Evaluation of low temperature performance of asphalt mixture is significant not only for mitigating transverse thermal cracking but also for preventing potential traffic accidents. In addition, the engineers in pavement agency need to inform the proper pavement section where urgent management is needed. Since early 2000, Korea Expressway Corporation Research Division (KECRD) developed an 3D Pavement condition Monitoring profiler vehicle (3DPM) to survey expressway pavement surface condition precisely. The management of whole expressway network became more precise, effective and efficient than before due to application of 3DPM and HPMS. One thing recommended is: performing extensive mechanical test and corresponding data analysis work procedure to further strengthen the feasibility of current 3DPM approach and HPMS. In this paper two activities were considered: first, the pavement section where the urgent care is recommended is selected by means of 3DPM approach. Then asphalt mixture cores were acquired on that specified section then low temperature fracture test: Semi Circular Bending (SCB) test, was performed. The mechanical parameters, energy release rate and fracture toughness were computed then compared. It is concluded that the current 3DPM approach in KEC can successfully evaluate and analyze selected pavement condition. However, more extensive experimental works are needed to further strengthen the current pavement analyzing approaches.

인공지능(Artificial Intelligence, AI)은 1950년대 초기개념과 이론을 앨런 튜링이 튜링 테스트를 제안하여 기계가 인간과 같은 수준의 지능을 가질 수 있는지 대한 질문을 던지면서 시작되었다. 1980년대부터 특정 분야의 전문 지식을 모방하여 지원하는 AI 시스템인 전 문가 시스템이 부상하기 시작하면서 Machine Learning이 중요성을 얻기 시작하였다. 특히, Decision Tree, Clustering 그리고 Neural Network Algorithm 등이 연구되기 시작하였다. Clustering 기법은 다양한 분야에서 통계분석에 사용되는 자료를 정제하기 위한 비지도 학습 중 하나로, 군집화 알고리즘을 사용하여 자료의 값(Pointer)들을 특정 그룹으로 분류하는 방법이다. 이러한 Clustering을 활용하여 기존 데이터에서 숨겨진 데이터들의 특성을 파악할 수 있으며, 일정 패턴이나 특징을 가진 데이터들끼리의 군집화를 할 수 있게 된다. 이러한 클러스터링은 다양한 산업 분야에서 적용 및 활용하고 있다. 산업화 이후 미국, 벨기에 등 많은 나라에서 효율적인 도로 관 리를 위해 자국의 특성에 맞는 Pavement Management System (PMS)를 운영하고 있지만 현재 많은 분야에서 적용하고 있는 AI를 활용한 사례가 매우 드물다. 한국에서도 수십년 동안 국토교통부와 한국도로공사에서 PMS를 이용하여 도로를 관리해 왔으며, 최근에 는 몇 개 지자체에서 PMS를 도입하였다. 하지만 한국에서는 오랜 PMS 운영 경험에도 불구하고 AI를 활용하지 않고 전통적 방법인 회귀모형을 활용하여 개발한 공용성 예측모형을 사용하고 있기 때문에 그 성능이 떨어지고 있다. 따라서 본 연구에서는 Machine Learning Clustering 기법을 PMS 자료에 적용이 가능한지 확인하였다. 공용성 예측모형의 종속변수인 Performance Factors와 독립변 수인 Influencing Factors 간의 상관성을 확인할 수 없는 경우 클러스터링을 적용하여 종속변수와 독립변수 간의 상관성을 분명히 나 타내고 회귀분석이 가능하도록 하였다. Delaunay Triangulation을 적용하여 인천광역시 기상관측소의 삼각망을 형성하였다. 삼각망의 각 꼭짓점과 도로 각 지점 간의 거리에 대하여 Inverse Distance Weighted 방법을 적용하여 도로 각 구간의 PMS 자료와 영향인자를 매칭하였다. 클러스터링 기법을 원자료에 적용한 결과 공용성인자와 영향인자 간의 상관성이 분명해졌다. 또한, 클러스터링 이전과 이 후 자료의 확률밀도함수의 분포를 비교하여 클러스터링 이후의 자료가 이전의 대해서 대표성을 갖고 있는지 확인하였다.

