UC Irvine Institute of Transportation Studies

This paper discusses important developments in discrete choice modeling for transportation applications. Since there have been a number of excellent recent surveys of the discrete choice literature aimed at transportation applications ( see Bhat, 1997 and 2000a), this paper will concentrate on new developments and areas given less weight in recent surveys. Small and Winston (1999) give an excellent review of the transportation demand literature that includes many examples of how discrete choice models have been used in demand analysis. 

Discrete choice modeling is closely related to activity-based modeling of travel demand and duration modeling. Since I have little to add to the excellent recent surveys on these topics by Bhat (2000b) and Bhat and Koppelman (2000), I have restricted this paper to "pure" unordered discrete choice modeling. 

The next section discusses recent developments in flexible discrete choice modeling. Note that I define flexible to mean that the parametric model family is rich enough to arbitrarily approximate any discrete choice process consistent with random utility maximization, and I concentrate on the mixed logit model. There is also a relatively new literature which seeks to estimate discrete choice models without making parametric functional form assumptions (see Savin, 2001, Horowitz, 1998, and Koop and Poirier, 2000 for a Bayesian approach). Since this literature is currently limited to binary discrete choice, I have not included it in this paper.