Date of Award
Master of Science
This thesis addresses the problem of prediction of taxi trip duration for any given
day, time, pickup point and dropo point. Data on taxi trips from the Chicago Data
Portal is used. The main idea of the model is to cluster similar trips together and use
the mean duration of all those clustered taxi trips to predict the duration of a new taxi
trip in that cluster. Furthermore, for a possible additional reduction of prediction error,
estimators from dierent days which are not signicantly dierent from each other are
pooled together. It is shown that this procedure improves prediction error.
Bitter, Frank, "A Statistical Model for the Prediction of the Taxi Trip Time in the City of Chicago" (2020). Theses and Dissertations. 2350.