Urban traffic flow prediction model based on BP artificial neural network in Beijing area

This paper analyzes the characteristics of traffic flow in a certain section of Beijing and builds a traffic flow prediction model based on the BP neural network. In thisresearch, by monitoring the traffic flow during a peak period in a section of Beijing and generating statistical data, the BP neural network algorithmisapplied to form a neural network training set with strong timeliness, and the data of training set is used to predict the traffic flow for a certain period in the future. Making a comparison between the predict data and the actual data, the simulation experiment result shows that the model is of high precision. Hence, the research can make prediction of a short-term traffic flow and provides a reference for Beijing residents' travel plans.