A study on travel demand for high-speed train based on nested logit model

High speed train (HST) has received plenty of attention due to the characteristics of safety, quickness, convenience and better service in China over recent years. With consideration of rapid development of HST and intense competition between HST and other transport modes, it is essential to estimate the travel demand for HST. In this research, a disaggregate logit model is applied to estimate the travel demand for high-speed train based on stated preference data. Considering the independence of irrelevant alternatives attribute, a nested structure is chosen to these alternatives. Besides, both the service attributes of transport mode and passengers' attributes are taken into account when establishes model. The results obtained confirm that HST occupies a significant position in modes conpetition and have an important impact on air in middle and long distance market.