In the optimization of mixed urban and freeway networks, most existing control strategies implement centralized controllers that are not appropriate for real-time control in large-scale traffic networks due to the huge computational complexity. In this article, a distributed control framework for the cooperative control of mixed urban and freeway traffic networks is developed. First, an integrated traffic model is presented to characterize the interactions between the urban and freeway networks. In addition, a partitioning method is proposed, and then, the mixed traffic network is divided among urban agents and freeway agents for the easy implementation of the distributed control framework. The optimization problem of the whole network can then be decomposed into a number of suboptimization problems based on the partition of the network. In the proposed distributed control strategy, each agent solves its own optimization problem independently with local information and transmitted information from neighboring agents to seek the Nash equilibrium. Finally, the computational efficiency and the effectiveness of the distributed integrated control strategy of mixed traffic networks are evaluated through a numerical example.