A study of the traffic flow predictive model based on mathematical statistics and stochastic process

摘要

Real-time traffic flow prediction is one of important issues of intelligent transportation system. Based on the theory of stochastic process of the traffic flow data, the prediction methods, such as grey expecting model and neural network, were applied in this paper. Then according to the actual traffic flow data, an improved model was proposed and the fluctuation range of predicted traffic flow was determined due to calculate an accurate result. Finally, the experiment shows that the designed prediction model can be able to achieve a short time prediction accurately for traffic flow.