As only O-D demand data, an outdated AM peak-hour matrix 
was available. This matrix had previously gone through a multitude of manual adjustments and factorizations - even retracing its exact ``history'' was impossible.
Thus, compared to the ambitious goal of the project, only a minimal data set was available as input data to the model.
In an initial trial, only two basic states were defined: AM and PM. The corresponding demand matrices were defined as the available AM-peak matrix and its transpose
To our great surprise, even with this very crude 2-state model, we were able to predict the observed volumes with an 
of around 80% for all day-time hours, i.e. between 07h and 20h. Figure 1 shows the regression coefficients, as well as the hourly values that were obtained from this AM/PM model. It is interesting to note that the coefficients 
and 
can be interpreted graphically as well. Note especially the secondary peak
