• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.113-130
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• 2002

In this paper, we developed DNL(Dynamic Network Loading) model based on Moving cell theory to analyze the dynamic characteristics of traffic flow in congested network. In this paper vehicles entered into link at same interval would construct one cell, and the cells moved according to Cell following rule. In the past researches relating to DNL model a continuous single link is separated into two sections such as running section and queuing section to describe physical queue so that various dynamic states generated in real link are only simplified by running and queuing state. However, the approach has some difficulties in simulating various dynamic flow characteristics. To overcome these problems, we present Moving cell theory which is developed by combining Car following theory and Lagrangian method mainly using for the analysis of air pollutants dispersion. In Moving cell theory platoons are represented by cells and each cell is processed by Cell following theory. This type of simulation model is firstly presented by Cremer et al(1999). However they did not develop merging and diverging model because their model was applied to basic freeway section. Moreover they set the number of vehicles which can be included in one cell in one interval so this formulation cant apply to signalized intersection in urban network. To solve these difficulties we develop new approach using Moving cell theory and simulate traffic flow dynamics continuously by movement and state transition of the cells. The developed model are played on simple network including merging and diverging section and it shows improved abilities to describe flow dynamics comparing past DNL models.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2484-2496
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• 2000

High speed switches have been developing to interconnect a large number of nodes. It is important to analyze the switch performance under various conditions to satisfy the requirements. Queueing analysis, in general, has the intrinsic problem of large state space dimension and complex computation. In fact, The petri net is a graphical and mathematical model. It is suitable for various applications, in particular, manufacturing systems. It can deal with parallelism, concurrence, deadlock avoidance, and asynchronism. Currently it has been applied to the performance of computer networks and protocol verifications. This paper presents a framework for modeling and analyzing ATM switch using stochastic activity networks (SANs). In this paper, we provide the ATM switch model using SANs to extend easily and an approximate analysis method to apply A TM switch models, which significantly reduce the complexity of the model solution. Cell arrival process in output-buffered Queueing A TM switch with finite buffer is modeled as Markov Modulated Poisson Process (MMPP), which is able to accurately represent real traffic and capture the characteristics of bursty traffic. We analyze the performance of the switch in terms of cell-loss ratio (CLR), mean Queue length and mean delay time. We show that the SAN model is very useful in A TM switch model in that the gates have the capability of implementing of scheduling algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.233-239
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• 2006

Most research for until at now link travel time were research for mean link travel time calculate or estimate which uses the average of the individual vehicle. however, the link travel time distribution is divided caused by with the impact factor which is various traffic condition, signal operation condition and the road conditional etc. preceding study result for link travel time distribution characteristic showed that the patterns of going through traffic were divided up to 2 in the link travel times. therefore, it will be more accurate to divide up the link travel time into the one involving delay and the other without delay, rather than using the average link travel time in terms of assessing the traffic situation. this study is it analyzed transit hour distribution characteristic and a cause using examine to the variables which give an effect at link travel time distribute using simulation program and determinate link travel time distribute ratio estimation model. to assess the distribution of the link travel times, this research develops the regression model and the fuzzy model. the variables that have high level of correlations in both estimation models are the rest time of green ball and the delay vehicles. these variables were used to construct the methods in the estimation models. The comparison of the two estimation models-fuzzy and regression model- showed that fuzzy model out-competed the regression model in terms of reliability and applicability.