The 20th and 21st joint COTA International Conference of Transportation Professionals (CICTP 2020-21)

Abstract: Highway passenger travel demand increased steadily before 2012. It declined sharply in 2013 and then kept decreased steadily. These make highway passenger travel demand difficult to predict. In order to forecasting travel demand in the accurate way and guarantee passenger traffic prediction accuracy, highway passenger kilometers is chosen as the research object to study on influencing factors, such as population, gross domestic product, highway kilometers, high-speed railway operating kilometers and private car ownership. We measure the constructed elasticity model using the panel data at the city and provincial levels of China for the years 1997, 1998, 2007, 2008, 2017, 2018. Results show the growth of high-speed railway operating kilometers will decrease highway passenger kilometers. The high-speed railway operating kilometers elasticity of highway passenger kilometers is -0.074, meaning a 1% growth of high-speed railway operating kilometers will decrease 0.074% highway passenger kilometers. The calculated model could predict the passenger kilometers in 1999, 2009, 2019. The errors analysis between these forecasting results and accurate data collection in National Bureau of Statistics of China certify the correct elasticity model formation. And then the highway passenger kilometers in 2030 is predicted. Results show that highway passenger travel demand forecasting under the development of high-speed railway should consider trend traffic volume (influence of population and GDP), induced traffic volume (influence of highway kilometers), and transfer traffic volume (influence of high-speed railway operating kilometers). These provide valuable suggestions for the construction of a sustainable passenger transportation system. Keywords: highway passenger travel demand; elasticity model; high-speed railway operating kilometers; panel data; demand forecasting

CICTP