• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.75-84
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• 2010

Controlled traffic intersection is critical point in terms of transportation network performance, where the most of traffic congestion arises. One of the most important and favorable measure of effectiveness in the signal controlled intersection is approach delay. Although lots of efforts to develop traffic delay estimation models have been made throughout the years, most of them were focusing on homogeneous traffic flow. The purpose of this research is to develop a traffic delay estimation model for traffic flow mixed with bus based on the horizontal shockwave theory. Traffic simulation is performed to test the adaptation level of the model in generic environment. The result shows that the delay increases with increasing bus traffic. Overall model accuracy comparing simulation result is acceptable, that shows the error range around 10 percent.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.57-66
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• 2004

When we estimate an origin-destination matrix from traffic counts. origin-destination matrix estimation from traffic counts according to the selected optimal traffic counting links is method for improving the results of origin-destinaation matrix estimation and for increasing economic efficiency. This paper proposed model of selecting traffic counting links using integer program technique, and selected a traffic counting links using this model, and estimated and origin-destingtion matrix from traffic counts according to the selected optimal traffic counting links. Also, we compared a result of estimating origin-destination matrix from the selected optimal traffic counting links using this model to a result of estimating origin-destination matrix from the randomly selected traffic counting links. The error analysis result was more improved a result of origin-destination matrix estimation using this model than a result of randomly selected links.

• Journal of Korea Port Economic Association
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• v.21 no.4
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• pp.255-274
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• 2005

To acquire a port traffic, governments in North-East Asia have intensively invested port development. Furthermore, the major shipping company directly make a call at northern chinese ports like Qingdao, Dalian and Tianjin. Those changes of port environment will have a considerable effect on a port traffic in Korea. In order to prepare against those changes, it is necessary to estimate a port traffic in Korea A port traffic in Korea is estimated by the use of explanation variables like GDP of Korea, real effective exchange rate, world economic performances and the trade in China, et al. When GDP in Korea goes up 1%, it is estimated that container port traffic of all ports and Pusan Port is upward $1.0{\sim}1.2%$ and $0.8{\sim}0.9%$ respectively. When the trade in China goes up 1%, it is estimated that Container transshipment is upward $1.6{\sim}1.7%$ approximately.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.3
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• pp.257-263
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• 2009

Recently, as the 3G services of Korea have stepped into the developing stage and the traffic has been rapidly increasing, the spectrum requirements have been getting very large. Therefore spectrum reforming is considered actively and firstly exact methodology of spectrum requirement estimation is needed. But existing methodology depends on the future's service forecast than the present substantial data. This paper proposed the exact methodology of spectrum requirement estimation is based on the real data. So this paper analyzed the characteristics of Korean mobile communication traffic based on the real data and the algorithm suitable for estimation of spectrum requirements for 3G mobile communications, and calculated the parameters needed to estimate the spectrum requirements. Based on the traffic parameters of December 2007, simulations to Bet the estimation of annual spectrum requirements were implemented for the two different cases: one of which is 44 % annual increase in the data traffic and the other is 21 % annual increase. The simulation results show 90 MHz for the first case and 60 MHz for the second case in December 2011.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.1-13
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• 2023

This study develops an optimal mobile-communication-based National Highway traffic volume estimation model using an ensemble-based machine learning algorithm. Based on information such as mobile communication data and VDS data, the LightGBM model was selected as the optimal model for estimating traffic volume. As a result of evaluating traffic volume estimation performance from 96 points where VDS was installed, MAPE was 8.49 (accuracy 91.51%). On the roads where VDS was not installed, traffic estimation accuracy was 92.6%.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1373-1380
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• 2014

In order to calculate accurate traffic and traffic speed, qualified and sufficient GPS data should be provided. However, it is difficult to provide accurate traffic information using restricted GPS data from probe vehicles because of communication costs. This paper developed a algorithm that recovers links omitted by restricted GPS data with topology information, and calculate traffic speed with original links and recovered links. T traffic information service of city with a new algorithm can provide more accurate traffic and traffic speed than the original system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.581-588
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• 2002

Precise highway traffic noise simulation and reduction require the accurate data for sound power levels omitted by vehicles, varied to road surface, traffic speed, vehicle types and makers, different from countries to countries. In this study, we have elaboratively measured Korea highway traffic noise and parameters affecting noise levels at the nearside carriageway edge. From numerical simulation using the measured results for highway traffic noise, we propose not only two correction factors to enhance the accuracy of Korea highway traffic sound power estimation using ASJ Model-1998 but also its typical power spectrum according to road surface type. The measured and predicted highway traffic noise levels using the proposed sound power show little difference within 1 dB.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1069-1076
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• 2016

Recent development in visual sensor technologies has encouraged various researches on adding imaging capabilities to sensor networks. Video data are bigger than other sensor data, so it is essential to manage the amount of image data efficiently. In this paper, a new method of video traffic estimation is proposed for efficient traffic management of visual sensor networks. In the proposed method, a first order autoregressive model is used for modeling the traffic with the consideration of the characteristics of video traffics acquired from visual sensors, and a Kalman filter algorithm is used to estimate the amount of video traffics. The proposed method is computationally simple, so it is proper to be applied to sensor nodes. It is shown by experimental results that the proposed method is simple but estimate the video traffics exactly by less than 1% of the average.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.11-19
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• 2012

PURPOSES: The new methodology is proposed for estimation of long-term performance and pavement life based on the national highway database in Daejeon area. Furthermore, this study tried to verify the applicability of performance estimation using NHPCI (National Highway Pavement Condition Index) on tendency of pavement deterioration as time goes by under Korean road environments. METHODS: Reliability theories are applied to estimate the mean life and to determine the appropriate distribution using 3 levels of traffic loads (high, medium, low) based on maintenance and rehabilitation history data for 15 years. RESULTS: As a result, Lognormal distribution is suitable for explanation of pavement lifetime in Daejeon area regardless of traffic loads. In addition, we found that the results of mean life and maintenance timing based on NHPCI for the pavement sections of 3 levels of traffic loads are available. CONCLUSIONS: Based on this study, it was found that mean life of high, medium and low levels of traffic loads are about 8.1 years, 12.2 years and 12.7 years, respectively. Higher level of traffic loads shorten the pavement mean life.