• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.628-646
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• 2016

This paper proposes a novel channel assignment scheme that is based on finite projective plane (FPP) theory. The proposed scheme involves using a Markov chain model to allocate N channels to N users through intermixed channel group arrangements, particularly when channel resources are idle because of inefficient use. The intermixed FPP-based channel group arrangements successfully related Markov chain modeling to punch through ratio formulations proposed in this study, ensuring fair resource use among users. The simulation results for the proposed FPP scheme clearly revealed that the defined throughput increased, particularly under light traffic load conditions. Nevertheless, if the proposed scheme is combined with successive interference cancellation techniques, considerably higher throughput is predicted, even under heavy traffic load conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1169-1176
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• 2000

In this paper, label assignment schemes considering the IP flow model for the efficient MPLS traffic engineering are proposed and evaluated. Based on the IP flow model, the IP flows are classified into transient flows and base flows. Base flows, which last for a long time, transmit data in high bit rate, and be composed of many packets, have good implications for the MPLS traffic engineering, because they usually cause network congestion. To make use of base flows for the MPLS traffic engineering, we propose two base flow classifiers and label assignment schemes where transient flows are allocated to the default LSPs and base flows to explicit LSPs. Proposed schemes are based on the traffic-driven label triggering method combined with a routing tabel. The first base flow classifier uses both flow size in packet counts and routing entries, and the other one, extending the dynamic X/Y flow classifier, is based on a cut-through ratio. Proposed schemes are shown to minimize the number of labels, not degrading the total cut-through ratio.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.476-488
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• 2016

This study reviewed factors and causes that affect on reliability and accuracy of transportation demand forecasting. In general, the causes of forecasting errors come from variety and irregularity of trip behaviors, data limitation, data aggregation and model simplification. Theoretical understanding about the inevitable errors will be helpful for reasonable decision making for practical transportation policies. The study especially focused on traffic assignment with the KTDB data, and described the factors and causes of errors by classifying six categories such as (1) errors in input data, (2) errors due to spacial aggregation and representation method of network, (3) errors from representing values for variations of traffic patterns, (4) errors from simplification of traffic flow model, and (5) errors from aggregation of route choice behavior.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.97-108
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• 2001

A dynamic transportation management should be applied specially in AM peak because AM peak is more critical than PM peak in traffic volume and demand. AM peak trip can be characterized by commuting and schooling. which have the high level of usage on public transportation, and constraint on arrival time. So transportation management applied in AM peak could deal with a mode choice and an arrival time constrain. Researchers were involved in the dynamic transportation assignment models for management of congested traffic network. But, there were no models which considered a mode choice and an arrival time constrain should be included in management of AM peak. So there are limits to use exist models to control and analyze AM peak traffic. In this study, it is proposed the combined dynamic transportation model, considering a mode choice and the start time selection with arrival time constrains, based on Ran and Boyce's model. The proposed model is verified the compatibility by applying to the newly designed time space expanded network. The result shows that proposed model consistent with dynamic user optimal travel pattern. From this we certificate the applicability of the proposed model to control and analyze AM peak traffic.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.129-147
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• 2002

This paper presents a variational equality formulation by Providing new dynamic route choice condition for a link-based dynamic traffic assignment model. The concepts of used paths, used links, used departure times are employed to derive a new link-based dynamic route choice condition. The route choice condition is formulated as a time-dependent variational equality problem and necessity and sufficiency conditions are provided to prove equivalence of the variational equality model. A solution algorithm is proposed based on physical network approach and diagonalization technique. An asymmetric network computational study shows that ideal dynamic-user optimal route condition is satisfied when the length of each time interval is shortened. The I-394 corridor study shows that more than 93% of computational speed improved compared to conventional variational inequality approach, and furthermore as the larger network size, the more computational performance can be expected. This paper concludes that the variational equality could be a promising approach for real-time application of a dynamic traffic assignment model based on fast computational performance.

• 한국ITS학회:학술대회논문집
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• 2002.11a
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• pp.181-184
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• 2002

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.19-31
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• 2007

When estimating the benefits from an investment project in the transportation sector, errors caused by many factors may exist. This study focuses on user equilibrium traffic assignment methods and stopping criteria. According to previous studies, when using a user equilibrium assignment model, the benefits of travel time savings can be effected by the relative gap value. As the stopping criteria decreases, the time needed for traffic assignment increases, so that lowering the criteria cannot be the best solution. Therefore, an effort is necessary to reduce this change rate and thus improve reliability. This paper considers three methods: reducing the links subject to benefit calculation, extracting sub-area O/D tables and networks, and applying the mean value of successive traffic assignment results. The results of the analysis show that the method using the mean value of five results is more proper than the other methods. Using the sub-area analysis method, if the study area is small the benefits of a project might be over- or under-estimated. This paper used a nationwide O/D table and network at peak time as a case study. The resulting patterns can differ according to basic data to be used in analysis. So further analysis using the data from metropolitan areas are needed.

• Management Science and Financial Engineering
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• v.10 no.2
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• pp.89-102
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• 2004

In this paper, we deal with a processor assignment problem that minimizes the total traffic load of an ATM switch controller by optimally assigning processors to ATM interface units. We develop an integer programming (IP) model for the problem, and devise an effective tabu search heuristic. Computational results reveal the efficacy of the proposed tabu search procedure, finding a good quality solution within 5% of optimality gap.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.143-155
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• 2009

A dynamic traffic assignment (DTA) has recently been implemented in many practical projects. The core of dynamic model is the inclusion of time scale. If excluding the time dimension from a DTA model, the framework of a DTA model is similar to that of static model. Similar to static model, with given exogenous travel demand, a DTA model loads vehicles on the network and finds an optimal solution satisfying a pre-defined route choice rule. In most DTA models, the departure pattern of given travel demand is predefined and assumed as a fixed pattern, although the departure pattern of driver is changeable depending on a network traffic condition. Especially, for morning peak commute where most drivers have their preferred arrival time, the departure time, therefore, should be modeled as an endogenous variable. In this paper, the authors point out some shortcomings of current DTA model and propose an alternative approach which could overcome the shortcomings of current DTA model. The authors substitute a traditional definition for time-dependent OD table by a new definition in which the time-dependent OD table is defined as arrival time-based one. In addition, the authors develop a new DTA model which is capable of finding an equilibrium departure pattern without the use of schedule delay functions. Three types of objective function for a new DTA framework are proposed, and the solution algorithms for the three objective functions are also explained.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.135-150
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• 2002

The basic assumption of analytical Dynamic Traffic Assignment models is that traffic demand and network conditions are known as a priori and unchanging during the whole planning horizon. This assumption may not be realistic in the practical traffic situation because traffic demand and network conditions nay vary from time to time. The rolling horizon implementation recognizes a fact : The Prediction of origin-destination(OD) matrices and network conditions is usually more accurate in a short period of time, while further into the whole horizon there exists a substantial uncertainty. In the rolling horizon implementation, therefore, rather than assuming time-dependent OD matrices and network conditions are known at the beginning of the horizon, it is assumed that the deterministic information of OD and traffic conditions for a short period are possessed, whereas information beyond this short period will not be available until the time rolls forward. This paper introduces rolling horizon implementation to enable a multi-class analytical DTA model to respond operationally to dynamic variations of both traffic demand and network conditions. In the paper, implementation procedure is discussed in detail, and practical solutions for some raised issues of 1) unfinished trips and 2) rerouting strategy of these trips, are proposed. Computational examples and results are presented and analyzed.