• Title/Summary/Keyword: 설계시간계수

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A Study on Characteristic Design Hourly Factor by Road Type for National Highways (일반국도 도로유형별 설계시간계수 특성에 관한 연구)

  • Ha, Jung-Ah
    • 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.

Estimation of K-factor according to Road Type and Economic Evaluation on National Highway (일반국도의 도로 유형별 설계시간계수 산정 및 경제성 평가)

  • Kim, Tae-woon;Oh, Ju-sam
    • The Journal of the Korea Contents Association
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    • v.15 no.11
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    • pp.582-590
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    • 2015
  • Road type classification and K-factors are important role when design of number of lane. In this study not only classifies road type and estimating of K-factor but also economic evaluation tries for feasibility verification. Road type analysis results, time of day traffic volume variation, weekend-factor and vacation-factor are large in recreation roads. Weekday traffic volume and weekend traffic volume are similar patterns in provincial roads. AADT is high and time of day traffic volume variation is small in urban roads. In this study compares with economic analysis that designing of number of lane between KHCM's K-factor and this study K-factor. Economic analysis results, designed roads by this study's K-factor reduce cost about 4,708 hundred million won. So this study's K-factor is economical on provincial 4 lane roads.

Estimating Design Hour Factor Using Permanent Survey (상시 교통량 자료를 이용한 설계시간계수 추정)

  • Ha, Jung Ah;Kim, Sung Hyun
    • 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.

Design Hourly Factor Estimation with Vehicle Detection System (차량검지기자료를 이용한 고속도로 설계시간계수 산정 연구)

  • Baek, Seung-Geol;Kim, Beom-Jin;Lee, Jeong-Hui;Son, Yeong-Tae
    • 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.

Time series property of the 30th Design Hourly Factors in National Highways (일반국도 30번째 설계시간계수의 시계열적인 특성 분석에 관한 연구)

  • Oh, Ju-Sam;Im, Sung-Man
    • 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.

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Estimation Problem of Design Hour Factor (K) on Urban Expressways and its Improved Direction (도시부 고속도로 설계시간계수(K) 추정방법의 문제점 및 개선방향 제시)

  • Kim, Sang-Gu;Gang, Seon-Uk;Kim, Yeong-Chun;Go, Seung-Yeong
    • Journal of Korean Society of Transportation
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    • v.28 no.2
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    • pp.111-121
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    • 2010
  • DHV (Design-Hour Volume) for the estimation of number of lanes is determined by design-hour factor (K). The design-hour factor is defined as the proportion between the 30th highest hourly volume and AADT and determines the level of road planning. However, the K-factor estimated by an existing method has a problem because the hourly volumes on holiday and weekend appear in the relatively low rank in real world in spite of expected high volumes. To improve this problem, this study make use of the concept of traffic demand in estimating the design-hour factor. After the congested hourly volumes transfer to traffic hourly demand, the K-factors are estimated on urban expressways and are compared to the existing K-factors. It is perceived that the new K-factors have more realistic values due to utilizing the traffic demand. reflecting the congested flow.

An Estimation of Regression Equation for Temporal Distribution of Design Rainfall Using Variable Selection Method (변수선택 방법을 이용한 설계강우량 시간분포 회귀식의 산정)

  • Lee, Sung Ho;Lee, Jae Joon;Park, Jin Hee;Rhee, Dong Sop
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.169-169
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    • 2018
  • 국내에서는 유량자료의 부족으로 수공구조물을 설계하기 위한 기초자료로서 설계강우량을 활용하고 있다. 따라서 설계강우량의 산정 및 시간분포가 중요한 요인으로 작용하고 있으며, 국내에서는 설계강우량 시간분포를 위한 방법으로 Huff의 4분위 방법을 사용하는 것이 일반적이다. 실무에서는 확률강우량도 개선 및 보완연구(Ministry of Land, Transport and Maritime Affairs, 2011)에서 제시한 관측소별 Huff의 무차원 누가우량 백분율을 이용하여 Huff의 4분위 방법 중 3분위의 자료를 이용하여 시간분포 회귀식을 산정하고 있으며, 회귀식의 차수는 전반적으로 결정계수가 높은 6차식을 사용하고 있다. 회귀식의 경우 고차식으로 갈수록 결정계수가 높아지는 것은 당연하지만 4차 이상의 회귀식에서는 결정계수의 차이가 미미하므로 6차식을 사용하는 것이 합리적이라고 할 수 없다. 따라서 본 연구에서는 통계적 유의수준에 기초하여 Huff 4분위 방법의 시간분포 회귀식에 대한 유의성 검정을 실시하여 회귀계수에 대한 통계적 검증을 실시하고 변수선택 방법인 전방선택법(Forward Selection)을 이용하여 유의하지 않은 회귀계수들을 제외하면서 가장 좋은 변수들로 구성된 간결한 설계강우량 시간분포 회귀식을 산정하고자 한다. 또한 산정된 회귀식과 기존 확률강우량도 개선 및 보완연구(Ministry of Land, Transport and Maritime Affairs, 2011)에서 제시한 회귀식과 비교하여 변수선택 방법인 전방 선택법(Forward Selection)을 이용하여 산정된 회귀식의 적합성을 검증하고자 한다.

