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Abstract ▼ AI-Helper

A number of variables affect the rail travel demand. It is true that a scale of economy, quality of rail travel service, fare, time of rail travel, quality of other modes of transport service and so on have significant influences on the rail travel demand. However, no study has been done in Korea so...

A number of variables affect the rail travel demand. It is true that a scale of economy, quality of rail travel service, fare, time of rail travel, quality of other modes of transport service and so on have significant influences on the rail travel demand. However, no study has been done in Korea so far on what kind of variable has how much influence nor is it rarely known in Korea that how much significance the changes of rail travel service or other modes of transport service have on the rail travel demand. The environment for estimating a mode choice model and a direct demand model is sufficiently prepared in Korea. That is, the monthly ticket sales records data (including passengers and freight) and the train operation data, in case of inter-city rail travel, have been hoarded in a database by Korea Railroad Corporation. These data can give birth to various types of model estimation and provide foundations for scenario analysis under various policy circumstances. The purpose of this study is to estimate the aggregate mode choice model and the direct demand model on the Seoul-Busan and Seoul Honam corridors of the inter-city rail and, then, compare the predictive power of the model with the real result. This article found that time factor on rail demand was more crucial rather than fare factor.

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