Determining appropriate utility specifications for discrete choice models is time-consuming and prone to errors. With the availability of larger datasets, as number possible exponentially grows with variables under consideration, analysts need spend increasing amounts time on searching good through trial-and-error, while expert knowledge required ensure these are sound. This paper proposes an a...

Social-economic variables influence transportation demand largely. Analyses of discrete choice model consider social-economic variables to study traveler’s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. Also, an aggregative model is proposed. The historical data of passenger volumes for high speed rail and domestic civil avi...

Since completing a " Trend-Delphi " based regional forecast and transportation plan in 1996, Metro has developed an integrated transportation and land use model (Metroscope). We are presently using the model to explore several regional growth management options as well as produce a new regional forecast and transportation plan. Comparing our Metroscope results to our previous forecast reveals t...

We propose a framework for nonparametric identification and estimation of discrete choice models with unobserved sets. recover the joint distribution sets preferences from panel dataset on choices. assume that either latent are sparse or is sufficiently long. Sparsity requires number possible to be relatively small. It satisfied, instance, when nested, they form partition. Our procedure comp...