• 한국ITS학회:학술대회논문집
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• v.2006 no.10
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• pp.118-122
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• 2006

• 한국ITS학회:학술대회논문집
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• 2004.11a
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• pp.257-263
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• 2004

• Proceedings of the KOR-KST Conference
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• 2007.02a
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• pp.236-245
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• 2007

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.1 s.9
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• pp.1-12
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• 2006

In order to estimate a dynamic origin and destination demand between on and off-ramps in the freeways, a traffic flow theory can be used to calculate a link distribution proportion of traffics moving between them. We have developed a dynamic traffic estimation model based on the three-phase traffic theory (Kerner, 2004), which explains the complexity of traffic phenomena based on phase transitions among free-flow, synchronized flow and moving jam phases, and on their complex nonlinear spatiotemporal features. The developed model explains and estimates traffic congestion in terms of speed breakdown, phase transition and queue propagation. We have estimated the link, on and off-ramp volumes at every time interval by using traffic data collected from vehicle detection systems in Korea freeway sections. The analyzed results show that the developed model describes traffic flows adequately.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.349-352
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• 2001

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 are assinged for each node, and the network is simulated using OPNET simulation tools. Here, we investigate the shortest routing scheme using OPNET simulation tools. As a result the realistic WDM network design for Korea topology is proposed.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.56-63
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• 1997

Under most system assumptions, closed form solutions of performance measures for ATM switches with input queueing are not available. In this paper, we present expressions and bounds for the derivatives of cell loss probabilities with respect to the arrival rate evaluated at a zero arrival rate. These bounds are used to give an approximation by Taylor expansion, thereby providing an economical way to estimate cell loss probabilities in light traffic.

• Journal of Korea Port Economic Association
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• v.20 no.2
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• pp.151-167
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• 2004

Traditional traffic forecast has employed regression analysis or time-series analysis based on past trends of explanatory variables. However, not existing but planned port facilities do not have historical data for traffic estimation. Consequently, arbitrary traffic allocation has been subject to researcher's intuition. In this paper, container throughput at New Incheon Outer-South Port will be estimated using stated preference(SP) and sample enumeration methodology on the basis of survey data about the choice behaviors of port users in a theoretical situation. In the SP survey, shippers, freight forwarders and carriers were required to answer a choice between two alternative ports: Busan and Incheon. Although total 27 scenarios of questionnaires were constructed with 3 levels of 3 explanatory variables, each interviewee was asked to answer for just 9 scenarios chosen at random. A binary choice logit model was applied to the survey data. The elasticity of travel time is estimated to be very high, implying that building New Incheon Outer-South Port could be effective in relieving the congestion of the Kyungin corridor. The analysis result shows that increasing service level at Incheon Port would bring in the substantial diversion of container cargo in the Capital region to Incheon Port from Busan Port.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.281-291
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• 2017

Nowadays, as traffic jams are a daily elementary problem in both developed and developing countries, systems to monitor, predict, and detect traffic conditions are playing an important role in research fields. Comparing them, researchers have been trying to solve problems by applying many kinds of technologies, especially roadside sensors, which still have some issues, and for that reason, any one particular method by itself could not generate sufficient traffic prediction results. However, these sensors have some issues that are not useful for research. Therefore, it may not be best to use them as stand-alone methods for a traffic prediction system. On that note, this paper mainly focuses on predicting traffic conditions based on a hybrid prediction approach, which stands on accuracy comparison of three prediction models: multinomial logistic regression, decision trees, and support vector machine (SVM) classifiers. This is aimed at selecting the most suitable approach by means of integrating proficiencies from these approaches. It was also experimentally confirmed, with test cases and simulations that showed the performance of this hybrid method is more effective than individual methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.77-86
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• 1993

Recently it is reported in many countries that highway bridges are seriously damaged due to increasing volume of overloaded heavy vehicles. The safety of bridges are highly related to the design load level and the characteristics of extreme load effect induced by traffic loads during its lifetime. The maximum structural load effect during lifetime may be produced by simultaneous loading of trucks with moderate weights on a bridge rather than by single loading of extremely heavy trucks. In this study, a simulation technique to estimate extreme load effect due to traffic loadings has been developed, in which important characteristics of traffic loadings, such as heavy vehicle proportion, traffic mode, vehicle weights, headway distribution. daily traffic volume, etc., should be properly considered. In addition. sensitivity analysis on those factors have been performed.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.157-166
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• 2008

This study proposed a model to estimate traffic accident likelihood using real-time traffic data obtained from freeway traffic surveillance systems. Traffic variables representing spatio-temporal variations of traffic conditions were utilized as independent variables in the proposed models. Binary logistics regression modelings were conducted to correlate traffic variables and accident data that were collected from the Seohaean freeway during recent three years, from 2004 to 2006. To apply more reliable traffic variables, outlier filtering and data imputation were also performed. The outcomes of the model that are actually probabilistic measures of accident occurrence would be effectively utilized not only in designing warning information systems but also in evaluating the effectiveness of various traffic operations strategies in terms of traffic safety.