• Title/Summary/Keyword: Free automata

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Some Regular Languages and Prefix Coding (어떤 정규언어와 Prefix Coding)

  • Golin, Mordecai;Na, Hyeon-Suk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.2C
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    • pp.1-9
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    • 2005
  • Code is a set of words. If, for any pair of words in the code, one is not prefix of another, the code is called "Prefix(-Free) Code". The prefix coding problem is, given n, to find an optimal code with the minimum-sum of lengths of n words. As a special case of this, we present a method to find, given language L in some specific classes of regular languages, an optimal code among prefix codes in L. We also show how the structure of optimal codes varies as n grows, using trees.

A Study on Link Travel Time Prediction by Short Term Simulation Based on CA (CA모형을 이용한 단기 구간통행시간 예측에 관한 연구)

  • 이승재;장현호
    • Journal of Korean Society of Transportation
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    • v.21 no.1
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    • pp.91-102
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    • 2003
  • There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.