Abstract
Transportation demand in China has experienced rapid development and transformation in recent years, which has led to enormous energy consumption and environmental emissions. The aim of this manuscript is to construct a hybrid model to forecast future transportation demand in China that combines the advantages of existing methodologies. We first review previous studies to summarise the main categories, advantages and disadvantages, and results of various methodologies for forecasting transportation demand. Based on this review, we develop a hybrid model based on the GDP elastic coefficient method, which uses the mode split method and vehicle population method and includes three modules: the vehicle population module, the passenger traffic module and the freight traffic module. Using this model, a forecast of transportation service demand in China in 2030 is derived and compared with other studies. According to the results, vehicle ownership, passenger transportation demand, and freight transportation demand will continue to experience rapid growth. The total traffic volume, the share of aviation in passenger traffic and the share of water in freight traffic are very sensitive to the GDP growth rate.
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