• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.1030-1038
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• 2008

Traffic monitoring method is mainly loop detector and piezo sensor. But this method is only detecting the number of vehicle. Monitoring traffic volume is not checking the number of vehicle but checking the length of access road, width of road, number of passing people, passing vehicle, delayed vehicle. The traffic signal control cycle is not fixed by only passing vehicle number but all related traffic proposal. This paper proposed selecting common characteristic out of each unrelated traffic proposal through Analytic Hierachy Process and this characteristic is applied to compose fuzzy sensor algorithm which find out new traffic volume concept of confusion degree. The accumulated delayed vehicle time is shorter in new fuzzy sensor algorithm applied by AHP than other traffic method

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.276-285
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• 2008

Traffic monitoring method is mainly loop detector and piezo sensor. But this method is only detecting the number of vehicle. Monitoring traffic volume is not checking the number of vehicle but checking the length of access road, width of road, number of passing people,passing vehicle,delayed vehicle. The traffic signal control cycle is not fixed by only passing vehicle number but all related traffic proposal. This paper proposed selecting common characteristic out of each unrelated traffic proposal through Analytic Hierachy Process and this characteristic is applied to compose fuzzy sensor algorithm which find out new traffic volume concept of confusion degree. The accumulated delayed vehicle time is shorter in new fuzzy sensor algorithm applied by AHP than other traffic method

• 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.

• International Journal of Highway Engineering
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• v.15 no.6
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• pp.33-39
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• 2013

PURPOSES : This research investigates traffic noise characteristics as change the transverse rumble strips shape from rectangular to cylinder at toll plaza of highway. METHODS : The traffic noise was investigated at two different places at toll plaza of highway. One is modified grooving, another is employed cylinder shape of TRS instead of rectangular shape of TRS. A measurement of traffic noise was conducted at same location and time period. The traffic volume information was gotten from office of highway office and vehicle speed was measured by speed measuring device. The traffic noise measurement was conducted from 13:00 to 23:00 and by pass-by method. Also, the traffic noise was measured behind noise barrier. Various distance from noise barrier(7.5m, 30m, 50m) and different heights(1.2m, 3m, and 5m) were parameter for measurement of traffic noise in this study. RESULTS : The class 1 vehicle was contributed from traffic volume which was increased 1,500. However, the distribution of traffic speed didn't change compare to previous investigated period. From this study, It was found that the external traffic noise was changed as function of geometric shape of TRS. The external noise from modified grooving was less than 1.2dB(A) of the current TRS. A difference of traffic noise was 20dB(A) before and after barrier. It came from a noise barrier effect as reduction of traffic noise. According to investigate a traffic noise distribution near barrier, there is similar noise characteristic as function of height at 7.5m distance from noise barrier. Also, There is no different traffic noise between 30m and 50m from source of the noise of sound barrier. CONCLUSIONS : Based on this traffic noise investigation result, there is a clear characteristic difference as changed TRS shape. The traffic noise was reduced by changed TRS shape. Specially, traffic noise was decreased although the traffic volume was increase for same investigation time and period. It is implied that cylinder type of TRS significantly reduces the traffic noise. The specification of various TRS will be studied in the future.

• Journal of Urban Science
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• v.7 no.1
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• pp.45-54
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• 2018

The purpose of this study is to find the factors that reduce prediction error in traffic volume using highway traffic volume data. The ARIMA model was used to predict the day, and it was confirmed that weekday and weekly characteristics were distinguished by prediction error. The forecasting results showed that weekday characteristics were prominent on Tuesdays, Wednesdays, and Thursdays, and forecast errors including MAPE and MAE on Sunday were about 15% points and about 10 points higher than weekday characteristics. Also, on Friday, the forecast error was high on weekdays, similar to Sunday's forecast error, unlike Tuesday, Wednesday, and Thursday, which had weekday characteristics. Therefore, when forecasting the time series belonging to Friday, it should be regarded as a weekly characteristic having characteristics similar to weekend rather than considering as weekday.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.138-147
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• 2010

As inaccurate traffic volume prediction may result in inadequate transportation planning and design, traffic volume prediction based on traffic volume data is very important in spatial decision making processes such as transportation planning and operation. In order to improve the accuracy of traffic volume prediction, recent studies are using the geostatistical approach called kriging and according to their reports, the method shows high predictability compared to conventional methods. Thus, this study estimated traffic volume data for St. Louis in the State of Missouri, USA using the kriging method, and tested its accuracy by comparing the estimates with actual measurements. In addition, we suggested a new method for enhancing the accuracy of prediction by the kriging method. In the new method, we estimated traffic volume data: first, by applying anisotropy, which is a characteristic of traffic volume data appearing in determining variogram factors; and second, by performing co-kriging analysis using interstate highway, which is in a high spatial correlation with traffic volume data, as a secondary variable. According to the results of the analysis, the analysis applying anisotropy showed higher accuracy than the kriging method, and co-kriging performed on the application of anisotropy produced the most accurate estimates.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.447-454
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• 2007

To assess the port development and maritime traffic environment, the future traffic volume has been estimated using the number of inbound and outbound vessel for a specific port. The estimation of future traffic volume should be considered as an important factor to establish the degree of fairway congestion, the determination of fairway width and the operational role. Until now, the number of in and out vessel for the port has been only estimated mainly, but the type and size of inbound and outbound ships are different depending on the port's characteristics. So, it is difficult to estimate the future traffic volume using the change of only one item. This paper calculates the future traffic volume using the marine traffic characteristic factors as the number of coastal ship and ocean-going ship, the size of ship and the change of cargo volume per a ship etc. And it compared with the results of Artificial Neural Network(ANN) for accurate identification of nonlinear system.

• 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.33 no.3
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• pp.1131-1142
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• 2013

This study aims to verify the applicability of TRANSIMS (TRansportion ANalysis SIMulation System) in interrupted traffic flow through calibration and validation process based on observation data; such as headway, traffic volume, speed, and travel time from Dalguberl Boulevard in Dae-gu metropolitan city. On this study, several micro-simulation parameters are derived from the calibration and validation process through performing a headway comparison and applying an ID back tracking methodology. As a result, it is figured out that actual circumstances of Korean roadway; for example, traffic volume per lane, speed, and travel time, can be applied on the TRANSIMS. Especially, it was possible to find out the influence of cell size parameter to traffic flow characteristic of simulation. However, it is hard to conclude that TRANSIMS is applicable to Korean roadway environment with studying particular target area. Therefore, additional studies; such as more case studies with various types of road, signal, and land use, will be required to localize TRANSIMS to Korea.

• Journal of the Korean Society of Industry Convergence
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• v.5 no.4
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• pp.329-337
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• 2002

It is the actual condition that the increasing traffic delay and accident caused by inefficient management on various construction by occupying the roadways. Since almost roadway improvements are for the public convenient, negative effects by them are ignored. But now due to the increase of traffics demand and limitation of road supply, the positive management scheme and treatment plan on the constructions must be considered. Thus, to the extent of this study divides uninterrupted flow into freeways and the Highway, yielding the time spread between under construction and not, that is delay time, we build capacity and delay model in the change of traffic volume and occupying length.