PURPOSES : This study analyzed explanatory variables, such as dangerous driving behaviors, in a negative binomial regression model, using the Digital Tachograph data of commercial vehicles, to assess the factors associated with freeway accidents.
METHODS : Fixed parameter and random parameter negative binomial regression models were constructed using freeway accident data of commercial vehicles from January 2007 to July 2018 on the Gyeongbu Expressway from West Ulsan Interchange to Gimcheon Junction.
RESULTS : Six explanatory variables (logarithm of average annual daily traffic, sunny, rainy, and snowy weather conditions, road curvature, and driving behaviors that included sudden stops) were found to impact the occurrence of freeway accidents significantly. Two of these variables (snowy weather conditions and sudden stops among dangerous driving behaviors) were analyzed as random parameters. These variables were shown as probabilistic variables that do not have a fixed impact on traffic accidents
CONCLUSIONS : The variables analyzed as random parameters should be carefully considered when the freeway operating authorities plan an improvement project for highway safety.

ABSTRACT
1. 서론
2. 선행연구
3. 연구 방법 및 모형 검토
    3.1. 연구 방법 및 분석 프로세스
    3.2. 모형 검토
4. 결과 및 분석
    4.1. 데이터 구축 및 기초통계량 검토
    4.2. 다중공선성 진단 및 과분산 여부 판정
    4.3. FPNB 및 RPNB 모형 분석 결과
5. 결론 및 한계점
REFERENCES

• 정다운(서울대학교 건설환경공학부) | Jeong Da-Woon
• 김동규(서울대학교 건설환경공학부/서울대학교 건설환경종합연구소) | Kim Dong-Kyu
• 조신형(조지아 공과대학교 박사후연구원) | Cho Shin-Hyung 교신저자