Classifying Drivers' Behavior in Public Transport using Inertial Measurement Units and Decision Trees

Abstract

Santiago's public transit system uses a Passenger Service Quality Index (ICA) to measure the quality of service offered by buses companies. Parts of this index are related to bus driver's behavior, and are obtained in a superficial and very subjective manner. The main objective of this research is to formulate a new methodology that uses data provided by inertial measurement units to classify drivers' behavior. This is achieved by means of a classification method: decision trees. Data are collected to evaluate the method and results show that the use of decision trees delivers good performance and an interpretable output that allows further analysis. The proposal uses elements from the ICA index and produces a methodology that is simple, objective and capable of being implemented on a large scale with good performance at a low cost.

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