fitness indicators, comparing actual values with predicted values, showed an MPB of 1.54, MAD of 2.57, and RMSE of 7.03. CONCLUSIONS : This study quantified the factors contributing to pedestrian traffic accidents on community roads by considering both static and dynamic elements. Instead of uniformly implementing measures, such as pedestrian priority zones and facility improvements on community roads, developing diverse strategies that consider various dynamic factors should be considered.

1. 서론
2. 기존 문헌 고찰
3. 데이터 수집
    3.1. 분석대상
    3.2. 변수수집 및 기초통계 분석
4. 분석방법론
5. 생활도로 보행자 교통사고 모형구축 결과
    5.1. 음이항회귀모형(NB) 구축결과
    5.2. 영과잉 음이항회귀모형(ZINB) 구축결과
    5.3. 모형의 적합도 비교(Vuong Z Test 결과)
    5.4. 모형해석 및 검증
6. 결론

• 김선정(정회원 · 서울시립대학교 교통공학과 박사수료) | Kim Sunjung
• 김동기(PINTEL 대표이사) | Kim Dongkey
• 이수범(정회원 · 서울시립대학교 교통공학과 교수) | Lee Soobeom
• 임준범(정회원 · 한국교통안전공단 모빌리티정책연구처 책임연구원) | Lim Joonbeom 교신저자