포장상태 지수간의 상관모형 개발 및 국도 포장 보수보강 공법 선정 논리 개선 연구

Abstract

우리나라 도로는 1970년대 경부고속도로 건설과 함께 급격히 성장하여 2014년 말 기준으로 도로 연장은 105,672km이고, 포장 연장은 89,701km에 이르고 있다. 2000년대 이후, 이상기후 발생, 중차량 증가, 도로 노후화 등의 요인에 의해 포장 파손은 급격히 진행되고 있으며, 이에 따른 도로 포장 유지보수 예산도 점차로 증가되고 있다. 최근 국민 삶의 질과 의식수준이 향상되면서 국민과 국회에서는 증가된 도로 유지보수 예산에 대한 설명을 요구하고 있으며, 국가에서는 집행된 예산이 포장상태를 어떻게 향상시켰는지에 대한 설명 자료가 필요한 실정이다. 그러나, 국내 도로관리기관에서 제시하고 있는 포장상태는 각각의 유지관리 목적에 맞도록 개발된 포장상태 지수를 사용함으로 인하여 국가에서는 전체 도로망에 대한 포장상태를 손쉽게 파악할 수 없는 실정이다. 이에 본 연구는 국내 도로관리 기관의 각기 다른 포장상태 지수에 대한 특성을 이해하고, 포장상태 지수간의 상관모형을 개발하여 국가차원의 포장상태를 손쉽게 파악하고, 비교할 수 있는 체계를 갖추고자 수행하였다. 우선, 각 기관에서 사용되고 있는 포장상태 지수의 특성을 이해하기 위하여 8년간 수집된 현장 포장상태 자료를 이용하여 실제 나타날 수 있는 파손 범위를 설정하고 각 지수식의 파손인자별 민감도 분석을 실시하였다. 그 결과, 고속도로의 HPCI는 소성변형과 평탄성에 가장 민감하였고, 서울시의 SPI는 균열에 가장 민감하였다. 이러한 민감도 분석을 바탕으로 대표 포장상태 지수를 일반국도 NHPCI로 선정하고, 회귀분석 방법을 이용하여 NHPCI와 타지수간의 상관모형을 개발하였다. 개발된 상관모형을 활용하는 측면에서, 타지수의 보수 경계값을 NHPCI로 환산하여 비교한 결과, 고속도로, 일반국도, 서울시 순으로 관리기준이 설정되어 있는 것을 확인하였다. 또한, 일부 타기관의 지수를 수집하여 NHPCI로 비교한 결과에서도 고급도로일수록 포장상태가 좋은 것으로 평가되었다. 년차별 도로 등급별 포장상태 비교에서는 2012년 기준으로 일반국도의 포장상태 점차로 나빠지는 경향을 보였다. 이러한 결과는 유지보수 예산 제약과 더불어 개별파손 지수만으로 보수우선 순위 및 포장 보수보강 공법을 선정하는 논리의 한계점에 기인한 것으로 판단되었다. 이에 따라, 추가적으로 본 연구에서는 현 일반국도 포장 보수보강 공법 선정 논리에 포장상태 지수와 평탄성이 기준항목으로 포함되도록 하여 복합적인 파손상태에 대한 보수우선 순위 및 보수보강 공법이 결정되도록 하는 개선안을 제시하였다. 개발된 포장상태 지수간의 상관모형은 현재 도로관리기관별로 수집되고 있는 포장상태를 하나의 대표 포장상태 지수로 표현할 수 있는 기틀을 마련하는 것으로 국가 차원의 도로망 전체에 대한 포장상태를 파악하는 도구로 활용할 수 있을 것으로 판단된다.|The construction of the Gyeongbu Expressway in the 1970s lead to an exponential growth of road network. Based on 2014 statistics, there are 105,672 km of roads and 89,701 km of paved roads. After the 2000s, abnormal weather conditions, increase in larger vehicles, and deterioration of roads all factor into rapid damage and increased maintenance budgets. Improved quality of life and general intelligence have prompted the public to question rising road maintenance budgets. The current state, however, is that the nation is in need of data to represent the improvements made on paved roads. Currently, the Pavement Condition Index (PCI) used by the domestic road administration, is meant to represent individual pavement conditions and management which causes for a difficult understanding of conditions of the whole road network. This study aims to understand the characteristics of each individual PCI and to develop a correlation model between these Indices in order to comprehend pavement conditions as a whole and to formulate a system which enables comparisons between different Indices. First, in order to understand the PCI of each organization damage scale was set using combined field pavement condition data of eight years, then each index formula of damage sensitivity was analyzed. The HPCI (Highway Pavement Condition Index) was mostly affected by rut depth and roughness, while the SPI (Seoul Pavement Index) was affected by cracking. Through these Sensitivity Analyses, pavement condition Indices were set to the NHPCI (National Highway Pavement Condition Index) and by using regression analysis, a correlation model between NHPCI and comparable Indices was devised. Using the correlation model, boundary values of various Indices were converted to NHPCI values resulting in a high management criteria of expressway, national roads, seoul city roads, in descending order. Moreover, converting Indices collected by various organizations and converting these to the NHPCI also showed higher conditions in high-quality roads. Yearly pavement conditions based on road class shows that based on 2012, pavement conditions of national roads have been steadily deteriorating. As a result, with budget restrictions for national roads