Reference
M. van den Berg, B. De Schutter, H. Hellendoorn, and A. Hegyi, "Day-to-day
route choice control in traffic networks - A model predictive control approach
based on mixed integer linear programming,"
Proceedings of the
10th TRAIL Congress 2008 - TRAIL in Perspective - CD-ROM, Rotterdam, The
Netherlands, 14 pp., Oct. 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 optimisation 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. This global
optimisation feature is not present in most of the other mixed integer
optimisation methods that are usually used for MPC (such as simulated
annealing, genetic programming, tabu search, etc.). 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:08-022,
author = {van den Berg, Monique and De Schutter, Bart and Hellendoorn,
Hans and Hegyi, Andreas},
title = {Day-to-Day Route Choice Control in Traffic Networks -- {A}
Model Predictive Control Approach Based on Mixed Integer Linear
Programming},
booktitle = {Proceedings of the 10th TRAIL Congress 2008 -- TRAIL in
Perspective -- CD-ROM},
address = {Rotterdam, The Netherlands},
month = oct,
year = {2008}
}