Applying measures of modelling quality to a national time series: a benchmark for transport demand models

In current urban planning practice, macroscopic transport demand and assignment models are essential for the evaluation of mid- and long-term land use developments and infrastructure investments. The credibility of their projections strongly depends on their ability to reproduce present day traffic volumes. Obviously, a simplified model of reality will display some shortcomings, and the effect of these is asserted by quality measures that quantify the divergence from observed traffic volumes. There is, however, only rough guidance regarding acceptable ranges of these measures. Most of the literature on this subject approach these ranges from below, by discussing measures attained by operational models and using these as a benchmark, or by using the adverse effects of modelling errors to derive a minimum quality level. On the contrary, this study suggests upper limits for quality measures by analysing year-on-year variations in traffic volumes that result from changing land use and infrastructure.