and using only damage individual index to select maintenance priority and repair reinforcement methods leads to limitations and selection bias. Through this study, on top of current selection standards, new articles such as PCI and Roughness should also be considered to accommodate comprehensive damage conditions when selecting maintenance priority and repair reinforcement methods. The developed PCI correlation model can be used as a foundation for displaying current pavement condition data being collected by different road organizations into one representative condition index (PCI). Therefore, it can be stated that this index can be used to understand the pavement conditions of the road network on a national scale.; The construction of the Gyeongbu Expressway in the 1970s lead to an exponential growth of road network. Based on 2014 statistics, there are 105,672 km of roads and 89,701 km of paved roads. After the 2000s, abnormal weather conditions, increase in larger vehicles, and deterioration of roads all factor into rapid damage and increased maintenance budgets. Improved quality of life and general intelligence have prompted the public to question rising road maintenance budgets. The current state, however, is that the nation is in need of data to represent the improvements made on paved roads. Currently, the Pavement Condition Index (PCI) used by the domestic road administration, is meant to represent individual pavement conditions and management which causes for a difficult understanding of conditions of the whole road network. This study aims to understand the characteristics of each individual PCI and to develop a correlation model between these Indices in order to comprehend pavement conditions as a whole and to formulate a system which enables comparisons between different Indices. First, in order to understand the PCI of each organization damage scale was set using combined field pavement condition data of eight years, then each index formula of damage sensitivity was analyzed. The HPCI (Highway Pavement Condition Index) was mostly affected by rut depth and roughness, while the SPI (Seoul Pavement Index) was affected by cracking. Through these Sensitivity Analyses, pavement condition Indices were set to the NHPCI (National Highway Pavement Condition Index) and by using regression analysis, a correlation model between NHPCI and comparable Indices was devised. Using the correlation model, boundary values of various Indices were converted to NHPCI values resulting in a high management criteria of expressway, national roads, seoul city roads, in descending order. Moreover, converting Indices collected by various organizations and converting these to the NHPCI also showed higher conditions in high-quality roads. Yearly pavement conditions based on road class shows that based on 2012, pavement conditions of national roads have been steadily deteriorating. As a result, with budget restrictions for national roads and using only damage individual index to select maintenance priority and repair reinforcement methods leads to limitations and selection bias. Through this study, on top of current selection standards, new articles such as PCI and Roughness should also be considered to accommodate comprehensive damage conditions when selecting maintenance priority and repair reinforcement methods. The developed PCI correlation model can be used as a foundation for displaying current pavement condition data being collected by different road organizations into one representative condition index (PCI). Therefore, it can be stated that this index can be used to understand the pavement conditions of the road network on a national scale.