An evolutionary approach to traffic assignment

Traffic assignment is an important stage in traffic modeling. Most of the existing approaches are based on finding an approximate solution to the user equilibrium or to the system optimum, which can be computationally expensive. In this paper we use a genetic algorithm to compute an approximate solution (routes for the trips) that seeks to minimize the average travel time. To illustrate this approach, a non-trivial network is used, departing from binary route choice scenarios. Our result shows that the proposed approach is able to find low travel times, without the need of recomputing shortest paths iteratively.