Driver Classification Based on Driving Behaviors

Abstract

In this paper we develop a model capable of classifying drivers from their driving behaviors sensed by only low level sensors. The sensing platform consists of data available from the diagnostic outlet (OBD) of the car and smartphone sensors. We develop a window based support vector machine model to classify drivers. We test our model with two datasets collected under both controlled and naturalistic conditions. Furthermore, we evaluate the model using each sensor source (car and phone) independently and combining both the sensors. The average classification accuracies attained with data collected from three different cars shared between couples in a naturalistic environment were 75.83%, 85.83% and 86.67% using only phone sensors, only cars sensors and combined car and phone sensors respectively.

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