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Register a new userInfluence of High-Speed Railway System on Inter-city Travel Behavior in Vietnam
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To analyze the influence of introducing the High-Speed Railway (HSR) system on business and non-business travel behavior, this study develops an integrated inter-city travel demand model to represent trip generations, destination choice, and travel mode choice behavior. The accessibility calculated from the RP/SP (Revealed Preference/Stated Preference) combined nested logit model of destination and mode choices is used as an explanatory variable in the trip frequency models. One of the important findings is that additional travel would be induced by introducing HSR. Our simulation analyses also reveal that HSR and conventional airlines will be the main modes for middle distances and long distances, respectively. The development of zones may highly influence the destination choices for business purposes, while prices of HSR and Low-Cost Carriers affect choices for non-business purposes. Finally, the research reveals that people on non-business trips are more sensitive to changes in travel time, travel cost and regional attributes than people on business trips.
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It is one of hottest topics in Vietnam whether to construct a High Speed Rail (HSR) system or not in near future. To analyze the impacts of introducing the HSR on the intercity travel behavior, this research develops an integrated intercity demand forecasting model to represent trip generation and frequency, destination choice and travel mode choice behavior. For this purpose, a comprehensive questionnaire survey with both Revealed Preference (RP) information (an inter-city trip diary) and Stated Preference (SP) information was conducted in Hanoi in 2011. In the SP part, not only HSR, but also Low Cost Carrier is included in the choice set, together with other existing inter-city travel modes. To make full use of the advantages of each type of data and to overcome their disadvantages, RP and SP data are combined to describe the destination choice and mode choice behavior, while trip generation and frequency are represented by using the RP data. The model estimation results show the inter-relationship between trip generation and frequency, destination choice and travel mode choice, and confirm that those components should not dealt with separately.
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