Forecast of Passenger and Freight Traffic Volume based on Elasticity Coefficient Method and Grey Model

Abstract

The increase in passenger and freight traffic in a region reflects the development of railways, highways, waterways, aviation, and pipeline. With the growth of economy, China's transportation develops rapidly. However, the passenger and freight traffic present different growth features in different regions. Therefore, a reasonable forecast model for passenger and freight traffic and the analysis of relationship between regional transportation and economy are important for transportation planning. The elasticity coefficient between the passenger traffic volume, freight traffic volume and gross domestic product (GDP) is calculated based on the data from 2001 to 2010 in different regions in China. Then, the relationship between the change of regional traffic volume and regional economic development is obtained. With the analysis of the pros and cons for different forecast models, Elasticity Coefficient Method, GM (1, 1) model, and DGM model have been used to forecast passenger and freight traffic volumes from 2011 to 2015. In order to improve the accuracy of the forecast results, the combined models based on the variance reciprocal and the optimal weighting are applied to optimize the forecasting model. Among all the forecast models, the combined model with optimal weights outperforms other models with a relative error less than 0.006% for the freight traffic volume. The accuracy of forecast models on passenger and freight traffic volume has been improved, which provides a reasonable basis for the planning and development of the transportation system.