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Summary: Traffic light coordination is a complex problem. In this paper, weextend previous work on an abstract model of city traffic to allow for multiplestreet intersections. We test a self-organizing method in our model, showingthat it is close to theoretical optima and superior to a traditional method oftraffic light coordination.  Abstract: The elementary cellular automaton following rule 184 can mimicparticles flowing in one direction at a constant speed. This automaton cantherefore model highway traffic. In a recent paper, we have incorporatedintersections regulated by traffic lights to this model using exclusivelyelementary cellular automata. In such a paper, however, we only explored arectangular grid. We now extend our model to more complex scenarios employingan hexagonal grid. This extension shows first that our model can readilyincorporate multiple-way intersections and hence simulate complex scenarios. Inaddition, the current extension allows us to study and evaluate the behavior oftwo different kinds of traffic light controller for a grid of six-way streetsallowing for either two or three street intersections: a traffic light thattries to adapt to the amount of traffic (which results in self-organizingtraffic lights) and a system of synchronized traffic lights with coordinatedrigid periods (sometimes called the "green wave" method). We observe a tradeoffbetween system capacity and topological complexity. The green wave method isunable to cope with the complexity of a higher-capacity scenario, while theself-organizing method is scalable, adapting to the complexity of a scenarioand exploiting its maximum capacity. Additionally, in this paper we propose abenchmark, independent of methods and models, to measure the performance of atraffic light controller comparing it against a theoretical optimum.

Self-organizing traffic lights at multiple-street intersections