• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.199-209
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• 2008

This paper is described the concepts and limitations for the traditional directional design hour volume estimation. The main objective of this paper is to establish an estimation method of probabilistic directional design hour volume in order to improve the limitation for the traditional approach method. To express the traffic congestion of specific road segment, this paper proposed the link travel time as the probability that the road capacity can accommodate a certain traffic demand at desired service level. Also, the link travel time threshold was derived from chance-constrained stochastic model. Such successive probabilistic process could determine optimal ranked design hour volume and directional design hour volume. Therefore, the probabilistic directional design hour volume can consider the traffic congestion and economic aspect in road planning and design stage. It is hoped that this study will provide a better understanding of various issues involved in the short term prediction of directional design hourly volume on different types of roads.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.93-99
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• 1999

The service level of Metro stations is affected by the design criteria such as platform area, width and length of stairways, and the number of turnstile, etc. The Korean station design process utilizes peak-hour volume as design volume. Hourly volume, however, can not explicitly account for the variation of traffic and consequently the variation of the level of service within the one-hour time period. Movements in various areas inside of stations are simulated with a queueing network under various operating conditions. A discrete simulation tool called SIMUL8 was utilized. Based on the results, peak volume for 15 minutes period was recommended as a preferred base volume over the peak-hour volume for station design purpose to realistically account for user delays under. Simulation runs also confirmed that escalators have positive effects on passenger processing capacity and on securing stability of passenger flows in stations.

• 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.

• 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.

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

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2D
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• pp.105-111
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• 2010

Operating speed is one of key elements in the design and operation of freeway. Few studies have been carried out macroscopically to find characteristics of free-flow speed (FFS) using small sample size and not considering the conditions of traffic volume and the effects of hour periods. As an attempt to find out the characteristics of FFS, this study microscopically analysed both the distributions of freeway FFS and percentile speeds according to traffic volume and daily hour periods using huge sample size. It was found out that speed distributions are changed and showed different behaviors under the conditions of traffic volumes(1-5 veh/30sec) and daily hour periods(0-5, 6-8, 9-11, 12-19, 20-23). V85(85th percentile speed) at morning, night, and midnight period decreases according to increase in traffic volume respectively, whereas V85 at day time does not show considerable differences. So the behaviors of V85 according to hour periods dramatically changed according to the increase in traffic volume.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.23-30
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• 2006

The variation in the traffic volume on any given roads is the reflection of its user's economic activities and life patterns. And traffic volume flows in every hour usually take different charateristics depending on the location and the function of the roads. This study produced the Monthly Adjustment Factor, Weekly Adjustment Factor and Design hourly Factor, each of which is the index indicating the traffic volume charaterirstics on the highways leading to the recreation areas in the mountainous and seaside tourist sites. Applying these results, it might be possible to calculate the optimal AADT (Annual Average Daily Traffic) and DHV (Design Hour Volume), also be a help to establish a traffic management policy. Finally, it hopes to promote new version of KHCM (Korea Highway Capacity Manual) which includes traffic volume characteristics on recreation areas.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1913-1926
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• 2007

Number of highway lanes and level of service are based on the 30th, 60th or 100th highest hour volume of the target year. On the other hand, railroad design volume is generally expressed in average annual daily traffic (AADT). This procedure ignores attributes of railroad demand's concentration on peak days and hours. Actual data analysis represents railroad's peaking characteristics very similar to those of highways. Therefore it is necessary to set a procedure in selecting design volume for railroad planning. This study presents a concept and the calculating procedure for railroad design hourly volume to analyze effect of railroad investment.

• International Journal of Highway Engineering
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• v.17 no.1
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• pp.91-98
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• 2015

PURPOSES : Although signalized intersections have been considered the best way to control traffic volume in urban areas for several decades, roundabouts are currently being discussed as an alternative way to control traffic volume, especially when traffic is light. Because a roundabout's efficiency depends on the load geometry as well as the traffic volume, design guidelines for roundabouts are recommended only if the incoming traffic volume is very low. It is rare to substitute a roundabout for an existing signalized intersection in urban areas. This study aims to estimate the benefits from the transformation of an existing signalized intersection into a roundabout in an urban area. When there is a more moderate volume of traffic, roundabouts can be effectively used by optimizing signals located at an approaching roadway. METHODS : The methodologies of this paper are as follows: First, a signalized intersection was analyzed to determine the traffic characteristics. Second, the signalized intersection was transformed into a roundabout using VISSIM microscopic traffic simulation. Then, we estimated and analyzed the effects and the performance of the roundabout. In addition, we adjusted a method to improve the benefits of the transformation via the optimization of signals located at an approaching road to control the incoming traffic volume. RESULTS : The results of this research are as follows: The signal-optimized roundabout improved delays compared with the signalized intersection during the morning peak hour, non-peak hour, and evening peak hour by 1.78%, 12.45%, and 12.72%, respectively. CONCLUSIONS : According to the simulation results of each scenarios, the signal-optimized roundabout had less delay time than the signalized intersection. If optimized signal control algorithms are installed in roundabouts in the future, this will lead to more efficient traffic management.