Prediction analysis of traffic flow based on cloud model

Abstract

For the city's road traffic conditions, an urban traffic flow prediction algorithm based on cloud model theory is described in this paper. Based on existing traffic conditions analyzing and traditional traffic flow forecasting methods, the cloud model theory is used to simulate and forecast urban traffic conditions. Cloud model theory, the basic principles of fuzzy mathematics, is a comprehensive evaluation method to evaluate the object that cannot be quantitative evaluation. This method can overcome the defects of traditional assessment methods that qualitative and quantitative cannot be considered both. It can also reflect the actual data in ambiguity and randomness. Simulation results show that the cloud model theory can be applied effectively in the prediction and evaluation of urban road traffic, provide a reliable technical support for urban traffic information mining and evaluation and has broad application prospects. © 2012 Springer-Verlag GmbH.