A hybrid model for model predictive control of urban traffic

In this preliminary paper the simulation of an efficient hybrid model is presented to predict the behavior of an urban area as controlled by a certain control strategy. Intersections and on-ramps are modelled by Timed Petri Nets while road links are modelled by a stochastic discrete time model. It is assumed that vehicle routings at each intersection are stochastic. An algorithm for the on-line identification of routing rates is presented. The control inputs are traffic lights´ switching times. The aim is to minimize the average number of vehicles in the urban area over a fixed time horizon to avoid a traffic congestion in the area.