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지역 특성에 따른 강원도 내 일반국도 아스팔트 포장의 평탄성 변화
이재훈,이재훈,우병찬,이수형,김연태,정진훈 한국도로학회 2023 한국도로학회논문집 Vol.25 No.2
PURPOSES : For most local governments, including that of Gangwon-do, the establishment of an organized pavement management system is insufficient, resulting in problems such as inefficient distribution and use of maintenance budgets for deteriorated road pavements. In this study, we aimed to contribute to the establishment of a more reasonable road maintenance strategy by developing a model for predicting the annual international roughness index (IRI) change for national highway asphalt pavements in Gangwon-do based on big data analysis. METHODS : Data on independent and dependent variables used for model development were collected. The collected data were subjected to exploratory data analysis (EDA) and data preprocessing. Independent variable candidates were selected to reduce multicollinearity through correlation analysis and specific conditions. A final model was selected, and sensitivity analysis was performed. RESULTS : The final model that predicts annual IRI change uses independent variables such as annual temperature range, minimum temperature, freeze-thaw days, IRI, surface distress (SD), and freezing days. The sensitivity analysis confirmed that the annual IRI change was affected in the order of annual temperature range, minimum temperature, freeze-thaw days, IRI, SD, and freezing days. CONCLUSIONS : Road maintenance can be performed rationally by predicting future pavement conditions using the model developed in this study. The accuracy of the prediction model can be improved if additional data, such as material properties and pavement thickness, are obtained in future studies.
제주도 지방도 포장의 공용성에 영향을 미치는 인자의 분석
이재훈,이재훈,김연태,이강훈,엄병식,우병찬,정진훈 한국도로학회 2022 한국도로학회논문집 Vol.24 No.3
PURPOSES : The objective of this study is to develop regression models for surface distress (SD), rut depth (RD), and international roughness index (IRI) of Jeju Island local road by analyzing the correlations between the pavement performance and its influencing factors. METHODS : First, the differences between pavements in inland Korea and Jeju Island in terms of performance and influencing factors were investigated. Influencing factors were assigned to pavement sections on Jeju Island using the inverse distance weighting method, and the correlations between the pavement performance and influencing factors were analyzed. As a result, maximum temperature, heat wave days, annual temperature range, precipitation days, precipitation intensity, ESAL, etc. were determined as independent variables for the pavement performance prediction models. Multiple regression analysis was performed to develop the pavement performance models using the selected independent variables. RESULTS : The RD, maximum temperature, and precipitation days were determined to be the independent variables for the SD predictive model. The SD, maximum temperature, annual temperature range, heat wave days, and precipitation days were selected as independent variables of the RD prediction model. In addition, the RD, annual temperature range, heat wave days, precipitation days, and ESAL were selected as independent variables for the IRI prediction model. CONCLUSIONS : As a result of the study, an actual forecast model for SD, RD, and IRI was developed. Based on this model, it is possible to estimate the predictive value of the missing performance data in the studied interval. If the factors affecting performance are managed in terms of maintenance beyond a certain level, it can help those responsible for road maintenance to rationally select the maintenance method and timing.
인천광역시의 지역 및 도로등급 별 포장 공용성 예측모형 개발
이재훈,이재훈,김연태,이수형,정진훈 한국도로학회 2022 한국도로학회논문집 Vol.24 No.6
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.