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Self-organizing and edge of chaos analysis of the multi-agent traffic evolution model

In order to study the quantification of emergence in the complex transportation system, self-organizing traffic evolution model based on multi-agent is established by using the one-dimensional binary cellular automaton in which travellers' actual behavior is considered. “Decision coefficient” and “the evolution entropy of route choice” is transplanted form Langton parameter and evolution entropy of the cellular automata dynamics, which are used to quantify the group decision of transportation system, relationship between “decision coefficients” and “the evolution entropy of route choice” is discussed. The “edge of chaos” state of travellers' route choice is analyzed through genetic evolution computation aim for the traffic efficiency. The study found that (1) the relationship between “decision coefficients” and “the evolution entropy of route choice” accords with the conclusion of “edge of chaos” in cellular automata dynamics; (2) total travel time under “edge of chaos” state was superior to the traditional model; (3) the new model expressed the relationship between travellers' level of information interaction and traffic efficiency.