• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.84-98
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• 1995

Network-based model were developed to predict short term future traffic volume based on current traffic, historical average, and upstream traffic. It is presumed that upstream traffic volume can be used to predict the downstream traffic in a specific time period. Three models were developed for traffic flow prediction; a combination of historical average and upstream traffic, a combination of current traffic and upstream traffic, and a combination of all three variables. The three models were evaluated using regression analysis. The third model is found to provide the best prediction for the analyzed data. In order to balance the variables appropriately according to the present traffic condition, a heuristic adaptive weighting system is devised based on the relationships between the beginning period of prediction and the previous periods. The developed models were applied to 15-minute freeway data obtained by regular induction loop detectors. The prediction models were shown to be capable of producing reliable and accurate forecasts under congested traffic condition. The prediction systems perform better in the 15-minute range than in the ranges of 30-to 45-minute. It is also found that the combined models usually produce more consistent forecasts than the historical average.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.1
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• pp.1-10
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• 1989

The stress history of a bridge is different depending on the characteristic of traffic flow. Because the flow is varied with vehicle type, weight and headway time etc., statistical analysis in bridges is necessary to estimate the history by traffic flow. By applying the statistical analyses in fracture mechanics, the remaining service life of the structure can be estimated. In this paper, 1)the statistical analysis of vehicle type, weight and headway time etc. to analysis randomness of traffic flow, 2)measuring and analysis of stress history of a real bridge, 3)reappearance of stress history by Monte-Carlo Simulation using constitution ratio of vehicle type, weight and headway time as probabilitic variable, 4)comparision of the calculated and modelled stress history, 5)calculation of reduction factor, 6)comparision of frequency of stress range depending on span length etc. were performed. From the results, the basic modelled stress history which is necessary for the method of estimation of the remaining service life of the structure could be suggested.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.13-20
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• 2022

Road conditions and weather conditions are very important factors in the case of traffic accident fatalities in fog and ice sections that occur on roads in winter. In this paper, a simulation was performed to estimate the traffic accident risk rate assuming traffic accident prediction data. In addition, in this paper, in order to reduce traffic accidents and prevent traffic accidents, factor analysis and traffic accident fatality rates were predicted using the WEKA data mining technique and TENSOR FLOW open source data on traffic accident fatalities provided by the Korea Transportation Corporation.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.333-350
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• 1999

Today freeway is thought to be a very important transportation facility carrying tremendous traffic flow as the main corridor within the area of between the areas. However freeway is experiencing severe congestion and accidents by increased entrance ramp flow especially at peak time period. Ramp meters on the freeway entrance ramps that supply traffic to the freeway in a measured or appropriately regulated amount are needed for alleviating freeway congestion. Because ramp meters can be operated to discharge traffic at a measured or regulated rate thus maintaining more uniform speed on the mainline section maximizing the throughput to the freeway within the capacity of a downstream bottleneck and reducing the congestion related accidents. Thus the objectives in this study were to analyze the traffic characteristics on the freeway I-94 with ramp metering system before/after ITS technology in Detroit (Michigan) area compare shifts of the traffic characteristics on the freeway I-94 before/after ITS technology and finally suggest a better ramp metering strategy for the freeway system The following results were obtained: i)Flow occupancies and speeds on the mainline merge section of freeway were shown to be a big difference depending on the peak periods areas and directions based on the distribution of traffic flow characteristics on the freeway. ii)Reduced speed was shown to be more than 5 mph and ramp flow was also shown to be more than 240 vph at peak periods if there was the ramp metering system constructed on the freeway. iii)Ramp metering system was shown to be optimally operated on the freeway if ramp flow could be maximized within the range of over 900 vph and reduced occupancy could be also maximized by no more than 2 percent at peak periods. iv)The average flows on the freeway after the ITS technology were shown to be a decrease of over 20% depending on the peak periods areas and directions when compared with those flow on the freeway before the ITS technology. over 20% depending on the peak periods areas and directions when compared with those speeds on the freeway before the ITS technology. vi)The average metering rates on the freeway after the ITS technology were shown to be an increase of over 10% depending on the peak periods areas and directions when compared with those metering rates on the freeway before the ITS technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1307-1323
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• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.101-116
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• 1996

Increased attention has been paid in recent years to the need of traffic management for alleviating urban traffic congestion. This paper presents a discrete event modeling and simulation framework for analyzing the traffic flow. Traffic simulation models can be classified as being either microscopic and macroscopic models. The discrete event modeling and simulation technique can be basically employed to describe the macroscopic traffic simulation model. To do this, we have employed the System Entity Structure/Model Base (SES/MB) framework which integrates the dynamic-based formalism of simulation with the symbolic formalism of AI. The SES/MB framework supports to hierarchical, modular discrete event modeling and simulation environment. We also adopt the Symbolic DEVS (Discrete Event System Specification) to developed the automated analysis methodology for generating optimal signal light policy. Several simulation tests will demonstrates the techniques.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.21 no.3
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• pp.11-21
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• 2019

The purpose of this study was to present an analysis model for finding the correlation between visibility and evacuation time as users move in the outpatient department of the general hospital. The spatial scope of the study was limited to the first floor and second floor which are used for the outpatient department. Traffic density in outpatient departments was surveyed on site. Based on the surveyed traffic density, the evacuation simulation model was established for calculating the escape route and evacuation time for an individual user. The traffic density of the outpatient department as per the evacuation time was also calculated. With using evacuation simulations, the flow of evacuees was calculated through the density of traffic over the time of evacuation. Visibility data were set in the simulation model for users' escape routes. A correlation analysis between the product of evacuation flow measure and visibility measure of the evacuation population and evacuation time was performed. The analysis result showed negative correlation within a specific distance range. This study presented an analysis model showing that the evacuation condition considering spatial visibility in the outpatient department of general hospital visibility was negatively related to the analyzed evacuation time at the design stage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6B
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• pp.600-607
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• 2011

As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic identification becomes important for the effective use of network resources. In this paper, we present an Internet application traffic identification method based on flow correlation to overcome limitation of signature-based identification methods and to improve performance (completeness) of it. The proposed method can identify unidentified flows from signature-based method using flow correlation between identified and unidentified flows. We propose four separate correlation methods such as Server-Client, Time, Host-Host, and Statistic correlation and describe a flow correlation-based identification system architecture which incorporates the four separate methods. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.7-14
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• 2011

This paper discusses operational technique and effectiveness of Variable Speed Limits system that is implemented to control the traffic-flow on the Naebu Expressway. As the first step of the analysis, traffic data collected from vehicle detectors are corrected and smoothed. Applying a pattern analysis technique to the traffic data, the weekday traffic is classified into four different groups, and median of each group is calculated. Using three state variables, i.e., diverted traffic volume, average density and average speed, the conditions of roadway segments are determined. Computational outputs resulted from the application of the proposed model to the scenarios show that implementation of Variable Speed Limits system improved both safety and efficiency of the expressway. For the operational strategy, this paper also presents the change rate of the speed limit, and the effective duration of the speed limit according to the entering traffic volume.