Abstract
Selecting an appropriate simulation-model structure for complicated, large-scale transport systems is a non-trivial and challenging task. This paper reports practical research which evaluates a number of alternative model structures for the Arizona state-highway network system based on the immediate dependency on input data obtained from a multistage mail survey. The most appropriate topology structure selected is a data-driven, link-based, discrete-event simulation model using conditional probability branching logic. Separating model and data makes the simulation model a generic traffic-routeing logic processor that is easy to use and does not require simulation skills. Different transport systems can easily be accommodated by simply changing input data. The model is validated by comparative analysis of input data using statistical techniques. An upper bound on the size of the valid network is thus obtained.
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