Abstract
In this paper, the authors propose a novel pattern-based approach to model the classification and transition properties of traffic flow. First, fuzzy-set classification method is utilized to divide the traffic states, where the states are partitioned into a number of patterns. Then, fuzzy qualitative reasoning is applied to analyze the transitions between these states. Based on the probability of transition, stability of the traffic states is further investigated. Finally, a case study on urban transportation system is performed to demonstrate the usage of the proposed approach.
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