Measuring the Complexity of Self-organizing Traffic Lights

Abstract

We apply measures of complexity, emergence and self-organization to an abstract city traffic model for comparing a traditional traffic coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only traffic is a non-stationary problem, which requires controllers to adapt constantly. Controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures, we can say that the self-organizing method achieves an adaptability level comparable to a living system.

18 pages, 11 figures

References in corpus (4)

• Complexity and Information: Measuring Emergence, Self-organization, and Homeostasis at Multiple Scales
• Self-Organizing Traffic Lights
• When Can we Call a System Self-organizing?
• Complexity measurement of natural and artificial languages

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