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.