This paper studies the reconstruction of road traffic flow state based on multi-source monitoring data and establishes a model. From this, it analyses the degree of road unimpeded and realizes the prediction of road congestion change. Then, it carries out congestion prediction of newly increased vehicles, and verifies the rationality and real-time of the model. The model is the basic model of traffic flow. The model uses traffic volume, speed and traffic density as the basic characteristics of the actual traffic flow state, follows Mamdani-type fuzzy logic inference, and further derives by mathematical and physical analysis method, and obtains the ratio of driving speed and traffic density, which can be used to describe the actual state of traffic flow, and evaluate the degree of road unimpeded.

Topics
Fuzzy logic
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