Abstract State observability and demand estimation are two main issues in large-scale traffic networks which hinder real-world application of real-time control strategies. This study proposes a novel combined estimation and control framework (CECF) to develop perimeter control strategies based on macroscopic fundamental diagram (MFD). The proposed CECF is designed to operate with limited real-time traffic data and capture discrepancies in a priori demand estimates. The CECF is developed with a moving horizon estimator (MHE) that estimates traffic states, route choices and demand flows considering region accumulations and boundary flows observed from the network. The estimated traffic states are incorporated into a model predictive controller (MPC) scheme to derive the control decisions, which are then executed in the urban network. A novel accumulation-based MFD model is developed in this study to address the observability problem, which is incorporated into MHE and MPC schemes. The proposed CECF is implemented in a large-scale traffic network where several demand scenarios are tested. The results confirm the success of the CECF in overcoming observability issues and improving the performance of perimeter control strategies.

    Highlights A novel accumulation based MFD formulation addressing the observability issues. Demand estimation for online (rolling horizon) control problems. Estimation of regional route/destination choice and accumulation states.


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    Titel :

    Demand and state estimation for perimeter control in large-scale urban networks


    Beteiligte:


    Erscheinungsdatum :

    2023-05-24




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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