title: Driver behavior profiling: An investigation with different smartphone sensors and machine learning.
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.
authors.affiliation: Applied Computing Lab, Instituto Tecnológico Vale, Belém - PA, Brazil.|Institute of Exact and Natural Sciences, Federal University of Pará, Belém - PA, Brazil.
authors.forename: Jair
authors.initials: J
authors.lastname: Ferreira
authors.affiliation: Applied Computing Lab, Instituto Tecnológico Vale, Belém - PA, Brazil.|SENAI Institute of Innovation - Mineral Technologies, Belém - PA, Brazil.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Carvalho
authors.affiliation: Applied Computing Lab, Instituto Tecnológico Vale, Belém - PA, Brazil.|SENAI Institute of Innovation - Mineral Technologies, Belém - PA, Brazil.
authors.forename: Bruno V
authors.initials: BV
authors.lastname: Ferreira
authors.affiliation: Applied Computing Lab, Instituto Tecnológico Vale, Belém - PA, Brazil.|Institute of Exact and Natural Sciences, Federal University of Pará, Belém - PA, Brazil.
authors.forename: Cleidson
authors.initials: C
authors.lastname: de Souza
authors.affiliation: Recruit Institute of Technology, Mountain View - CA, United States of America.
authors.forename: Yoshihiko
authors.initials: Y
authors.lastname: Suhara
authors.affiliation: Media Lab, Massachusetts Institute of Technology, Cambridge - MA, United States of America.
authors.forename: Alex
authors.initials: A
authors.lastname: Pentland
authors.affiliation: Applied Computing Lab, Instituto Tecnológico Vale, Belém - PA, Brazil.|Institute of Exact and Natural Sciences, Federal University of Pará, Belém - PA, Brazil.
authors.forename: Gustavo
authors.identifier: http://orcid.org/0000-0002-7411-9229
authors.initials: G
authors.lastname: Pessin
mesh_terms: D061725:Accelerometry / Q000295:instrumentation; D019540:Area Under Curve; D001334:Automobile Driving / Q000523:psychology; D001499:Bayes Theorem; D001519:Behavior; D006801:Humans; D000069550:Machine Learning; D016571:Neural Networks, Computer; D012372:ROC Curve; D000068997:Smartphone / Q000295:instrumentation*