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This paper uses revealed preference and stated preference data collected from a web-based commuter survey in Austin, Texas, to estimate a commute mode choice model. This model accommodates weekly and daily commute and midday stop-making behavior, as well as travel time reliability. A mixed logit framework is used in estimation. The results emphasize the effects of commute and midday stop-making on commute mode choice. The results also indicate that travel time reliability is an important variable in commute mode choice decisions. The paper applies the estimated model to predict the potential mode usage of a proposed commuter rail option as well as to examine the impact of highway tolls. More generally, the mode choice model can be used to examine a whole range of travel mode-related policy actions for the Austin metropolitan region.