Model predictive control for mixed urban and freeway networks


Reference:
M. van den Berg, B. De Schutter, A. Hegyi, and J. Hellendoorn, "Model predictive control for mixed urban and freeway networks," Proceedings of the 83rd Annual Meeting of the Transportation Research Board, Washington, DC, 19 pp., Jan. 2004. Paper 04-3327.

Abstract:
We consider coordinated traffic control for networks consisting of both urban roads and freeways. One of the main problems that has to be addressed when designing traffic control strategies for such networks is that we should prevent a shift of problems from the urban network to the freeway network (or vice versa) due to the applied control strategy. First, we develop an integrated model to describe the evolution of the traffic situation in mixed urban and freeway networks. For the freeways we use the METANET macroscopic traffic flow model. For the urban traffic a new model is developed that is based on an earlier model by Kashani. Furthermore, we also provide model equations that describe the connection between the two models via on-ramps and off-ramps. Next, we present a model predictive control framework for mixed urban and freeway networks. The control objective used in this paper is the total time spent by all vehicles in the network, and the control measures are the urban traffic signals (but the method can easily be extended to include other objectives and/or control measures). Finally, we illustrate our approach with a synthetic case study that captures the essential elements of a mixed urban and freeway network.


Downloads:
 * Corresponding technical report: pdf file (249 KB)
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Bibtex entry:

@inproceedings{vanDeS:03-009,
        author={M. {van den Berg} and B. {De Schutter} and A. Hegyi and J. Hellendoorn},
        title={Model predictive control for mixed urban and freeway networks},
        booktitle={Proceedings of the 83rd Annual Meeting of the Transportation Research Board},
        address={Washington, DC},
        month=jan,
        year={2004},
        note={Paper 04-3327}
        }



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