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.
Downloads
- Corresponding technical report:
pdf
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(296 KB)
Bibtex entry
@inproceedings{vanDeS:08-010,
author={M. van den Berg and B. {D}e Schutter and J. Hellendoorn and A.
Hegyi},
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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Last update: February 21, 2026.