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Estimating Road Design Hourly Volume via Inflection Point Identification (변곡점 탐색을 통한 도로설계시간계수 산정)

  • Ahn, Seongchae;Choi, Keechoo;Kim, Boowon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.6
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    • pp.2427-2435
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    • 2013
  • Design hourly volume and the K-factor, first proposed by FHWA in the 1950s, is based on the 30th hourly traffic volume during a year (out of 8,760 hours). It was used when surveying the traffic volume was laborious in the past and is still being used now although it leaves some to be desired for practical applications. More reasonable K-factor for better design, based on theoretical evidence, is needed. This paper proposes the knee searching method based on simple linear regression to find out the inflection point of the volume ranking curve that describe the annual 8,760 hourly traffic volumes. The method was applied to the Chungcheong province's national highway, and the results were compared to the existing guidelines' values of K-factors. Identified design hourly traffic volumes ranked between 43rd to 694th, which is much lower than the 30th volume, meaning that some overdesign examples are inevitable if the conventional $30^{th}$ volume is used.

A Study on Improvement of the DDHV Estimating Method (설계시간교통량 산정방법 개선)

  • 문미경;장명순;강재수
    • Journal of Korean Society of Transportation
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    • v.21 no.5
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    • pp.61-71
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    • 2003
  • Existent DDHV draws and is calculating K coefficient. D coefficient from sum of traffic volume two-directions time. There is difference of design order and actuality order, error of DDHV estimation value, problem of irregular change etc. of DDHV thereby. In this study, among traffic volume of each other independent two direction(going up, going down), decide design target order in the directional traffic volume, presented way(way) applying without separating K coefficient and D coefficient at the same time. The result were analysis about national highway permanent count point 360 points 30 orders by existing DDHV estimation value method(separation plan) analysis wave and following variation appear. - design order and actuality order are collision at 357 agencies(99.2%) - actuality order special quality : Measuring efficiency of average 80 orders, maximum 1,027 order, minimum 2 orders - error distribution of design order and actuality order : inside 10 hours is(30$\pm$10hour) 106 points(29.4%), 254 points(70.6%) more than 30 orders and $\pm$10 orders error occurrence be - DDHV estimation value : Average 8.4%, maximum 46.7% The other side, average 50 orders. error improvement effect of DDHV 8.4% was analysed that is at design hourly volume computation by inseparability method in case of AADT premises correct thing because inseparability plan agrees actuality order at whole agency with design order and measuring efficiency of DDHV estimation value is "0".t;0".uot;.

Directional Design Hourly Volume Estimation Model for National Highways (일반국도의 중방향 설계시간 교통량 추정 모형)

  • Lim, Sung-Han;Ryu, Seung-Ki;Byun, Sang-Cheol;Moon, Hak-Yong
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.3
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    • pp.13-22
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    • 2012
  • Estimating directional design hourly volume (DDHV) is an important aspect of traffic or road engineering practice. DDHV on highway without permanent traffic counters (PTCs) is usually determined by the annual average daily traffic (AADT) being multiplied by the ratio of DHV to AADT (K factor) and the directional split ratio (D factor) recommended by Korea highway capacity manual (KHCM). However, about the validity of this method has not been clearly proven. The main intent of this study is to develop more accurate and efficient DDHV estimation models for national highway in Korea. DDHV characteristics are investigated using the data from permanent traffic counters (PTCs) on national highways in Korea. A linear relationship between DDHV and AADT was identified. So DDHV estimation models using AADT were developed. The results show that the proposed models outperform the KHCM method with the mean absolute percentage errors (MAPE).