Discrete Choice Methods and Their Applications to Short Term Travel Decisions

Modeling travel behavior is a key aspect of demand analysis, where aggregate demand is the accumulation of individuals’ decisions. In this chapter, we focus on “short-term” travel decisions. The most important short-term travel decisions include choice of destination for a non-work trip, choice of travel mode, choice of departure time and choice of route. It is important to note that short-term decisions are conditional on long-term travel and mobility decisions such as car ownership and residential and work locations. 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.