s can be seen, this approach combines both assignment and regression techniques in a simple manner in order to best predict the hourly volumes as a convex combination of a few basic states. Of course, this framework as such does not guarantee a successful application. The main problem, which is to be resolved for each application separately, is the choice of the basic state set S and the availability of suitable corresponding demand matrices. In the Basel application, which is discussed below, three basic states were chosen: ``AM'', ``PM'' and ``Off-peak''.

The Basel Application

In 1988, the City of Basel initiated a study project with the goal of providing a new assignment framework, which would be able to model the flow variations during the day (Rapp, 1989). The results of this model would subsequently be used as a basis for the computation of the fuel consumption and the emissions of the various pollutants caused by the road traffic, such as , , , , and soot.

The region spanned by the Basel network is subdivided into 330 zones. The base year network consists of 794 nodes and 2200 links. The times on the links are modelLED by a set of conical volume-delay functions (see Spiess [5]).

Hourly observed volumes were available on 220 links. 107 of these countpo

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