A new aggregate model of urban traffic is presented. The main challenge in the formulation of an aggregate model is to analytically grasp the correlation between the different components of the network while maintaining atractable model. This correlation explains congestion effects and quantifies their overall network impact. The analytic queueing network model captures this correlation and can therefore explicitly model complex phenomenasuch as spillbacks. This is useful to identify the sources of congestion (e.g. bottlenecks) and quantify their effects. This analytic model fits well within an optimization framework. This is illustrated in the context ofthe optimization of traffic signal timing in the network of the city of Lausanne. The aggregate model is calibrated using the outputs of a disaggregate model, that is a microscopic traffic simulation model. The analytic formulation of this optimization problem is presented. The optimal solutionis then evaluated with the microscopic traffic simulation model. Its performance is compared with that of several other methods. It is shown how these methods differ in their ability to cope with increasing congestion, and the importance of taking into account the correlation between consecutive roads is emphasised. For the covering abstract see ITRD E145999
Abstract