• International Journal of Highway Engineering
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• v.9 no.4
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• pp.1-9
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• 2007

To decide the number of road lane is very important and related to the 30th design hourly factor in the design of transportation facilities. But, as the quantitative division of road types is difficult, most planner and designer for deciding the 30th design hourly factors have used the fixed values in our country. In this study, we have analyzed the time series property of the design hourly factors in national highways and developed the model capable of estimating the 30th design hourly factors using real data. The presented model is a simple regression model(DHV = K*AADT), which is applied to the division of road lanes(2 or 4 lanes) and the level of AADT(3 levels). As a results, the simple regression model have better performance than the existing method with respect to MAPE and $R^2$. Also, the variations of the 30th design hourly factors are small. The more traffic volume increase, the more the factors decrease. But, the limitation of this study is to use the exiting method estimating the values of the factors, it is subject to study hereafter.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.11-16
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• 2009

The estimation of total travel time on highway link for a day or year is the most important process for the feasibility analysis of highway or railway. Most of current guidelines for feasibility studies have been based on the time-traffic volume relationship from the BPR, and the traffic volumes have been determined by the application of the design hour factor to the annual average daily traffic volume. Both of the BPR function and the application of the design hour volume may result in the over-estimation of travel time due to the fact that the traffic volume on the large portion of highway links in Korea are close to the capacities. This study proposed a new way which is based on the distribution of hourly volumes for a year. It could be closer to the real situation, and provide more reasonable estimation. This methodology was validated for the national highways, but may be applicable for any type of highway with the AADT.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.32-38
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• 2018

Studies on classification of national roads have been continued, but there is little research on the classification of urban arterial roads. Due to the increase of traffic volume, urban arterial roads do not perform well as main roads. In this paper, the function of urban arterial road was established by using cluster analysis using traffic characteristics. Traffic characteristics such as traffic volume, weekend coefficient and speed coefficient were used to establish the functions of 55 main arterial roads in Seoul. The results of this paper are compared with those of the method using AADT. The method using AADT classifies the characteristics according to the traffic volume of the whole lane. In this paper, however, the results are derived using the traffic volume per lane reflecting the actual traffic volume. In addition, the functional classification of the arterial roads in Seoul was compared with the results of this paper to verify that the traffic characteristics were reflected. As a result, the method presented in this paper is more effective in showing traffic characteristics than the current highway functional classification method, and the functional classification system will be helpful for road extension and planning design.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.406-414
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• 2015

Existing relative researches for traffic were studied under favorable weather or excluding impact of weather. This study present traffic volume variation according to rainfall intensity in national highway provincial road and rainfall-factor. Continuous traffic count section match AWS after selecting to analyze provincial road 256 section. Weekdays ADT(Average Daily Traffic) and rainfall-factor are influenced by rainfall a little because of business travel. But non-weekdays ADT and rainfall-factor are influenced much more than weekdays because of leisure travel. Estimated AADT(Annual Average Daily Traffic) by adjusting rainfall-factor is lower MAPE than non-adjusting rainfall factor. So, rainfall have to be considered when estimating AADT. ADT decrease according to rainfall intensity, continuous studies considered rainfall intensity are needed when road design and operation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.155-162
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• 2008

This study shows how to estimate the design hour factor when the counting stations don't have all of the hourly volumes such as in a coverage survey. A coverage survey records traffic volume from 1 to 5 times in a year so it lacks the detailed information to calculate the design hour factor. This study used the traffic volumes of permanent surveys to estimate the design hour factor in coverage surveys using correlation and regression analysis. A total 7 independent variables are used : the coefficient of variance of hourly volume, standard deviation of hourly volume, peak hour volume, AADT, heavy traffic volume proprotion, day time traffic volume proportion and D factor. All of variables are plotted on a curve, so it must use non-linear regression to analyze the data. As a result the coefficient of determination and MAE are good at logarith model using AADT.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.759-766
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• 2008

Road classification system is the first step for determining the road function and design standards. Currently, roads are classified by various indices such as road location and function. In this study, we classify road using various traffic indices as well as to identify traffic characteristics for each type of road. To accomplish the objectives, mixture model was applied for classifying road and analyzing traffic characteristics using traffic data that observed at permanent traffic count stations. A total of 8 variables were applied: annual average daily traffic(AADT), $K_{30}$ coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and coefficient of variation(COV). A total of 350 permanent traffic count points were categorized into three groups : Group I (Urban road), Group II (Rural road), and Group III (Recreational road). AADT were 30,000 for urban, 16,000 for rural, and 5,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.

