Rail-induced Traffic in China

  • Nan He Dalian Jiaotong University
  • Jitao Li Dalian Jiaotong University
  • Yu Wang Dalian Jiaotong University
  • Caiwen Ma Dalian Jiaotong University
Keywords: train operation planning, rail-induced traffic, elasticity model, rail kilometres, rail passenger kilometres,


The rapid development of China’s railway has exerted an enormous influence on the intercity passenger transport structure in recent years. However, it has not satisfied the passengers’ travel demand due to induced traffic. This paper is committed to solving such issue, with the aim of satisfying the current travel demand, and of anticipating the demand of the predicted traffic growth over the next 20 to 30 years. The paper has considered the increase in rail passenger kilometres caused by the growth of rail kilometres as rail-induced traffic. Based on the concept and former research of induced traffic, the panel data of 26 provinces and 3 municipalities of China between the year 2000 and 2014 were collected, and the elasticity models (including elasticity-based model, distributed lag model, high-speed rail (HSR) elasticity model and rail efficiency model) have been constructed. The results show the importance of model formation incorporation of rail-induced traffic. It is better to get the correct value in divided zones with different train frequencies or incorporation rail efficiency in cities or provinces. The lag time and rail types also need to be considered. In summary, the results analysis not only confirms the existence of rail-induced traffic, but also provides substantial recommendations to train operation planning.

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Nan He, Dalian Jiaotong University

School of Traffic and Transportation

Assistant Professor

Jitao Li, Dalian Jiaotong University
Ph.D. Candidate
Yu Wang, Dalian Jiaotong University
Caiwen Ma, Dalian Jiaotong University


Wardman M. Demand for rail travel and the effects of external factors. Transportation Research Part E: Logistics & Transportation Review. 2006;42(3): 129-148.

Cascetta E, Ben-Akiva M, Coppola P, et al. High Speed Rail Demand Forecasting in a Competitive Market: the Italian Case Study. World Conference on Transportation Research WCTR 2010.

Hsu CI, Chung WM. A model for market share distribution between high-speed and conventional rail services in a transportation corridor. Annals of Regional Science. 1997;31(2): 121-153.

Fröidh O. Perspectives for a future high-speed train in the Swedish domestic travel market. Journal of Transport Geography. 2008;16(4): 268-277.

Cascetta E, Coppola P. High Speed Rail (HSR) Induced Demand Models. Procedia - Social and Behavioral Sciences. 2014;111: 147-156.

Cascetta E, Coppola P. Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services. Transportation Research Part A: Policy & Practice.

;84: 93-108.

Fulton LM, Noland RB, Meszler DJ, et al. A statistical analysis of induced travel effects in the US mid-Atlantic region. Journal of Transportation and Statistics. 2000;3(1): 1-14.

Hansen M, Gillen D, Dobbins A, et al. The Air Quality Impacts of Urban Highway Capacity Expansion: Traffic Generation and Land Use Change. University of California Transportation Center Working Papers; 1993.

González RM, Marrero GA. Induced road traffic in Spanish regions: A dynamic panel data model. Transportation Research Part A: Policy & Practice. 2012;46(3): 435-445.

He N, Zhao S. Induced Traffic in China: Elasticity Models with Panel Data. Journal of Urban Planning & Development. 2014;141(4): 04014046.

Hymel KM, Small KA, Dender KV. Induced demand and rebound effects in road transport. Transportation Research Part B: Methodological. 2010;44(10): 1220-1241.

Noland RB. Relationships between highway capacity and induced vehicle travel. Transportation. Research Part A: Policy and Practice. 2001;35(1):47-72.

National Bureau of Statistics of China. 2000-2014. Available from: http://www.stats.gov.cn/

White H. A Heteroskedasticity-Consistent Covariance Matrix and a Direct Test for Heteroskedasticity. Econometrica. 1980;48(4): 817-838.

Bai ZL. The Unit Root Test in the panel data with longitudinal time series. Econometric Analysis of Panel Data. Tianjin: Nankai University Press; 2008.

How to Cite
He N, Li J, Wang Y, Ma C. Rail-induced Traffic in China. Promet [Internet]. 2017Nov.5 [cited 2024Jun.23];29(5):511-20. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/2235