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Nowadays urban traffic is one of the main challenges for urban areas in terms of congestion, accidents and pollution. This problem has been stressed by the increasing mobility promoted by the use of private vehicles. So, the time wasted on users' trips has an important impact on urban economy. In this context, transport models become relevant for the development of new strategies and policies for a sustainable urban transport. In particular, models for traffic forecasting like dynamic traffic assignment models, providing temporal coherent representation of the interactions among traffic choices, flows, time and cost measures. In this paper, the authors develop a dynamic traffic assignment model based on the dynamic user equilibrium by solving a variational inequalities formulation under a preventive approach. An iterative solution algorithm, which is a modification of the Method of Successive Averages, explicitly considers the time and a variable traffic demand on each path of the network within the flow propagation and assignment processes. The dynamics of the reassigned flows at each iteration are simulated by a new mesoscopic multiclass multilane simulation model accounting for lane changes and traffic control at signalized intersections.
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