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

TL;DR

This study compares different adaptive traffic signal systems using a cellular automaton model, revealing how their design influences network performance, heterogeneity, and capacity under various boundary conditions.

Contribution

It introduces a comprehensive comparison of adaptive traffic signal systems' effects on macroscopic fundamental diagrams in urban networks.

Findings

Self-organizing signals outperform realistic systems in homogenizing network density.

Stationary MFDs depend on signal type and heterogeneity levels.

Hysteresis in MFDs correlates with density heterogeneity during peak periods.

Abstract

Using a stochastic cellular automaton model for urban traffic flow, we study and compare Macroscopic Fundamental Diagrams (MFDs) of arterial road networks governed by different types of adaptive traffic signal systems, under various boundary conditions. In particular, we simulate realistic signal systems that include signal linking and adaptive cycle times, and compare their performance against a highly adaptive system of self-organizing traffic signals which is designed to uniformly distribute the network density. We find that for networks with time-independent boundary conditions, well-defined stationary MFDs are observed, whose shape depends on the particular signal system used, and also on the level of heterogeneity in the system. We find that the spatial heterogeneity of both density and flow provide important indicators of network performance. We also study networks with time-dependent boundary conditions, containing morning and afternoon peaks. In this case, intricate hysteresis loops are observed in the MFDs which are strongly correlated with the density heterogeneity. Our results show that the MFD of the self-organizing traffic signals lies above the MFD for the realistic systems, suggesting that by adaptively homogenizing the network density, overall better performance and higher capacity can be achieved.