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포장상태 예측방법 개선에 관한 연구Development of Prediction Method for Highway Pavement Condition

Other Titles
Development of Prediction Method for Highway Pavement Condition
Authors
박상욱서영찬정철기
Issue Date
Sep-2008
Publisher
한국도로학회
Keywords
포장상태 예측모델; 확률론적 모형; 결정론적 모형; pavement performance prediction model; probabilistic and deterministic modeling; pavement performance prediction model; probabilistic and deterministic modeling
Citation
한국도로학회논문집, v.10, no.3, pp 199 - 208
Pages
10
Indexed
KCI
Journal Title
한국도로학회논문집
Volume
10
Number
3
Start Page
199
End Page
208
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/42820
ISSN
1738-7159
2287-3678
Abstract
포장상태 예측은 의사결정과정에서 포장의 공용성능을 평가하고 사업대상구간의 우선순위를 선정하기 위한 적정한 정보를 제공해준다. 근래들어 현재의 포장상태가 장래에 어느 정도 저하되는지를 예측하려는 많은 접근이 있었으나 포장의 서비스수명을 적정히 예측하는 데에는 한계를 보여왔다. 본 논문에서는 포장상태 예측방법을 개선하기 위하여 포장상태 공용성모형과 포장상태 예측모형을 개발하였다. 공용성 모형은 실제 포장상태 분석결과를 회귀분석하여 포장의 종류별, 교통량별로 백분위 50%, 25%, 15%, 5%의 확률분포 모형을 도출한 것이다. 예측모형은 앞서 도출된 공용성모형 모형식을 기준으로 하여 대상구간 각각의 포장상태 측정값에 의해 포장상태 확률을 결정한다. 개발된 예측모형의 검증을 위하여 비교대상구간을 선정하였고, HPCI의 평균값 표준편차, 3.0이하 비율을 비교분석하였다. 이를 통하여 기존예측모형이 안고 있는 교통량, 재령, 현재 포장 상태를 고려하여 보다 현실에 부합되는 포장상태를 예측하는 방법을 제공하고자 한다.
Prediction the performance of pavement provides proper information to an agency on decision-making process; especially evaluating the pavement performance and prioritizing the work plan. To date, there are a number of approaches to predict the future deterioration of pavements. However, there are some limitation to proper prediction of the pavement service life. In this paper, pavement performance model and pavement condition prediction model are developed in order to improve pavement condition prediction method. The prediction model of pavement condition through the regression analysis of real pavement condition is based on the probability distribution of pavement condition, which set to 5%, 15%, 25% and 50%, by condition of the pavement and traffic volume. The pavement prediction model presented from the behavior of individual pavement condition which are set to 5%, 15%, 25% and 50% of probability distribution. The performance of the prediction model is evaluated from analyzing the average, standard deviation of HPCI, and the percentage of HPCI which is lower than 3.0 of comparable section. In this paper, we will suggest the more rational method to determine the future pavement conditions, including the probabilistic duration and deterministic modeling methods regarding the impact of traffic volume, age, and the type of the pavement.
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