The main aim of this paper is to use multi-class macroscopic traffic flow and emission models for Model Predictive Control (MPC) for traffic networks. In particular, we use and compare extended versions of multi-class METANET, FASTLANE, multi-class VT-macro, and multi-class VERSIT+. In addition, end-point penalties based on these multi-class traffic flow and emission models are also included in the objective function of MPC to account for the behavior of the traffic system beyond the prediction horizon. A simulation experiment is implemented to evaluate the multi-class models. The results show that the approaches based on multi-class METANET and the extended emission models (multi-class VT-macro or multi-class VERSIT+) can improve the control performance for the total time spent and the total emissions with respect to the non-control case, and they are more capable of dealing with the queue length constraints than the approaches based on FASTLANE. Including end-point penalties can further improve the control performance with a small sacrifice in the computational efficiency for the approaches based on multi-class METANET but not for the approaches based on FASTLANE.


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    Titel :

    Model Predictive Control for Freeway Networks Based on Multi-Class Traffic Flow and Emission Models




    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.84 / 55.24 / 55.84 Straßenverkehr / 55.24 Fahrzeugführung, Fahrtechnik





    Multi-class traffic flow and emission control for freeway networks

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    Schreiter, Thomas / Landman, Ramon L. / van Lint, J. W. C. (Hans) et al. | Transportation Research Record | 2012