  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.
