Model predictive control for multi-class traffic flows

P. Deo, B. De Schutter, and A. Hegyi, "Model predictive control for multi-class traffic flows," Proceedings of the 12th IFAC Symposium on Transportation Systems, Redondo Beach, California, pp. 25-30, Sept. 2009.

In this paper we first present an extension of the macroscopic traffic flow model METANET to multi-class flows. The resulting multi-class model takes into account the differences between, e.g., fast vehicles (cars) and slow vehicles (trucks) including their possibly different free-flow speeds and critical densities. Next, we show how this model can be used in a model-based predictive control approach for coordinated and integrated traffic flow control. In particular, we use Model Predictive Control (MPC) to coordinate various traffic control measures such as variable speed limits, ramp metering, etc. Using a simple benchmark example from the literature we illustrate that by taking the heterogeneous nature of multi-class traffic flows into account a better performance can be obtained.

 * Online version of the paper
 * Corresponding technical report: pdf file (121 KB)
      Note: More information on the pdf file format mentioned above can be found here.

Bibtex entry:

        author={P. Deo and B. {D}e Schutter and A. Hegyi},
        title={Model predictive control for multi-class traffic flows},
        booktitle={Proceedings of the 12th IFAC Symposium on Transportation Systems},
        address={Redondo Beach, California},

Go to the publications overview page.

This page is maintained by Bart De Schutter. Last update: October 11, 2016.