Day-to-day route choice control in traffic networks - A model predictive control approach based on mixed integer linear programming

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.