Forecast and analysis of Beijing passenger volume based on ARIMA model

Passenger volume is a key index to measure the level of economic development in a region. The size and change trend of passenger volume have a profound impact on guiding regional transportation and road network planning. The passenger volume includes the passenger volume of railway, road and civil aviation. In the process of modern urban development, the forecast and analysis of passenger volume is of great significance to urban traffic management, policy formulation and infrastructure planning. As the capital of China, Beijing is faced with increasing traffic demand and complex traffic conditions. Therefore, the accurate prediction of passenger volume can not only provide data support for the optimization of urban transportation system, but also effectively help the traffic management department to alleviate traffic congestion and improve the level of public transportation service. This paper collected and sorted out the passenger volume data of Beijing from 1994 to 2023, and conducted stationarity test and differential processing on the data, which met the modeling requirements of ARIMA model. Through continuous fitting comparison, the optimal parameters of ARIMA model are finally determined as (0,4,3). Then the white noise test and residual test are carried out on the fitted model, the results show that the prediction is reasonable and reliable. The forecast results show that the passenger volume of Beijing will show a steady growth trend in the next period of time.