Model Predictive Control of Urban Networks with Perimeter Control and Route Guidance

Recent studies on empirical data demonstrated the existence of macroscopic fundamental diagram (MFD), which expresses an aggregated model of traffic dynamics linking accumulation and output flow of an urban region. Employing MFD in modeling of urban networks opens up possibilities to introduce a new generation of real-time traffic control structures and improve mobility. Although there are studies on using MFD modeling for designing control structures with perimeter control actuation, the potential of actuation via route guidance still needs to be explored. This paper proposes a traffic control scheme based on nonlinear model predictive control (MPC), an advanced control technique based on real-time repeated optimization, for improving mobility in urban networks, integrating perimeter control and route guidance type actuation. Perimeter control operates at region boundaries and manipulates the transfer flows between regions, whereas route guidance system recommends drivers at a region with a specific destination which neighboring region to go next. Two simpler controllers are designed for comparison: 1) perimeter control MPC and 2) route guidance MPC. Performance of the controllers are evaluated via simulations on a 7-region network for a high demand scenario. Results suggest substantial potential in improvement of urban mobility through use of route guidance based MPC schemes.