The process of calibrating and validating all types of transport simulation models (micro, meso or macro) is a labour intensive and costly process. There have been a number of theoretical advances in methods for efficient testing and running simulation experiments that could be applied to the calibration and validation process. However they have not yet penetrated to actual modelling or transport simulation practice.
Our detailed review of the transport research literature showed that many of the state-of-theart methods for validation and calibration are focused on the following: improving the OriginDestination (OD) matrix estimation process; optimization algorithms to automate calibration; and Sensitivity Analysis on the input-output relationships of the model’s parameters. While these methods are scientifically correct they are complex to understand and apply in practice, as the modeller needs an advanced level of mathematics to use them. Our consultation with simulation practitioners and our own experience in implementing changes to modelling practice [Shteinman 2010, 2011, 2012] lead us to expect a low probability of acceptance by practitioners of these methods.