In this paper a simple simulation model for a congested transport network is described. In the model the individual interactions between the drivers themselves and the interaction between the drivers and the information play a major role. The drivers' behaviour is modeled using the random utility theory. A "learning" mechanism is introduced to model the individuals' experience of the situation in the network in the past. This implies that new "decision" is based on a more extensive knowledge of the congested network. The learning mechanism can be changed to model more advanced kinds of information acquisition. Four different kinds of information mechanisms are presented. One of these is a real time information (RTI) system. Finally some simulation experiments are carried out with a network representing the major roads around Amsterdam in 1989. The simulations have produced some interesting results. These indicate, among other things, that following the shortest route will not always lead to the shortest travel time.
Abstract