PURPOSES : The purpose of this paper is to evaluate the performance of MAST composite pavement. METHODS : A Testbed with three different sections with varying pavement materials were constructed: Section 1 (MAST(Multi-Layered Asphalt Surface Treatment) Composite Pavement; RCC(Roller Compacted Concrete)+Modified DBST(Double Bituminous Surface Treatment), Section 2 (Aggregate base+Modified DBST), and Section 3 (aggregate base+General DBST). The structural stability and skid resistance were evaluated using LFWD test and sand patch test, respectively. Moreover, laboratory specimens of four different pavement materials (HMA(Hot Mix Asphalt), Gravel base+DBST, RCC+DBST, and RCC+Modified DBST) were fabricated using and the rutting resistance of each pavement type was evaluated using the MMLS3. RESULTS : As a result of the LFWD(Light Falling Weight Deflectometer) test, the elastic modulus of Section 1 was significantly higher compared to the other section with values between 450 MPa to 650 MPa. Meanwhile, the elastic modulus of Section 2 and Section 3 were almost similar from 50 MPa to 150 MPa. Moreover, sand patch test results showed that Section 1 and Section 2 have an excellent surface roughness with values higher than 0.7 mm but Section 3 has a poor surface roughness with MTD(Mean Texture Depth) value of 0.4 mm. Lastly, based on the results of the MMLS3(third scale Model Mobile Load Simulator) test, gravel base+DBST showed the lowest resistance to rutting among the four specimens, and both RCC+modified DBST and RCC+DBST showed good performance up to 600 loading cycles, but the rut depth increased rapidly until 1,000 loading cycles. CONCLUSIONS : MAST composite pavement(RCC+modified DBST) has superior structural stability compared to general DBST pavement (aggregate base+DBST), has excellent skid resistance with values higher than 0.7 mm, and has similar rutting resistance to that of general dense asphalt concrete pavement. Therefore, exhibiting its good performance in both structural and functional aspects, it can be concluded that MAST composite pavement(RCC+modified DBST) can be an effective alternative for pavement material in Southeast Asian developing countries where support for heavy vehicle loads is required and rutting is likely to occur.

PURPOSES : The purpose of this study is to provide basic data to improve the service life of asphalt pavement using basalt aggregate in Jeju Island by evaluating the performance of asphalt pavement through analysis of material and structural aspects. METHODS : To evaluate the performance of Jeju Island's asphalt pavement, cracks, permanent deformation, and longitudinal roughness were analyzed for the Aejo-ro road, which has high traffic and frequent premature damage. Cores were collected from Aejo-ro sections in good condition and damaged condition, and the physical properties of each layer were compared and analyzed. In addition, plate cores were collected from two sections with severe damage and the cause of pavement damage was analyzed in detail. RESULTS : About 45% of the collected cores suffered damage such as layer separation and damage to the lower layer. The asphalt content of surface layer in the damaged section was found to be 1.1% lower on average than that in the good condition section, and the mix gradations generally satisfied the standards. The density difference between the cores of each layer was found to be quite large, and the air voids was found to be at a high level. CONCLUSIONS : Test results on the cores showed that, considering the high absorption ratio of basalt aggregate, the asphalt content was generally low, and the high air voids of the pavement was believed to have had a significant impact on damage. High air voids in asphalt pavement can be caused by poor mixture itself, poor construction management, or a combination of the two factors. Additionally, the separation of each layer is believed to be the cause of premature failure of asphalt pavement.

PURPOSES : The purpose of this study was to improve the performance of concrete pavements by decreasing measurement deviations using an Internet of Things (IoT)-based air content measurement device. METHODS : We calculated the properties of concrete which varied according to the air content. For a low measurement deviation, the concrete pavement performed according to the design standard. To confirm the difference in the performance of the concrete pavement for various air contents, we verified the change in the relative dynamic modulus according to the number of freeze–thaw cycles for each value of the air content. In addition, we analyzed the number of durability cracks according to the freeze–thaw cycles in the field. RESULTS : We confirmed that IoT-based measurement equipment improved the performance of pavements without changing their mixing designs or specifications. We confirmed that the performance of concrete pavements changed even with variations in air content within the range of quality standards. Using IoT-based air content management, we confirmed the reduction in concrete pavement durability cracks without changing the mixing design. CONCLUSIONS : We confirmed that IoT-based air-content management improved pavement performance. The feasibility of extending this concept to manage other concrete properties such as the chloride content should be acknowledged. Future research will require laboratory tests to understand the variation in concrete properties with varying air contents and to consider diverse load conditions.

