Influencing Route Choice in Traffic Networks: A Model Predictive Control Approach Based on Mixed-Integer Linear Programming

Reference

M. van den Berg, B. De Schutter, J. Hellendoorn, and A. Hegyi, "Influencing route choice in traffic networks: A model predictive control approach based on mixed-integer linear programming," Proceedings of the 17th IEEE International Conference on Control Applications, San Antonio, Texas, pp. 299-304, Sept. 2008.

Abstract

Traffic control measures like variable speed limits or outflow control can be used to influence the route choice of drivers. In this paper we develop a day-to-day route choice control method that is based on model predictive control (MPC). A basic route choice model forms the basis for the controller. We show that for the given model and for a linear cost function it is possible to reformulate the MPC optimization problem as a mixed-integer linear programming (MILP) problem. For MILP problems efficient branch-and-bound solvers are available that guarantee to find the global optimum. We also illustrate the efficiency of the proposed approach for a simple simulation example involving speed limit control.

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BibTeX

@inproceedings{vanDeS:08-010,
   author    = {van den Berg, Monique and De Schutter, Bart and Hellendoorn,
                Johannes and Hegyi, Andreas},
   title     = {Influencing Route Choice in Traffic Networks: {A} Model
                Predictive Control Approach Based on Mixed-Integer Linear
                Programming},
   booktitle = {Proceedings of the 17th IEEE International Conference on
                Control Applications},
   address   = {San Antonio, Texas},
   pages     = {299--304},
   month     = sep,
   year      = {2008}
   }


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