Abstract
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.
Highlights
Accurate traffic forecasts are central to proper appraisal of rail schemes, considering whether there are new railway constructions
Rail-induced traffic is necessary to the accurate prediction, which means the generation of new rail traffic that would not have occurred at all without the capacity improvement
The aim of this paper is to find out rail-induced traffic, and construct the elasticity models for quantification and analysis
Summary
Accurate traffic forecasts are central to proper appraisal of rail schemes, considering whether there are new railway constructions. The relationship between rail kilometres and rail passenger kilometres is the necessary reason to make train timetable based on the traffic forecasting, especially induced traffic has effect on travel demand. Aggregate models are used to forecast railway demand based on aggregate demand elasticity values to GRP variations, railway travel times, fuel costs, population and so on. These models have not incorporated the rail kilometres’ influencing [1, 2]. Disaggregate models focus on the competition among multi-modes, showing the effect of mode changes [3,4,5,6] These models have not considered the cooperated relationship among road, rail and air transport, underestimating rail kilometres influencing. Present model formations have neglected induced traffic, which should be further researched
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