PURPOSES : The surface distress of asphalt pavements is one of the major factors affecting the safety of road users. The aim of this study was to analyze the factors influencing the occurrence of surface distress and statistically predict its annual change to contribute to more reasonable asphalt pavement management using the data periodically collected by the national highway pavement data management system.
METHODS : In this study, the factors that were expected to influence the surface distress were determined by reviewing the literature. The normality was secured by changing the forms of the variables to make the distribution of the variables got closer to normal distribution. In addition, min-max normalization was performed to minimize the effect of the unit and magnitude of the candidate independent variables on the dependent variable. The final candidate independent variables were determined by analyzing the correlation between the annual surface distress change and each candidate independent variable. In addition, a prediction model was developed by performing data grouping and multi-regression analysis. RESULTS : An annual surface distress change prediction model was developed using present surface distress, age, and below 0 ℃ days as the independent variables. As a result of sensitivity analysis, the surface distress affected the annual surface distress change the most. The positive correlation between the dependent variable and each independent variable demonstrated engineering and statistical meaningfulness of the prediction model.
CONCLUSIONS : The surface distress in the future can be predicted by applying the annual surface distress prediction model to the national highway asphalt pavement sections with survey data. In addition, the prediction model can be applied to the national highway pavement condition index (NHPCI) evaluating the national highway asphalt pavement conditions to be used in the prediction of future NHPCI.

ABSTRACT
1. 서론
2. 자료수집 및 분석
    2.1. 표면결함에 영향을 주는 인자
    2.2. 자료수집 방법
    2.3. 분석 대상구간 선정
3. 연간 표면결함 변화량 예측모형 개발
    3.1. 예측모형 개발 방법
    3.2. 변수 분포의 정규화
    3.3. 연간 표면결함 변화량과 영향 인자 간 상관성 분석및 그룹화
    3.4. 모형 개발 및 검증
    3.5. 민감도 분석
4. 결론
REFERENCES

• 이재훈(인하대학교 공과대학 스마트시티공학과 박사과정) | Lee Jae Hoon
• 이강훈(한국건설기술연구원 전임연구원 · 인하대학교 토목공학과 박사과정) | Lee Kang Hun
• 임재규(한국건설기술연구원 수석연구원) | Lim Jae Kyu
• 정진훈(인하대학교 공과대학 사회인프라공학과 교수) | Jeong Jin Hoon Corresponding author