• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.459-473
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• 2007

In this paper, we suggest a spatial regression model to predict AADT. Although Euclidian distances between one monitoring site and its neighboring sites were usually used in the many analysis, we consider the shortest travel path between monitoring sites to predict AADT for unmonitoring site using spatial regression model. We used universal Kriging method for prediction and found that the overall predictive capability of the spatial regression model based on shortest travel path is better than that of the model based on multiple regression by cross validation.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.57-65
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• 2018

PURPOSES : The study aims to predict the service life of national highway asphalt pavements through deep learning methods by using maintenance history data of the National Highway Pavement Management System. METHODS : For the configuration of a deep learning network, this study used Tensorflow 1.5, an open source program which has excellent usability among deep learning frameworks. For the analysis, nine variables of cumulative annual average daily traffic, cumulative equivalent single axle loads, maintenance layer, surface, base, subbase, anti-frost layer, structural number of pavement, and region were selected as input data, while service life was chosen to construct the input layer and output layers as output data. Additionally, for scenario analysis, in this study, a model was formed with four different numbers of 1, 2, 4, and 8 hidden layers and a simulation analysis was performed according to the applicability of the over fitting resolution algorithm. RESULTS : The results of the analysis have shown that regardless of the number of hidden layers, when an over fitting resolution algorithm, such as dropout, is applied, the prediction capability is improved as the coefficient of determination ($R^2$) of the test data increases. Furthermore, the result of the sensitivity analysis of the applicability of region variables demonstrates that estimating service life requires sufficient consideration of regional characteristics as $R^2$ had a maximum of between 0.73 and 0.84, when regional variables where taken into consideration. CONCLUSIONS : As a result, this study proposes that it is possible to precisely predict the service life of national highway pavement sections with the consideration of traffic, pavement thickness, and regional factors and concludes that the use of the prediction of service life is fundamental data in decision making within pavement management systems.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.79-88
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• 2007

Design Hourly Volume (DHV) is the hourly volume used for designing a section of road. DHV is also used to estimate the expected number of vehicles to pass or traverse the relevant section of road in a future target year. The Design Hour Factor (DHF) is defined as the ratio of DHV to Average Annual Daily Traffic (AADT). In addition to high precision of predicted traffic volume, in order to design a roadway to be the proper scale, applying appropriate DHFs considering traffic flow characteristics and type of area which surrounds the relevant roadway is important. This study categorizes sections of expressway (Suh Hae An Expressway) according to their area type and estimates DHFs utilizing traffic data obtained from a vehicle detection system (VDS). This study shows that DHFs calculated using VDS data are different from those using traffic data acquired from a coverage survey. While AADTs from both data show similar values, peak hour volumes from both data show significant differences especially for recreational areas. DHFs from the coverage survey are quite different from the values provided by the Korean design guide or previous research results and DHFs for urban areas are higher than recreational areas. However, DHFs from VDS shows similar values to previous research results. The result of this study suggests that using VDS for estimating DHFs is more reliable than using a coverage survey.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.59-68
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• 2002

AADT(Annual Average Daily Traffic) can be obtained by using short-term counted traffic data rather than using traffic data collected for 365 days. The process is a very important in estimating AADT using short-term traffic count data. Therefore, There have been many studies about estimating AADT. In this Paper, we tried to improve the process of the AADT estimation based on the former AADT estimation researches. Firstly, we found the factor showing differences among groups. To do so, we examined hourly variables(divided to total hours, weekday hours. Saturday hours, Sunday hours, weekday and Sunday hours, and weekday and Saturday hours) every time changing the number of groups. After all, we selected the hourly variables of Sunday and weekday as the factor showing differences among groups. Secondly, we classified 200 locations into 10 groups through cluster analysis using only monthly variables. The nile of deciding the number of groups is maximizing deviation among hourly variables of each group. Thirdly, we classified 200 locations which had been used in the second step into the 10 groups by applying statistical techniques such as Discriminant analysis and Neural network. This step is for testing the rate of distinguish between the right group including each location and a wrong one. In conclusion, the result of this study's method was closer to real AADT value than that of the former method. and this study significantly contributes to improve the method of AADT estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.487-493
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• 2017

