Nonlinear optimization for freeway control using variable-speed signaling

A traffic control problem with a dynamic macroscopic model is considered by means of simulations. An optimal control problem is stated for variable-sp eed signaling in order to improve traffic behavior near congestion, A traff ic state estimator based on the extended Kalman filter is designed to gener ate realtime estimates of the traffic density and, by means of these ones, to activate speed signaling. The variable-speed signaling control law is cl osed loop and is set by minimizing (or maximizing) a performance criterion. The optimization procedure is based on Powell's method, and its off-line e xecution has resulted computationally tractable on low-cost computers too. Simulation results demonstrate the efficacy of the proposed approach for pr eventing and reducing congestion.