PURPOSES : The purpose of this study was to evaluate the common performance of asphalt pavements, determine the timing of preventive maintenance, and determine the optimal timing of application of the preventive maintenance methods by analyzing PMS data. METHODS : Using PMS data on asphalt pavement performance on highways, we derived the major damage factors and evaluated them according to the public period and traffic level. Among the factors evaluated, we determined those that could be improved by preventive maintenance, calculated the amount of change annually, and derived the timing of the application of the preventive maintenance method through correlation analysis. RESULTS : Among highway PMS data factors, crack variation was found to affect preventive maintenance, which increased rapidly after five years of performance. Traffic analysis showed that changes increased rapidly in the fifth, sixth, and seventh years when AADT exceeded 20,000, exceeded 10,000, and was under 10,000, respectively. Analysis of the amount of crack variation according to the pavement type showed that crack variation increased rapidly in the overlay section compared to the general AP section. CONCLUSIONS : Crack variation is the performance factor that was expected to be effective in preventive maintenance, and the PMS data showed that the initial application time of the preventive maintenance method varied by one year, depending on the traffic volume.

PURPOSES : The numeric-based Highway Pavement Management System (HPMS), along with an advanced three-dimensional pavement condition monitoring profiler vehicle (3DPM), in South Korea has presented remarkable advancements in pavement management since the early 2000. Based on these results, visual distress on pavement surfaces can be easily detected and analyzed. Additionally, the entire expressway pavement surface conditions in South Korea can be easily monitored using the current graphical user interface-based advanced information graphic (AIG) approach. Therefore, a critically negative pavement section can be detected and managed more easily and efficiently. However, the actual mechanical performance of the selected pavement layer still needs to be investigated in a more thorough manner not only to provide more accurate pavement performance results but also to verify the feasibility of the current 3DPM and AIG approaches. In this study, the low-temperature performance of the selected asphalt pavement layer section was evaluated to further verify and strengthen the feasibility of the current 3DPM and AIG approaches developed by the Korea Expressway Corporation. METHODS : Based on 3DPM and AIG approach, the positive and negative-riding-quality road sections were selected, respectively. The asphalt material cores were extracted from each section then bending beam rheometer mixture creep test was performed to measure their low-temperature properties. Based on the experimental results, thermal stress results were computed and visually compared. RESULTS : As expected, the asphalt material from the negative driving performance section presented a poorer low-temperature cracking resistance than that from the positive driving performance section. CONCLUSIONS : Current 3DPM equipment can successfully evaluate expressway surface conditions and the corresponding material performance quality. However, more extensive experimental studies are recommended to verify and strengthen the findings of this study

PURPOSES : The purpose of this study was to improve the performance of concrete pavements by measuring the unit-water content with an Internet-of-Things (IoT)-based unit-water content measurement device at an increased precision compared with that of existing measuring equipment. METHODS : We calculated the properties of concrete that varied according to variations in the unit-water content. To confirm the change in the performance of concrete pavements, we compared and analyzed the fatigue cracking rate and international roughness index of concrete pavements at the 20-year point of public use according to the changes in properties using the Korea Pavement Research Program(KPRP). RESULTS : We confirmed that IoT-based measurement equipment can improve the performance of pavements without changing their mixing designs or specifications. We confirmed that the performance of the concrete pavements changed significantly, even with unit-water content variations within the range of quality standards. According to IoT-based unit-water content management, we confirmed that the performance of the concrete pavement (fatigue cracking rate and international roughness index) improved without changing the mixing design. CONCLUSIONS : We confirmed that by using IoT-based unit-water content management, pavement performance can be improved. It is necessary to consider whether the application of this concept to other concrete property management items, such as the chloride content, is possible. Considering the changes in concrete properties according to the unit-water content based on laboratory tests and considerations of various load conditions will be necessary for future research.

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.

PURPOSES : The purpose of this study was to investigate the characteristics of concrete pavement behaviors and performance depending on the group-axle types of heavy vehicles, such as single-, tandem-, and tridem-axles. METHODS : The concrete pavement performance indices (such as the rate of fatigue cracking and surface smoothness) according to the different group-axle types of heavy vehicles were predicted using the Korean pavement design program. It was assumed that the load magnitude was the same for each axle, and that the equivalent single-axle traffic volumes were the same for the different group-axle types. The concrete pavement stresses depending on the different group-axle types of heavy vehicles were also analyzed using a finite element analysis program. RESULTS : Based on the design criteria, the concrete pavement performance was the highest under tandem-axle traffic and lowest under single-axle traffic, although the difference in performance was not significant. Based on the structural analysis criteria, the tensile stress of the concrete pavement was the largest under the single-axle load and smallest under the tridem-axle load when the load magnitude of each axle was the same. CONCLUSIONS : Based on the results obtained from considering both the design and analysis criteria, it was concluded that the groupaxle types (such as the tandem- and tridem-axle configurations of heavy vehicles) would not increase the stress or decrease the performance of concrete pavements relative to the single-axle configuration.