The main purpose of this study is to evaluate the main parameters involved in the asphalt pavement distresses, including IRI (International Rough Index), fatigue, and permanent deformation. The main parameters are the region (Seoul and Busan), traffic level, asphalt binder, maximum aggregate of surface course, thickness of the surface course and base. A total of 64 case studies were carried out under the auspices of the KPRP (Korea Pavement Research Program). From the analysis of the KPRP test results, the key factors for the asphalt pavement distress were determined. Considering the effect of one variable in the basic condition, asphalt binder was the major factor having an effect on the distresses for an AADT (Annual Average Daily Traffic) of 5000 in the Seoul area. Among the remaining factors, the results were found to be in the order of the base layer thickness (A), surface layer thickness (B), and aggregate particle size thickness (D). The same results were obtained for an AADT of 10000. In the case of Busan with an AADT of 5000, the same result was obtained as for Seoul. Among the remaining factors, the results were in the order of the base layer thickness (A), aggregate particle thickness (D), and surface layer thickness (B). Even though there was a slight difference in the effect of the traffic level and region, asphalt binder was the parameter having the greatest effect on the asphalt pavement distress. In the case where the effect of multiple parameters was analyzed, the combination of the asphalt binder and base thickness showed a relatively strong effect.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.52-62
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• 2013

Design Hourly Factor(DHF) is defined as the ratio of design hourly volume(DHV) to Average Annual Daily Traffic(AADT). Generally DHV used the 30th rank hourly volume. But this case DHV is affected by holiday volumes so the road is at risk for overdesigning. Computing K factor is available for counting 8,760 hour traffic volume, but it is impossible except permanent traffic counts. This study applied three method to make DHF, using 30th rank hourly volume to make DHF(method 1), using peak hour volume to make DHF(method 2). Another way to make DHF, rank hourly volumes ordered descending connect a curve smoothly to find the point which changes drastic(method 3). That point is design hour, thus design hourly factor is able to be computed. In addition road classified 3 type for national highway using factor analysis and cluster analysis, so we can analyze the characteristic of DHF by road type. DHF which was used method 1 is the largest at any other method. There is no difference in DHF by road type at method 2. This result shows for this reason because peak hour is hard to describe the characteristic of hourly volume change. DHF which was used method 3 is similar to HCM except recreation road but 118th rank hourly volume is appropriate.

• International Journal of Highway Engineering
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• v.16 no.1
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• pp.11-19
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• 2014

PURPOSES : The purpose of this article is to investigate the predicted life of jointed concrete pavement (JCP) with two variables effecting on axle load spectra (ALS). The first variable is different data acquisition methods whether using high-speed weigh-in-motion (HS-WIM) or not and the other one is spectra distribution due to overweight enforcement on main-lane of expressway using HS-WIM. METHODS : Three sets of ALS had been collected i) ALS provided by Korea Pavement Research Program (KPRP), which had been obtained without using HS-WIM ii) ALS collected by HS-WIM before the enforcement at Kimcheon and Seonsan site iii) ALS collected after the enforcement at the same sites. And all ALS had been classified into twelve vehicle classes and four axle types to compare each other. Among the vehicle classes, class 6, 7, 10 and 12 were selected as the major target for comparing each ALS because these were considered as the primary trucks with a high rate of overweight loading. In order to analyze the performance of JCP based on pavement life, fatigue crack and International Roughness Index (IRI) were predicted using road pavement design program developed by KPRP and each ALS with same annual average daily traffic (AADT) was applied to design slab thickness. RESULTS : Comparison ALS of KPRP with those of HS-WIM shows that the ALS of KPRP has a low percentage of heavy spectra such as 6~9 tonnes for single axle, 18~21 tonnes for tandem axle and 27~30 tonnes for tridem axle than other two ALS of HS-WIM in most vehicle classes and axle types. It means that ALS of KPRP was underestimated. And after the enforcement, percentage of heavy spectra close to 10 tonnes per an axle are lowered than before the enforcement by the effect of overweight enforcement because the spectra are related to overweight regulation. Prediction results of pavement life for each ALS present that the ALS of HS-WIM collected before the enforcement makes the pavement life short more than others. On the other hand, the ALS of KPRP causes the longest life under same thickness of slab. Thus, it is possible that actual performance life of JCP under the traffic like ALS of HS-WIM could be short than predicted life if the pavement was designed based on ALS provided by KPRP. CONCLUSIONS : It is necessary to choose more reliable and practical ALS when designing JCP because ALS can be fairly affected by acquisition methods. In addition, it is important to extend performance life of the pavement in service by controlling traffic load such as overweight enforcement.

