Travel time estimation provides valuable information for traveler routing and transportation scheduling. This paper presents a methodology to estimate travel time using a regression tree model. Vehicle speed is predicted by the regression tree model and it in turn is used as a proxy to estimate travel time, because historical data on travel time is currently unavailable. To maintain stable prediction ability in both free-flow conditions and near-capacity flow conditions on freeways, the regression tree model developed includes thirteen explanatory variables in four types: traffic flow variables, incident related variables, weather data variables and time of day variable. The research reported in this paper is focused on the I5-I205 loop in Portland, Oregon.
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