Prediction of highway passenger transportation in Beijing based on BP neural network

The purpose of this paper is to explore the method and effect of using BP neural network to forecast the passenger transportation volume on highway. A prediction model based on BP neural network is constructed by analyzing and processing the historical data of highway transportation and related influencing factors in Beijing from 2000 to 2020, and its prediction results are analyzed and compared. The experimental results show that the model can effectively predict the road passenger traffic with high accuracy and generalization ability, which can provide a good reference for the prediction of road passenger traffic in other cities.