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A traffic control framework for urban networks based on within-day dynamic traffic flow models

ABSTRACT The paper aims to provide a further development of traffic control strategies, to propose an enhanced version of two traffic flow models and to integrate these models within an urban traffic control framework. Concerning the traffic control method, the synchronisation approach is adopted and three objective functions are considered and compared: two are mono-criterion and the third is multi-criteria. Simulated annealing and multi-objective simulated annealing are adopted as a solution algorithm. In terms of traffic flow representation the approaches analysed are macroscopic cell-based and mesoscopic link-based, both able to model path choice behaviours and vehicle dispersion phenomena. Furthermore, traffic flow prediction is pursued through a Kalman filter and a rolling horizon approach is adopted as a forecasting framework for the optimisation procedure. In order to test the framework and to compare two traffic flow models, a 15-node grid network was considered, including different levels of congestion and demand profiles.