In this paper, the authors explore the usefulness of cellular automata to traffic flow modeling. The authors extend some of the existing CA models to capture characteristics of traffic flow that have not been possible to model using either conventional analytical models or existing simulation techniques. In particular, the authors examine higher moments of traffic flow and evaluate their effect on overall traffic performance. The behavior of these higher moments is found to be surprising, somewhat counter-intuitive, and to have important implications for design and control of traffic systems. For example, the authors show that the density of maximum throughput is near the density of maximum speed variance. Contrary to current practice, traffic should, therefore, be steered away from this density region. For deterministic systems the authors found traffic flow to possess a finite period which is highly sensitive to density in a non-monotonic fashion. The authors show that knowledge of this periodic behavior to be very useful in designing and controlling automated systems. These results are obtained for both single and two lane systems. For two lane systems, the authors also examine the relationship between lane chaning behavior and flow performance. The authors show that the density of maximum land changing frequency occurs past the density of maximum throughput. Therefore, traffic should also be steered away from this density region.


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    Title :

    Cellular Automata for Traffic Flow Modeling


    Contributors:
    S. Benjaafar (author) / K. Dooley (author) / W. Setyawan (author)

    Publication date :

    1997


    Size :

    36 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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