Abstract: We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light 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 is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.
Keywords: self-organization; complexity; emergence; information; traffic; cellular automata; adaptation; autopoiesis
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Zubillaga, D.; Cruz, G.; Aguilar, L.D.; Zapotécatl, J.; Fernández, N.; Aguilar, J.; Rosenblueth, D.A.; Gershenson, C. Measuring the Complexity of Self-Organizing Traffic Lights. Entropy 2014, 16, 2384-2407.
Zubillaga D, Cruz G, Aguilar LD, Zapotécatl J, Fernández N, Aguilar J, Rosenblueth DA, Gershenson C. Measuring the Complexity of Self-Organizing Traffic Lights. Entropy. 2014; 16(5):2384-2407.
Zubillaga, Darío; Cruz, Geovany; Aguilar, Luis D.; Zapotécatl, Jorge; Fernández, Nelson; Aguilar, José; Rosenblueth, David A.; Gershenson, Carlos. 2014. "Measuring the Complexity of Self-Organizing Traffic Lights." Entropy 16, no. 5: 2384-2407.