• 한국도로학회:학술대회논문집
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• 2004.10a
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• pp.355-362
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• 2004

• 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.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.120-129
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• 2016

The user cost is an important analysis item which should be considered together with life-cycle of facility, administrator cost and discount rate in LCCA for efficient asset management of SOC facilities. Especially, a significant delay cost occurs often for users in the road field due to a work zone for cleaning and maintenance, and in such case, the administrator should consider the administrator cost as well as the user cost for more rational decision making. However, the user cost has not been considered in most decision making steps until recently and relevant studies also have not been carried out actively. In this study, the methodology to estimate the user cost and delay cost required in the decision making step using the traffic flow model and the direct benefit estimation model in the traffic facility investment evaluation guideline is suggested. And, the traffic flow model was estimated on 4 national highway sections where maintenance was actually carried out in 2014 using VISSIM and, the user cost and the delay cost were estimated based on the suggested methodology. The analysis result showed that the average user cost of $17,569,000KRW/km{\times}day$ occurred on Section A with approximately 30,000 AADT before a work zone occurred, and in case the first lane was blocked for maintenance, the delay cost of $10,193,000KRW/km{\times}day$ (158%) on average occurred additionally. The delay cost of $1,507,000KRW/km{\times}day$ (115%) and $1,985,000KRW/km{\times}day$ (119%) occurred on Sections B and D with approximately 20,000 AADT respectively and the delay cost of $262,000KRW/km{\times}day$ (105%) occurred on Section C with approximately 10,000 AADT. This result of this study was estimated based on the simulation of traffic flow model so that there is a limitation in its actual application. A study ot develop a highly appropriate model using actual observation data and improve the possibility to apply it through the verification using the simulation will be necessary in future.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.131-144
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• 2002

도로의 그룹핑(Grouping)이란 도고 계획, 설계, 관리, 조사 계획 및 정비 방침 등을 세우기 위해 유사한 성격의 도로 구간을 군집화하는 방법이다. 기존에 일반적으로 적용되고 있는 도로 그룹핑 방법은 그룹 수를 미리 지정함으써 분석가의 주관적 판단이 개입되었고, 그룹핑 변수 선정에 대한 근거가 부족하였다. 이에 본 연구에서는 기존에 일반적으로 적용되고 있는 도로 그룹핑 방법을 개선하여 새로운 방법론을 제시하였다. 또한 새로 제시된 방법론의 검증을 위해 도로 교통량 통계연보에서 제공하고 있는 일반국도의 2000년 294개 상시조사 지전의 교통량 자료를 이용하여 분석하였다. 연구 결과 기존의 월, 요일 변동계수만을 적용한 그룹핑 방법보다는 기타 교통지표(AADT, $\Sigma$K1000(K값의 상위 1000번 순위까지의 누적 값), 중차량 비율, 주야율)를 동시에 적용할 때 좀 더 효율적이면서 세부적으로 분류됨을 알 수 있었다. 또한 기타 교통지표론 적당한 그룹핑 결과로는 5그룹의 국도 기능 분류가 가능함을 알 수 있었다. 그 결과 기존의 소재지역과 기능에 따른 국토의 구분을 지방 산업도로 그룹, 지역 간선도로 그룹, 대도시 주변형 도로 그룹, 중소도시 주변형 및 관광도로 그룹, 관광도로 그룹으로 분류할 수 있었다. 본 연구에서의 도로 그룹핑 결과에 각 지역특성을 추가하여 분석한다면 도로의 계획, 선계, 관리 등에 매우 유용한 자료로 활용되리라 예상한다. 또한 본 연구의 결과를 이용하면 좀 더 효율적으로 설계시간계수 선정, 전역 조사 지점의 AADT추정, 상시 교통량 조사 자료의 누락 데이터 보정 및 교통량 조사의 스케줄링에 많이 활용할 수 있을 것으로 기대된다.