Discrete choice models

Discrete choice models have played an important role in transportation modeling for the last 25 years. They are namely used to provide a detailed representation of the complex aspects of transportation demand, based on strong theoretical justiications. Moreover, several packages and tools are available to help practionners using these models for real applications, making discrete choice models more and more popular. Discrete choice models are powerful but complex. The art of nd-ing the appropriate model for a particular application requires from the analyst both a close familiarity with the reality under interest and a strong understanding of the methodological and theoretical background of the model. The main theoretical aspects of discrete choice models are reviewed in this paper. The main assumptions used to derive discrete choice models in general, and random utility models in particular, are covered in detail. The Multinomial Logit Model, the Nested Logit Model and the Generalized Extreme Value model are also discussed.