• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.380-388
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• 2014

Annual average daily traffic(AADT) serves as important basic data in the transportation sector. AADT is used as design traffic which is the basic traffic volume in transportation planning. Despite of its importance, at most locations, AADT is estimated using short term traffic counts. An accurate AADT is calculated through permanent traffic counts at limited locations. This study dealt with estimating AADT using various models considering both the spatial correlation and time series data. Kriging models which are commonly used spatial statistics methods were applied and compared with each model. Additionally the External Universal kriging model, which includes explanatory variables, was used to assure accuracy of AADT estimation. For evaluation of various kriging methods, AADT estimation error, proposed using national highway permanent traffic count data, was analyzed and their performances were compared. The result shows the accuracy enhancement of the AADT estimation.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.181-184
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• 2000

In this paper, the design of WDM network using the traffic estimation modeling is implemented. Because of the lack of data of real traffic volumes, the information of statistic data is used. using the modeling results, the WDM channels is assigned for each node, and the network is simulated using OPNET simulation tools. As a result, the realistic WDM network design for Korea topology is proposed.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.127-131
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• 2011

Even if there are no causing factors such as car crash and road works, traffic congestion come from traffic growth on the road. In this case, estimation of traffic flow helps find the solution of traffic congestion problem. In this paper, we present a optimization model which used on traffic equilibrium problem and studied the problem of inverting shortest path sets for complex traffic system. And we also develop pivotal decomposition algorithm for reliability function of complex traffic system. Several examples are illustrated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.639-645
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• 2007

In this study, an estimation of call demand for the internet telephony was carried out using the monthly time-series data from June 2001 to December 2004. In the estimation, the call traffic was assumed to be explained by tariff of the internet telephony service, tariff of fixed and wireless services, income, quality of service, and lagged traffic variable. The traffic is assumed to follow the partial adjustment mechanism. The estimation result shows that the call traffic demand is elastic to the tariff of the service while it is inelastic to the change of income. The qualisty of service is regarded as an important factor of demand. Also there appeared the call demand is adjusting to the change of explanatory variables with some lags.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1375-1378
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• 1997

In this paper, we presents the algorithm which is to recognize the traffic sign on the road the traffic signal in a video image for autonomous navigation. First, the rocognition of traffic sign on the road can be detected using boundary point estimation form some scan-lines within the lane deducted. For this algorithm, index matrix method is used to detemine what sign is. Then, the traffic signal recognition is performed by usign the window minified by several scan-lines which position may be expected. For this algoritm, line profile concept is adopted.

• IE interfaces
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• v.12 no.4
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• pp.625-634
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• 1999

On this study we selected some variable which affect on the estimated of the voice traffic, and estimated daily average traffic by years according to the variables. We applied nonlinear growth curve model to future traffic forecast with estimated historical traffic data. As a result of the forecasting, this study investigates the year in which the internet traffic goes far than the voice traffic.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.109-123
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• 2005

The goals of this paper are two folds: i) to evaluate whether the data collected by a license plate matching AVI equipment being operated on some segment of a national highway are suitable or not for use in travel time estimation of interrupted traffic flows; ii) to study the statistical methodologies to be used for the determination of the optimal aggregation interval for travel time estimation. In this study it was found that the AVI data are not representative because the data are collected on some selected lanes of a roadway where main traffic is thru-traffic and, thus the AVI data are different from those collected from all lanes in traffic characteristics. For the determination of the optimal aggregation interval for travel time estimation. two statistical methods. namely point estimation and interval estimation. were tested. The test shows that the point estimation method is more sensitive and gives more desirable results in determing the optimal aggregation interval than the interval estimation method. And it turned out that the optimal aggregation interval on interrupted traffic flows has been calculated as 5 minute and thus the existing aggregation interval. 5 minute is proper.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.171-182
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• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• Korean Journal of Hazardous Materials
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• v.6 no.2
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• pp.68-76
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• 2018

This study aims to provide a methodological framework to estimate the travel demand of hazardous materials transporting vehicles by link and analyze daily traffic patterns on an expressway to develop safety roadway management strategies. Traffic volume of hazardous material vehicles is counted through the on-site investigation at twenty-five tollgates on the expressway, and their demands by a link are predicted through origin-destination flows estimation. The result shows that the number of the domestic hazardous materials vehicles is approximately 51,207 vehicles per day and it indicates that hazardous materials transport vehicles account for 1.5% of total daily traffic on the internal expressway and 6.2% of total cargo traffic volumes. This study roughly estimated how many hazardous materials vehicles pass through the expressway segment. Thus it is expected to be utilized for establishing a systematic highway management strategy in the future by calculating the traffic volume of the hazardous material vehicles traveling on the interstate expressway.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.2
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• pp.161-167
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• 2008

This paper describes the overview of spectrum requirement estimation recommended in ITU-R Rec. M.1390 and [IMT.METH] and its difference for the IMT mobile service, and a (IMT.METH) methodology is applied to the spectrum estimation of the recent IMT service. The traffic model and traffic calculation algorithm is briefly described for the carried traffic which is determined in terms of the offered traffic, system rapacity, and the criteria of quality of service. And the spectrum requirement demand which is required from year 2010 to year 2015 is calculated as an example for the IMT service which is recently operated and deployed in the current Korean market after obtaining the reasonable market data and the ITU market prediction data.