This paper describes a statistical framework to be used in a set of simulation and modelling guidelines. The framework was developed out of the necessity for defensible study results by the application of rigorous statistics. It is the result of a collaborative RTA-ACCM research project and provides a framework for analyzing simulation outputs, and also informs the design stage of a simulation study. The project was based on an analysis of thirty-six PARAMICS models supplied by the RTA. The guidelines apply Exploratory Data Analysis techniques (EDA) to the design and analysis of traffic micro- simulations, and include the graphing of output distributions to expose salient features and rigorous methods to detect and handle outliers in output data.
The framework includes methods to quantify and correct biases that result from the phenomenon of unreleased vehicles or incomplete trips.
Diagnostic tests are described for discriminating between running error, model error or extreme sensitivity to congested conditions
A model to predict the run cost of a simulation as a function of critical network features is also described. A regression model was built, based on an index of model complexity and the combination of critical input factors. The regression model was limited by the small sample size of models used (36). Further research is continuing on cost prediction, using a larger set of simulation outputs and model types.
The guidelines developed have provided value to RTA traffic control modelling practice and can be used by simulation modellers regardless of the micro-simulation package used.