• International Journal of Highway Engineering
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• v.17 no.4
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• pp.69-75
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• 2015

PURPOSES : The hydrated lime-modified asphalt, which improves moisture resistance, is normally used for pavements to reduce the number of potholes. However, the method of applying the material properties of the lime-modified asphalt mixture for use in pavements is not covered in the Korean Pavement Research Program (KPRP). The objective of this research is to find a method for the design application of lime-modified asphalt's material properties to the KPRP. METHODS: The section for test design is selected in some conditions which are related to the level of design regarding Annual Average Daily Traffic (AADT). To define the application methods of hydrated lime in the KPRP, the models of fatigue, rut and international roughness index (IRI) are determined based on the M-EPDG test results from some earlier research results. Moreover, it is well known that dynamic moduli of the unmodified mixture are not different from those of the lime-modified mixture. RESULTS: The performance results of hydrated lime-modified asphalt pavement were not very much different from those of the unmodified pavement, which meant the limited design regulations regarding fatigue failure, rutting deformation and IRI. CONCLUSIONS: The KPRP uses the weather model from the data for previous 10 years. It implies that the KPRP cannot predict abnormal climate changes accurately. Hence, the predictive weather data regarding the abnormal climate changes are unreliable. Secondly, the KPRP cannot apply the moisture resistance of asphalt mixtures. Therefore, a second level of design study will have to be performed to reflect the influence of moisture. It means that the influence on pavement performance can be changed by the application of hydrated lime in asphalt mixture design.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.4
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• pp.367-374
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• 2002

Maintainability of highways is an important problem that is considered in the planning steps of a highway development process. A number of asset management systems have been developed to precisely predict maintenance and pavement expenditures for better decision making, But these systems are not helpful in reducing maintenance costs. Optimization of some highway design characteristics in the planning phases may reduce maintenance costs over the life cycle of highway. The formulations for initial and maintenance costs have been developed based on which design variables can be chosen to minimize these costs, focusing on the sideslope in cut and fill sections. Maintenance cost has been represented as a function of sideslope, width of highway cross section, and annual average daily traffic. A real geographic database of between Chung joo and Sang joo city in Choong buk was used and it is presented to investigate the sensitivities of maintenance cost and soil characteristics in selecting alignments. In this study, we present that maintenance cost and soil characteristics are important considerations in alignment optimization.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.91-99
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• 2013

PURPOSES : This study aims at proposing the methodology for benefit evaluations in pavement maintenance methods and timings using KoPMS(Korean Pavement Management System) software which was developed for efficient pavement management. METHODS : This study classified pavement sections into 4 clusters considering AADT(Annual Average Daily Traffic) and ESAL(Equivalent Single-Axle Load) using cluster analysis and used the deterioration models in each cluster. Increased user costs due to pavement deterioration as time goes by and agent costs for maintenance were estimated. Based on deterioration model and KoPMS software, Methodology for benefit evaluation was proposed in pavement maintenance methods and with/without implementation using real pavement section data. RESULTS : This study verified that considering agent costs only would be constrained to decide pavement maintenance methods and timings, and ascertained that decision making with agent and user costs would be effective. In addition, this study revealed that pavement maintenance methods and timings can be affected by AADT and ESAL and frequent pavement maintenances can be more efficient for benefits in pavement sections with more AADT and ESAL. Also this study found that user costs would be more affected to decision making than agent costs. Moreover, Delay of conducting pavement maintenance caused increased vehicle operating costs and environmental costs because of poor conditions of pavements. CONCLUSIONS : This study proposed LCCA and benefit estimation methodology of pavement with considering agent and user costs. The results of this study can be used for baseline data of efficient pavement asset management.