The Equilibrium_Lohse procedure was developed by professor Lohse and is described in Schnabel (1997). This procedure models the learning process of road users using the network. Starting with an "all or nothing assignment", drivers consecutively include information gained during their last journey for the next route search. Several shortest routes are searched in an iterative process whereby for the route search the impedance is deduced from the impedance of the current volume and the previously estimated impedance. To do this, the total traffic flow is assigned to the shortest routes found so far for every iteration step.
During the first iteration step only the network impedances in the free network are taken into account (like 100 % best-route assignment).
The calculation of the impedance in every further iteration step is carried out using the current mean impedances calculated so far and the impedances resulting from the current volume, i.e. every iteration step n is based on the impedances calculated at n-1.
The assignment of the demand matrix to the network corresponds to how many times the route was found ("kept in mind" by Visum).
The procedure only terminates when the estimated times underlying the route choice and the travel times resulting from these routes coincide to a sufficient degree; there is a high probability that this stable state of the traffic network corresponds to the route choice behavior of drivers.
To estimate the travel time for each link of the following iteration step n+1, the estimated travel time for n is added to the difference between the calculated actual travel time of n (calculated from the VD functions) and the estimated travel time of n. This difference is then multiplied by the value DELTA (0.15...0.5) which results in an attenuated sine wave.
The termination condition arises from the requirement that the estimated travel times for iteration steps n and n-1, and the calculated actual travel time of iteration step n, sufficiently correspond to each other. This is defined by the precision threshold EPSILON.
