PURPOSES : To efficiently manage pavements, a systematic pavement management system must be established based on regional characteristics. Suppose that the future conditions of a pavement section can be predicted based on data obtained at present. In this case, a more reasonable road maintenance strategy should be established. Hence, a prediction model of the annual surface distress (SD) change for national highway pavements in Gangwon-do, Korea is developed based on influencing factors.
METHODS : To develop the model, pavement performance data and influencing factors were obtained. Exploratory data analysis was performed to analyze the data acquired, and the results show that the data were preprocessed. The variables used for model development were selected via correlation analysis, where variables such as surface distress, international roughness index, daily temperature range, and heat wave days were used. Best subset regression was performed, where the candidate model was selected from all possible subsets based on certain criteria. The final model was selected based on an algorithm developed for rational model selection. The sensitivity of the annual SD change was analyzed based on the variables of the final model.
RESULTS : The result of the sensitivity analysis shows that the annual SD change is affected by the variables in the following order: surface distress ˃ heat wave days ˃ daily temperature range ˃ international roughness index.
CONCLUSIONS : An annual SD change prediction model is developed by considering the present performance, traffic volume, and climatic conditions. The model can facilitate the establishment of a reasonable road maintenance strategy. The prediction accuracy can be improved by obtaining additional data, such as the construction quality, material properties, and pavement thickness.

ABSTRACT
1. 서론
    1.1. 연구배경
    1.2. 연구목적 및 방법
2. 데이터수집 및 탐색적 데이터 분석
    2.1. 공용성 데이터
    2.2. 영향인자 데이터
3. 데이터 전처리 및 변수 후보군 선정
    3.1. 데이터 전처리
    3.2. 상관성 분석을 통한 변수 선정
4. 최적 부분집합 회귀분석을 활용한 예측모형 개발
    4.1. 후보모형 개발
    4.2. 최종모형 선정 및 분석
5. 결론
REFERENCES

• 우병찬(인하대학교 공과대학 스마트시티공학과 석사과정) | Woo Byoung Chan
• 이수형(한국건설기술연구원 도로교통연구본부 수석연구원) | Lee Soo Hyung
• 나계주(인하대학교 공과대학 토목공학과 박사과정) | Na Gye Ju
• 정진훈(인하대학교 공과대학 사회인프라공학과 교수) | Jeong Jin Hoon Corresponding author