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As urbanization advances, cities are expanding, leading to a more decentralized urban structure and longer average commuting durations. The construction of an urban expressway system emerges as a critical strategy to tackle this challenge. However, the traditional link-level network design method faces modeling and solution challenges when dealing with the large-scale expressway network design problem (ENDP). To address the challenges, this paper proposes an expressway network design method for multiple urban subregions based on the macroscopic fundamental diagram (MFD). Initially, a mixed road network traffic model that describes traffic dynamics of multiple subregions and candidate expressways is developed by integrating the MFD and the cell transmission model (CTM). Then, treating urban subregions and candidate expressways as route nodes in the mixed road network, a route choice model is established based on stochastic user equilibrium. Finally, a decision model for ENDP is proposed to minimize vehicle travel time under the construction budget constraint. The impact of financial investment and traffic demand on expressway network design schemes in the case study is explored separately. The simulation results indicate that during the initial stages of expressway planning, the construction of new expressways can significantly alleviate traffic congestion. However, as the expressway network expands further, the effectiveness of improving traffic conditions through new expressway construction gradually diminishes if traffic demand does not continue to increase. Additionally, variations in traffic demand between subregions result in different construction schemes, emphasizing the importance of adjusting budget allocations based on specific traffic demands.

Facing the congestion challenges of mixed road networks comprising expressways and arterial road networks, traditional control solutions fall short. To effectively alleviate traffic congestion in mixed road networks, it is crucial to clear the interaction between expressways and arterial networks and achieve orderly coordination between them. This study employs the multi-class cell transmission model (CTM) combined with the macroscopic fundamental diagram (MFD) to model the traffic dynamics of expressway systems and arterial subregions, enabling vehicle path tracking across these two systems. Consequently, a comprehensive traffic transmission model suitable for mixed road networks has been integrated. Utilizing the SUMO software, a simulation platform for the mixed road network is established, and the average trip lengths within the model have been calibrated. Based on the proposed traffic model, this study constructs a route guidance model for mixed road networks and develops an integrated model predictive control (MPC) strategy that merges route guidance, perimeter control, and ramp metering to address the challenges of mixed road networks' traffic flow control. A case study of a scenario in which a bidirectional expressway connects two subregions is conducted, and the results validate the effectiveness of the proposed cooperative guidance and control (CGC) method in reducing overall congestion in mixed road networks.