• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.257-260
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• 2001

As today's network infrastructure continues to grow and DiffServ IP networks ate now available to provide various levels of flexible QoS services. DiffServ guarantees good scalability but shows dynamic QoS dependent on network traffic loads. Therefore, in this paper, we investigate the dynamics of DiffSev QoS and present analytical model to estimate the allowable traffic load under the given network conditions.

• 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 Radiation Protection and Research
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• v.32 no.2
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• pp.79-88
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• 2007

When an accident occurs at nuclear power plant and radionuclide material is released to the area around the plant, public evacuation is considered as a measure to protect the safety of the residents nearby. This study draws factors required to estimate evacuation time and make estimation of the time to evacuate all residents from the EPZ of Wolsong site in consideration of traffic condition in the neighborhood and on the basis of field data around the site for each factor. The traffic capacity and the traffic volume by season were investigated for the traffic analysis and simulation within EPZ of Wolsong site. As a result, the background traffic volume by season were established. To estimate TGT(Trip Generation Time), the questionnaire surveys were carried out for resident and transient. The TSIS code was applied to traffic analysis in the events of daytime/night and normal/adverse weather under normal day/summer peak traffic condition. The results showed that the evacuation time required for total vehicles to move out from EPZ took generally from 118 to 150 minutes. The evacuation time took longer maximum 17 minutes at night than daytime during summer peak traffic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.3
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• pp.171-190
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• 2008

With growing applications of wireless video streaming, an efficient video traffic model featuring modern high-compression techniques is more desirable than ever, because the wireless channel bandwidths are ever limited and time-varying. We propose a modeling and analysis method for video traffic by a class of stochastic processes, which we call '$GEO^Y/G/{\infty}$ input processes'. We model video traffic by $GEO^Y/G/{\infty}$ input process with gamma-distributed batch sizes Y and Weibull-like autocorrelation function. Using four real-encoded, full-length video traces including action movies, a drama, and an animation, we evaluate our modeling performance against existing model, transformed-M/G/${\infty}$ input process, which is one of most recently proposed video modeling methods in the literature. Our proposed $GEO^Y/G/{\infty}$ model is observed to consistently provide conservative performance predictions, in terms of packet loss ratio, within acceptable error at various traffic loads of interest in practical multimedia streaming systems, while the existing transformed-M/G/${\infty}$ fails. For real-time implementation of our model, we analyze G/D/1/K queueing systems with $GEO^Y/G/{\infty}$ input process to upper estimate the packet loss probabilities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.2
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• pp.354-363
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• 1994

This paper describes the method that voice traffic is served efficiently in BISDN. Voice is divided into talkspurt and silent period, and it is possible to transmit olny talksurt by the speech activity detection. This paper described the voice traffic control algorithm in the ATM network where cell discarding method is applied to the embedded ADPCM voice data. For traffic control, the cell discarding was used over low priority cells when it overflows the queue threshold. To estimate the efficiency of traffic control algorithm, the computer simuation was performed with cell loss probability, queue length and mean delay as performance parameters. The embedded ADPCM voice coding and cell disscarding resulted in improving the voice cell traffic efficiency and the dynamic control over network congestion.

• 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 Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.137-149
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• 2019

Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.

• 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.