• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.129-137
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• 2009

Operation of intelligent transport systems technologies in transportation networks and more detailed analysis give rise to necessity of dynamic traffic analysis model. Existing static models describe network state in average. on the contrary, dynamic traffic analysis model can describe the time-dependent network state. In this study, a dynamic traffic model for the expressway system using FTMS data is developed. Time-dependent origin-destination trip tables for nationwide expressway network are constructed using TCS data. Computation complexity is critical issue in modeling nationwide network for dynamic simulation. A subarea analysis model is developed which converts the nationwide O-D trip tables into subarea O-D trip tables. The applicability of the proposed model is tested under various scenario. This study can be viewed as a starting point of developing deployable dynamic traffic analysis model. The proposed model needs to be expanded to include arterial as well without critical computation burden.

• Atmosphere
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• v.22 no.4
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• pp.473-481
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• 2012

The objective methods estimating the radius of maximum wind (RMW) of tropical cyclones (TCs) are discussed using infraed (IR) imagery of geostationary satellite, and an alternative method is suggested that can estimate RMW in the TCs having eyes using IR imagery. The RMW-estimating methods are based on the characteristic structure of the eyewall of a tropical cyclone. RMW is dependent upon the radius of the eye and the distance from the center to the top of the most developed convective cloud. In order to test these methods, blackbody brightness temperature of Korean geostationary satellite, COMS (Communication, Ocean, and Meteorological Satellite) IR imagery are utilized in this study. The estimated RMWs are compared with surface winds of ASCAT (Advanced Scatterometer) of a polar orbiting satellite.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1025-1028
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• 2009

고속도로의 다양한 주행특성으로는 과속하는 차량, 휴게소나 기타목적의 이용차량, 운전자의 습관이나 피로도등이 있는데 이에 따라 고속도로 주행시간에 차이가 나타난다. 하지만 현재에는 이러한 특성을 고려하지 않고 통행시간 분류가 되고 있어 정확성과 신뢰성을 보장하지 못하고 있는 실정이다. 이에 본 연구에서는 데이터 분포에 따른 해석을 통하여 TCS데이터의 특성을 고려 할 수 있는 Fuzzy c-means 알고리즘과 단순히 임의의 초기값으로 분류하는 K-means와의 비교를 통해서 주행특성을 고려한 클러스터링 기법이 경우에 따라서 더 효과적이고 신뢰성 있는 분류방법이 될 수 있음을 증명하였다.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.147-155
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• 2005

The purpose of this paper is to develop a method for estimation of reliable path-travel time using data obtained from the toll collection system on freeways. The toll collection system records departure and arrival time stamps as well as the identification numbers of arrival and destination tollgates for all the individual vehicles traveling between tollgates on freeways. Two major issues reduce accuracy when estimating path-travel time between an origin and destination tollgate using transaction data collected by the toll collection system. First, travel time calculated by subtracting departure time from arrival time does not explain path-travel time from origin tollgate to destination tollgate when a variety of available paths exist between tollgates. Second, travel time may include extra time spent in service and/or rest areas. Moreover. ramp driving time is included because tollgates are installed before on-ramps and after off-ramps. This paper describes an algorithm that searches for arrival time when departure time is given between tollgates by a Progressive Iterative Forward and Backward (PIFAB) search method. The algorithm eventually produces actual path-travel times that exclude any time spent in service and/or rest areas as well as ramp driving time based on a link-based procedure.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.205-215
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• 2008

As static traffic assignment has reached its limitation with ITS policy applications and due to the increase of interest in studies of ITS policies since the late 1980's, dynamic traffic assignment has been considered a tool to overcome such limitations. This study used the Dynameq program, which simulates route choice behavior by macroscopic modeling and dynamic network loading and traffic flow by microscopic modeling in consideration of the feasibility of the analysis of practical traffic policy. The essence of this study is to evaluate the feasibility for analysis in practical transportation policy of using the dynamic traffic assignment technique. The study involves the verification of the values estimated from the dynamic traffic assignment with South Korea's expressway network and dynamic O/D data by comparing results with observed link traffic volumes. This study used dynamic O/D data between each toll booth, which can be accurately obtained from the highway Toll Collection System. Then, as an example of its application, exclusive bus-lane policies were analyzed with the dynamic traffic assignment model while considering hourly variations.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.51-61
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• 2002

