A pedestrian road network is a complex non-linear dynamic system, and it is prone to severe accidents due to the congestion of spatio-temporal mass gathering. This paper proposes a hybrid framework of crowd dynamics modeling and model predictive control to ease the pressure of pedestrian road networks. The framework is integrated on the basis of a mature paradigm in the field of traffic signal control; the theory is yet new to pedestrian road networks except general traffic signals on the streets. The novelty also lies in its ability to simultaneously monitor both the discrete and continuous dynamics changes in the overall network. We verify the framework through comparison with simulation of manual control commands restored from real cases of a large-scale outdoor event. The results indicate that the proposed framework has a superior performance in keeping the balance in the overall distribution of large-scale crowd and reducing the risk of saturation in a pedestrian road network.