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Using a stochastic cellular automaton model for urban traffic flow, we studyand compare Macroscopic Fundamental Diagrams (MFDs) of arterial road networksgoverned by different types of adaptive traffic signal systems, under variousboundary conditions. In particular, we simulate realistic signal systems thatinclude signal linking and adaptive cycle times, and compare their performanceagainst a highly adaptive system of self-organizing traffic signals which isdesigned to uniformly distribute the network density. We find that for networkswith time-independent boundary conditions, well-defined stationary MFDs areobserved, whose shape depends on the particular signal system used, and also onthe level of heterogeneity in the system. We find that the spatialheterogeneity of both density and flow provide important indicators of networkperformance. We also study networks with time-dependent boundary conditions,containing morning and afternoon peaks. In this case, intricate hysteresisloops are observed in the MFDs which are strongly correlated with the densityheterogeneity. Our results show that the MFD of the self-organizing trafficsignals lies above the MFD for the realistic systems, suggesting that byadaptively homogenizing the network density, overall better performance andhigher capacity can be achieved.

A comparative study of Macroscopic Fundamental Diagrams of arterial road networks governed by adaptive traffic signal systems