Citation

Ferreira J, Carvalho E, Ferreira BV, de Souza C, Suhara Y, Pentland A, Pessin G. PLoS One 2017; 12(4): e0174959.

Affiliation

Institute of Exact and Natural Sciences, Federal University of Pará, Belém - PA, Brazil.

Copyright

(Copyright © 2017, Public Library of Science)

DOI

10.1371/journal.pone.0174959

PMID

28394925

Abstract

Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver behavior profiling tries to understand and positively impact driver behavior. Usually driver behavior profiling tasks involve automated collection of driving data and application of computer models to generate a classification that characterizes the driver aggressiveness profile. Different sensors and classification methods have been employed in this task, however, low-cost solutions and high performance are still research targets. This paper presents an investigation with different Android smartphone sensors, and classification algorithms in order to assess which sensor/method assembly enables classification with higher performance. The results show that specific combinations of sensors and intelligent methods allow classification performance improvement.

Language: en