In this dissertation, We demonstrated the Travel Time forecasting model in the freeway of multi-section with regard of drives' attitude. Recently, the forecasted travel time that is furnished based on expected travel time data and advanced experiment isn't being able to reflect the time-lag phenomenon specially in case of long distance trip, so drivers don't believe any more forecasted travel time. And that's why the effects of ATIS(Advanced Traveler Information System) are reduced. Therefore, in this dissertation to forecast the travel time of the freeway of multi-section reflecting the time-lag phenomenon & the delay of tollgate, we used traffic volume data & TCS data that are collected by Korea Highway Cooperation. Also keep the data of mixed unusual to applicate real system. The applied model for forecasting is consisted of feed-forward structure which has three input units & two output units and the back-propagation is utilized as studying method. Furthermore, the optimal alternative was chosen through the twelve alternative ideas which is composed of the unit number of hidden-layer & repeating number which affect studying speed & forecasting capability. In order to compare the forecasting capability of developed ANN model. the algorithm which are currently used as an information source for freeway travel time. During the comparison with reference model, MSE, MARE, MAE & T-test were executed, as the result, the model which utilized the artificial neural network performed more superior forecasting capability among the comparison index. Moreover, the calculated through the particularity of data structure which was used in this experiment.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.151-162
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• 2002

The object of this study is to develop an operating time prediction model for expressways using toll collection data. A Prediction model based on modular neural network model was developed and tested using real data. Two toll collection system(TCS) data set. Seoul-Suwon section for short range and Seoul-Daejeon section for long range, in Kyongbu expressway line were collected and analyzed. A time series analysis on TCS data indicated that operating times on both ranges are in reasonable prediction ranges. It was also found that prediction for the long section was more complex than that for the short section. However, a long term prediction for the short section turned out to be more difficult than that for the long section because of the higher sensitivity to initial condition. An application of the suggested model produced accurate prediction time. The features of suggested prediction model are in the requirement of minimum (3) input layers and in the ability of stable operating time prediction.

• Korean Journal of Environmental Agriculture
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• v.30 no.1
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• pp.82-88
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• 2011

BACKGROUND: Tetracyclines (TCs) are mainly regulated as parent compounds by bioactivity-based screening methods in food. Especially with respect to antimicrobial residues, their metabolites/epimers are also highly concerning chemicals and traditionally applied microbial detection methods are needed to improve with validation for regulatory control. METHODS AND RESULTS: Detection capability and biological activity of tetracycline (TC), chlortetracycline (CTC), oxytetracycline (OTC) and their epimers; anhydrotetracycline (ATC), epianhydrotetracycline (EATC), epitetracycline (ETC), 4-epi-chlortetracycline (ECTC), 4-epianydrochlotetra-cycline (EACTC), 4-epioxychlortetracycline (EOTC), were measured by microbial growth inhibition screening method of Korea Food Code. CONCLUSION(S): Limited detection capabilities were found, B. megarerium and B. subtilis showed for TC and CTC, and B. subtilis for OTC. Biological potency of each epimer was also presented against various microorganisms, at the level from 50% to 96%, comparing with parent TCs. It is recommended that more advanced microbial screening methods with validation are needed, and biologically active epimers are to be considered as marker residues for MRL setting of regulatory control purpose.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.99-108
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• 2014

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.525-544
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• 2017

With the advent of the big data era, the interest in the development of land using traffic data has increased significantly. However, the current research on traffic big data lingers around organizing or calibrating the data only. In this research, a novel method for discovering the hidden values within the traffic data through data mining is proposed. Considering the fact that traffic data and network structures have similarities, network analysis algorithms are used to find valuable information in the actual traffic volume data. The PageRank and HITS algorithms are then employed to find the centralities. While conventional methods present centralities based on uncomplicated traffic volume data, the proposed method provides more reasonable centrality locations through network analysis. Since the centrality locations that we have found carry detailed spatiotemporal characteristics, such information can be used as an objective basis for making policy decisions.