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Travel demand forecasting with stated choice data.: Swedish domestic long-distance trips.
KTH, School of Architecture and the Built Environment (ABE), Transport Science.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The travel demand forecasting capability is affected by the model

performance and is restricted by the available modes. The Sampers models

being used in long distance travel demand forecasting doesn’t deal with

nonlinearity and contains no travel service qualitative variables. The RP models

can’t forecast the travel demand of the hypothetical mode of the high speed rail.

Meanwhile, the value of time which is an important indicator in cost-benefits

evaluation needs to be estimated in more specific way. Functional form

improving method of Box-Cox transformation is proved to be efficient in dealing

with nonlinearity and so does the piecewise function is effective in using

discrete variables. Variable related travel service quality is proved to be a

significant estimate in enriching model specification. The value of time is

re-evaluated by taking into account its distribution. The mean values are

sensitive to the model specified and the extent of self-selection has been

analyzed by comparing the value of different current mode users with different

alternatives Based on the stated choice survey about the high speed rail, the

preference and sensitivity is revealed by binary Logit model estimation. The

minor difference between X2000 and high speed rail and self-selection effect

imply the little attractiveness of high speed rail for both train users and air users.

Place, publisher, year, edition, pages
2011. , 85 p.
TEC-MT, 11-004
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-48032OAI: diva2:456644
Available from: 2011-11-15 Created: 2011-11-15

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