The analysis of travel behavior is typically disaggregate, meaning that the models represent the choice behavior of individual travelers. Discrete choice analysis is the methodology used to analyze and predict travel decisions. Therefore, we begin this chapter with a review of the theoretical and practical aspects of discrete choice models. After a brief discussion of general assumptions, we introduce the random utility model, which is the most common theoretical basis of discrete choice models. We then present the alternative discrete choice model forms such as Logit, Nested Logit, Generalized Extreme Value and Probit, as well as more recent developments such as Hybrid Logit and the Latent Class choice model. Finally, we elaborate on the applications of these models to two specific short-term travel decisions: route choice and departure time choice.
CITATION STYLE
Ben-Akiva, M., & Bierlaire, M. (2006). Discrete Choice Models with Applications to Departure Time and Route Choice. In Handbook of Transportation Science (pp. 7–37). Kluwer Academic Publishers. https://doi.org/10.1007/0-306-48058-1_2
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