• Journal of Korean Society of Transportation
• /
• v.22 no.2 s.73
• /
• pp.55-63
• /
• 2004

기존의 설계시간순위 결정은 "순위곡선의 기울기가 완만해지는 지점"이라는 정성적인 기준을 사용하였다. 따라서, 분석자마다 서로 다른 결과를 도출하고 도로 설계시 고려해야하는 두요소(교통혼잡, 경제성)를 전혀 고려하지 못하는 문제점이 있다. 또한 현재의 도로 설계시 대상으로 삼는 시간교통량은 국내 도로의 교통특성이 설, 추석 등의 연휴에 집중적으로 몰리는 등 외국과 그 특성이 상이함에도 불구하고 미국과 동일한 상위 30순위 교통량을 사용한다. 상위 30순위 교통량을 설계시간순위로 하는 경우, 상위 30순위교통량 중 휴일교통량의 비율이 74.1%(설, 추석 연휴 39.7%)로 휴일 집중 교통량의 영향을 크게 받으며, 연중 최대교통량이 용량의 85.2% 에 불과해 도로가 과다 설계된다. 본 연구에서는 목표년도의 연중 최대시간교통량이 용량에 도달하는 순위를 설계시간순위로 하였으며, 분석결과 상위 150순위가 교통혼잡과 도로의 경제성을 모두 고려할 수 있는 설계시간순위로 산정되었다. 설계시간순위를 150순위로 할 경우 현행 설계순위인 30순위에 비해 휴일비율 13.8% 감소, 최대시간교통량의 용량비율($V_1/C_a$) 16.0% 증가의 효과가 있을 것으로 분석되었다. - 현행 설계시간순위(30순위) : 휴일비율 74.1%(설, 추석 비율 39.7%), $V_1/C_a$ 85.2% - 제안 설계시간순위(150순위) : 휴일비율 60.3%(설, 추석비율 23.0%), $V_1/C_a$ 101.2%

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

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.6
• /
• pp.2427-2435
• /
• 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.

• Journal of Korean Society of Transportation
• /
• v.28 no.2
• /
• pp.111-121
• /
• 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.

• Journal of Korean Society of Transportation
• /
• v.21 no.5
• /
• pp.61-71
• /
• 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;.

• Journal of Korean Society of Transportation
• /
• v.27 no.2
• /
• pp.23-34
• /
• 2009

This paper is described as an experimental analysis for the probabilistic directional design hour volume estimation. The main objective of this paper is to derive acceptable design rankings, PK factors, and PD factors. In order to determine an appropriate distribution for acceptable design rankings, 12 probability distribution functions were employed. The parameters were estimated based on the method of maximum likelihood. The goodness of fit test was performed with a Kolmogorov-Smirnov test. The Beta General distribution among the probability distributions was selected as an appropriate model for 2 lane roadways. On the other hand, the Weibull distribution is superior for 4 lanes. The method of the inverse cumulative distribution function came up with an acceptable design ranking of design for LOS D. An acceptable design ranking of 2 lanes is 190, while an acceptable design ranking for 4 lanes is 164. The PK factor and PD factor of 2 lanes was elicited for 0.119 (0.100-0.139) and 0.568 (0.545-0.590), respectively. On the other hand, the PK factor and PD factor for 4 lanes was elicited as 0.106 (0.097-0.114) and 0.571 (0.544-0.598), respectively.

• International Journal of Highway Engineering
• /
• v.9 no.3
• /
• pp.13-20
• /
• 2007

For calculating the number of lane, it is essential to gain the 30th or 100th highest design hourly volume. The design hourly volume obtained from AADT multiplied by design hour factor. In this paper, we developed the regression models fur estimating the 30th highest hour volume and 100th highest hour volume as defined by AADT 50,000 criterion based on the data obtained the 34 monitoring sites in highway. By comparing the performance of the proposed models and conventional models using MAPE, the proposed model for 30th highest design hourly volume reduced the estimator error of 11.83% than that of conventional methods for less than AADT 50,000 and decreased estimation error of 22.17% than that of conventional method for more than AADT 50,000. Moreover, the proposed model for 100th highest design hourly volume reduced the estimator error of 8.16% than that of conventional methods for less than AADT 50,000 and decreased estimation error of 15.25% than that of conventional method for more than AADT 50,000.

• International Journal of Highway Engineering
• /
• v.7 no.4 s.26
• /
• pp.21-30
• /
• 2005

Traffic volume data have been used for the plan, the design, and the operation of highway. Since 1955, traffic survey has been nation- widely carried out at national highway and the regular survey in national highway has been conducted at the intersections of highways. However, it is critical issue to select the priority of the regular survey because it is almost impossible to conduct regular survey at all intersections of national highways. In this study, MCDM(Multiple Criteria Decision Making) using AHP(Analytic Hierarchy Process) was applied to decide the priority of the regular survey. The following standard variables for determining the priority was selected the highway plan variables[AADT, VKT, Peak Hourly Volume, Location of highway from Urban], the highway design variables[Volume(pcu), Directional Traffic Volume, Heavy Vehicle Rate], and the highway operation variables[Speed, Density, V/C]. The standard variables were quantified and normalized. Using the Eigen vector method, the weighted values of each hierarchy based on the pair-wise comparison values from the questionnaire survey were calculated. The selection of the priority of regular survey was dependent on the size of the product of the weighted values for each hierarchy and the normalized values for the standard variables. Finally, the priority of regular survey of the intersections of national highways was determined according to the order in the size of the product of two values.

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

• Journal of Korea Multimedia Society
• /
• v.11 no.8
• /
• pp.1051-1058
• /
• 2008

The advancement of technology for image processing and communications makes it possible for current traffic signal controllers and vehicle detection technology to make both emergency vehicle preemption and transit priority strategies as a part of integrated system. Present]y traffic signal control in crosswalk is controlled by fixed signals. The signal control keeps regular signals traffic even with no traffic, when there is traffic, should wait until the signal is given. Waiting time causes the risk of traffic accidents and traffic congestion in accordance with signal violation. To help reduce the risk of accidents and congestion, this paper explains traffic signal control system for the adaptive priority order so that signal may be preferentially given in accordance with the situation of site through the object detect images.