PURPOSES : In this study, surface distress (SD), rutting depth (RD), and international roughness index (IRI) prediction models are developed based on the zones of Incheon and road classes using regression analysis. Regression analysis is conducted based on a correlation analysis between the pavement performance and influencing factors.
METHODS : First, Incheon was categorized by zone such as industrial, port, and residential areas, and the roads were categorized into major and sub-major roads. A weather station triangle network for Incheon was developed using the Delaunay triangulation based on the position of the weather station to match the road sections in Incheon and environmental factors. The influencing factors of the road sections were matched Based on the developed triangular network. Meanwhile, based on the matched influencing factors, a model of the current performance of the road pavement in Incheon was developed by performing multiple regression analysis. Sensitivity analysis was conducted using the developed model to determine the influencing factor that affected each performance factor the most significantly.
RESULTS : For the SD model, frost days, daily temperature range, rainy days, tropical nights, and minimum temperatures are used as independent variables. Meanwhile, the truck ratio, freeze–thaw days, precipitation days, annual temperature range, and average temperatures are used for the RD model. For the IRI model, the maximum temperature, freeze–thaw days, average temperature, annual precipitation, and wet days are used. Results from the sensitivity analysis show that frost days for the SD model, precipitation days and freeze–thaw days for the RD model, and wet days for the IRI model impose the most significant effects.
CONCLUSIONS : We developed a road pavement performance prediction model using multiple regression analysis based on zones in Incheon and road classes. The developed model allows the influencing factors and circumstances to be predicted, thus facilitating road management.

ABSTRACT
1. 서론
2. 자료수집
    2.1. 인천광역시 지역분류체계 개발
    2.2. Delaunay Triangulation을 이용한 도로 영향인자의 매칭
3. 데이터 전처리 및 상관성 분석
    3.1. 정규성 검토
    3.2. Min-Max Scaling
    3.3. 상관성 분석
4. 모형개발 및 민감도 분석
    4.1. 공용성 모형 개발
    4.2. 민감도 분석
5. 결론
REFERENCES

• 이재훈(인하대학교 공과대학 스마트시티공학과 석사과정) | Lee Jae Hoon
• 이재훈(인하대학교 공과대학 스마트시티공학과 박사과정) | Lee Jae Hoon
• 김연태(한국건설기술연구원 도로교통연구본부 전임연구원) | Kim Yeon Tae
• 이수형(한국건설기술연구원 도로교통연구본부 수석연구원) | Lee Soo Hyoung
• 정진훈(인하대학교 공과대학 사회인프라공학과 교수) | Jeong Jin Hoon Corresponding author