  Traffic-responsive signal control is a cost-effective and easy-to-implement
network management strategy with high potential in improving performance in
congested networks with dynamic characteristics. Max Pressure (MP) distributed
controller gained significant popularity due to its theoretically proven
ability of queue stabilization and throughput maximization under specific
assumptions. However, its effectiveness under saturated conditions is
questionable, while network-wide application is limited due to high
instrumentation cost. Perimeter control (PC) based on the concept of the
Macroscopic Fundamental Diagram (MFD) is a state-of-the-art aggregated strategy
that regulates exchange flows between regions, in order to maintain maximum
regional travel production and prevent over-saturation. Yet, homogeneity
assumption is hardly realistic in congested states, thus compromising PC
efficiency. In this paper, the effectiveness of network-wide, parallel
application of PC and MP embedded in a two-layer control framework is assessed
with mesoscopic simulation. Aiming at reducing implementation cost of MP
without significant performance loss, we propose a method to identify critical
nodes for partial MP deployment. A modified version of Store-and-forward
paradigm incorporating finite queue and spill-back consideration is used to
test different configurations of the proposed framework, for a real large-scale
network, in moderately and highly congested scenarios. Results show that: (i)
combined control of MP and PC outperforms separate MP and PC applications in
both demand scenarios; (ii) MP control in reduced critical node sets leads to
similar or even better performance compared to full-network implementation,
thus allowing for significant cost reduction; iii) the proposed control schemes
improve system performance even under demand fluctuations of up to 20% of mean.
