PURPOSES : The primary purpose of this study is to establish a crash probability model based on a statistical method that explains the relationship between regressor and explanatory variables using both fixed and random effects to control the heterogeneous characteristics of the observed data. In addition, an attempt was made to discover the leading cause of crashes by vehicle type, including passenger car, bus, truck, and trailer.
METHODS : The levels of each route and day of the week are grouped using raw expressway crash data for 10 years from 2012 to 2021, and a multilevel mixed-effect logit model is constructed for each vehicle type assuming that the error terms are derived from the hierarchical structure of the group to which they belong.
RESULTS : Speeding and obstacles on the road are significant factors that increase the probability of passenger car crashes, and bus crashes have a high rate at toll gates on weekdays.
CONCLUSIONS : The multilevel mixed-effect logit model derived in the study has higher accuracy than the general logit model, confirming that mixed-effect analysis is plausible.

ABSTRACT
1. 서론
2. 기존 연구고찰
3. 다수준 혼합효과 로짓모형 (Multilevel mixed-effects logistic regression)
4. 분석결과
    4.1. 승용차 사고확률예측모형
    4.2. 버스 사고확률예측모형
    4.3. 화물차 사고확률예측모형
    4.4. 트레일러 사고확률예측모형
    4.5. 모형의 적합도 검증
5. 결론
REFERENCES

• 김강현(계명대학교 연구원) | Kim Kang Hyun
• 홍정열(계명대학교 조교수) | Hong Jung Yeol Corresponding author