Dynamics and Variability in Within-Day Mode Choice Decisions

Abstract

This research investigated within-day dynamics and variations in mode choice within and across individuals at the activity-episode level. Specifically, dynamics and variability were examined at four levels: (a) effect of variation over time of explanatory attributes such as episode–trip characteristics, (b) influence of state-dependence (past choice decisions) on current choice, (c) role of habit persistence (i.e., the influence of lagged explanatory variables), and (d) the effect of unobserved preference heterogeneity that persists over repeated choices of individuals. A mixed-logit model was calibrated by using the rich activity-diary data from a 2000 activity-travel survey for the San Francisco Bay Area in California. Several alternative specifications of dynamics were tested. The aforementioned sources of variability and dynamics were found to be significant, and the empirical results showed a substantial improvement in model fit with the inclusion of these factors. The within-day dynamic model also outperformed alternative models in validation tests. The proposed model has important implications for improved activity-based demand models, travel demand forecasting, and evaluation of transportation control measures.

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