This paper tackles the problem of real-time optimal control of traffic flow in a freeway network deployed with coordinated and integrated traffic controllers. One promising approach to this problem is casting the underlying dynamic control problem in a model predictive framework. The challenge is that the resulting optimization problem is computationally intractable for online applications in a network with a large number of controllers. In this paper, a game-theoretic approach with distributed controllers is proposed to address the foregoing issue. The efficiency of the proposed method is tested for a coordinated ramp metering and variable-speed limit control applied to a stretch of freeway network. The parallel nature of the optimization algorithm makes it suitable for solving large-scale problems with high accuracy. The speed and accuracy of the proposed solution approach are examined and compared with that of the conventional optimization method in a case study to demonstrate its superior performance.