Using Ensembles of Decision Trees to Predict Transport Mode Choice Decisions: Effects on Predictive Success and Uncertainty Estimates

Studies predicting transport mode choice have typically relied on a single equation, relating observed mode choices to a set of personal and contextual variables. The model applies then to all individuals. This paper explores the idea to replace a single equation/representation with an ensemble of predictions, using the decision tree formalism. Potentially, using ensembles might better capture any heterogeneity in decision heuristics. Results of the study, conducted in the Rotterdam region, The Netherlands, suggest that the accuracy of predicting transport mode choice is improved, albeit non-monotonically, with increasing ensemble size. Simultaneously, the uncertainty related to these predictions is decreasing. Finally, it is shown that the importance of the selected explanatory variables co-varies with ensemble size. Estimation results tend to become stable with an ensemble size of approximately 20.