단지 내 도로는 별도의 설계법 없이 AASHTO 및 TA 설계법, 한국형 도로포장 설계법을 적용하여 일률적인 포장 두께를 적용하고 있으나 비산먼지 방지 목적으로 중간층 또는 기층 포설 후, 공사차량을 사전개방하고 사업 준공 단계에서 표층을 시공하는 단계시공 을 실시하고 있다. 이에 의해 포장단면 두께는 공사차량의 영향으로 공용수명을 만족하지 못하게 되므로 포장 파손이 빈번하게 발생 하므로 이를 고려한 포장 설계법 정립이 필요하다. 따라서 공사차량 통행을 고려한 단지 내 도로포장 설계기준을 적용한 시험시공 구 간을 대상으로 현장 모니터링 조사를 수행하였으며, 구조해석 프로그램을 활용하여 단면두께에 대한 포장 공용수명을 산출함으로써 적정성을 검토하였다. 현장조사 결과, 표층 시공 후, 공사차량 교통량을 개방한 구간에서는 공용기간 48개월일 때 표면 균열율이 1% 미만으로 조사되었으며, 중간층만 포설된 단면에서 공사차량 하중이 재하되고, 표층을 포설한 구간의 균열율은 약 8%로 상대적으로 높게 나타났다. 일반적으로 균열율이 8% 초과할 경우, 노후화된 포장층으로 판단하여 유지보수를 실시(서울시, 2018)하므로 조기파손 이 발생한 것으로 제시할 수 있다. 또한, 기존 설계기준을 적용한 구간의 표면상태 조사결과와 KENPAVE를 활용한 Damage 산출 결과 가 유사한 추세로 나타났으며, 6,170 세대 이상의 공사차량이 통행할 경우 공용년수를 만족하지 못하였으므로 해당 세대수에 대해서는 상향 설계를 실시해야 한다. 유지보수 기준에 따라 5∼7년 동안 공용된 포장에서 나타나는 균열율을 기준으로 KENPAVE Damage 10%, KPRP 피로균열 6% 이하이면 10년 이상의 공용이 가능한 것으로 도출되었다. 그러나 절삭 후 덧씌우기를 진행하지 않은 포장 단면에서는 상대적으로 높은 표면 균열율이 발생하므로, 잔존수명 예측을 통해 적절한 절삭 깊이를 산출하여 목표 설계수명을 만족할 수 있는 단지 내 도로포장 설계단면의 적정 기준을 제시함으로써 공용수명을 향상시킬 수 있을 것으로 기대한다.

PURPOSES : The evaluation of the road pavement thickness in an apartment complex through a methodology for estimating the number of construction vehicles is presented. We also show the usability of the new design criteria. METHODS : A field survey plan was established by conducting literature and preliminary surveys, and the structural performance of each section of the road pavement was compared through a structural analysis program. The load on construction vehicles is required for analyzing the ESAL factors of construction vehicles; it is calculated as a methodology for estimating construction vehicles because it is difficult to measure the traffic volume through visual inspection. Accordingly, the extent of damage predicted by road pavement sections in apartment complexes was analyzed to examine the possibility of applying the methodology for estimating the number of construction vehicles. RESULTS : If the road crack exceeds 20% as a result of the site survey of a previous study, structural damage to the road pavement occurs from construction vehicles. Compared to the actual traffic volume observation, an error of 5% took place; therefore, it is necessary to perform a design such that the damage caused by the load of the construction vehicle be 15% or less for proper road performance. Structural analysis through the KENPAVE program showed that the damage caused by the load of the construction vehicle exceeded 20% in all sections except section B (with a thickness of 46 cm). CONCLUSIONS : Owing to the limitations of the test construction section and environmental conditions, it is necessary to assess the effects of various variables by conducting an analysis. This is expected to be applied as a design basis considering more reliable construction vehicles.

PURPOSES : As road pavement design in an apartment complex varies from one site to another, it is practically difficult to calculate and estimate the traffic volume of construction vehicles. Therefore, this study introduces a methodology to estimate the number of construction vehicles and use it as an indicator to evaluate the conditions of road pavement in an apartment complex. METHODS: Through a literature review and site survey, the operational status of the construction vehicles passing through the site was identified, and the factors affecting the number of construction vehicles were analyzed. The methodologies used to estimate the number of construction vehicles were verified by calculating the Cumulative Load Prediction Index (CLPI), which is a predictive index of the cumulative load on each path. By using this index, the traffic volume of construction vehicles can be estimated based on the number of households in an apartment complex. To prove this definition, we examined the surface and core conditions, and compared the results against the predicted values. RESULTS : By comparing the Cumulative Load Prediction Index with the crack rate on the pavement surface, we obtained a correlation coefficient of 0.92. Furthermore, the analysis indicated that the core condition rate would decrease as the Cumulative Load Prediction Index increased. This correlation between the Cumulative Load Prediction Index, and the pavement surface and core status demonstrates that the traffic volume can be estimated by considering the number of households. CONCLUSIONS: The Cumulative Load Prediction Index presented in this study is a suitable indicator for estimating the conditions of the road pavement in an apartment complex by considering the number of households in the complex, even if the construction processes and characteristics vary.