Real-time road traffic control has been the subject of active research efforts for more than fifty years. In recent years, however, the convergence of ubiquitous sensing with seamless communication technologies has motivated the development of more computationally efficient control methods, able to operate in real-time in a live environment. In this work, we present a fast decomposition method for network optimization problems, with application to real-time traffic control. Our approach is based on a nonlinear programming formulation of the network control problem and consists of an alternating directions method using forward numerical simulation in place of one of the optimization subproblems. The method is scalable to realistic city-size road networks for real-time applications, and is shown to perform well on synthetic and real traffic networks.