Mode Choice Analysis Using Random Forrest Decision Trees

Mode choice analysis forms an integral part of transportation planning process as it gives a complete insight to the mode choice preferences of the commuters and is also used as an instrument for evaluation of introduction of new transport systems. Mode choice analysis involves the procedure to study the factors in decision making process of the commuter while choosing the mode that renders highest utility to them. This study aims at modelling the mode choice behaviour of commuters in Delhi by considering Random Forrest (RF) Decision Tree (DT) method. The random forest model is one of the most efficient DT methods for solving classification problems. For the purpose of model development, about 5000 stratified household samples were collected in Delhi through household interview survey. A comparative evaluation has been carried out between traditional Multinomial logit (MNL) model and Decision tree model to demonstrate the suitableness of RF models in mode choice modelling. From the result, it was observed that model developed by Random Forrest based DT model is the superior one with higher prediction accuracy (98.96%) than the Logit model prediction accuracy (77.31%). (C) 2016 Published by Elsevier B.V.