Characterization of Braking and Clutching Events of a Vehicle Through OBD II Signals

Paúl Andrés Molina Campoverde, Néstor Diego Rivera Campoverde, Gina Pamela Novillo Quirola, Andrea Karina Bermeo Naula

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This work presents an algorithm capable of identifying two habitual driving maneuvers such as braking to decrease speed and disengaging to produce a gear change in the vehicle by studying the PID’s (Identification Parameters) signals from the electronic control unit. These signals are acquired through the OBD II connector through a data logger device capable of storing information during the engine operation. The obtained data is prost-processed using K-mean unsupervised learning algorithm. The algorithm is capable of identifying braking and clutch events in addition to classifying whether the vehicle has a motorized or mechanical body acceleration system. With the used algorithm, it is possible to determine the pilot’s driving style and the most frequently used change during a route. For this research, four vehicles from different years and manufacturers were used to verify the functionality of the algorithm.

Original languageEnglish
Title of host publicationSystems and Information Sciences - Proceedings of ICCIS 2020
EditorsMiguel Botto-Tobar, Willian Zamora, Johnny Larrea Plúa, José Bazurto Roldan, Alex Santamaría Philco
PublisherSpringer Science and Business Media Deutschland GmbH
Pages134-143
Number of pages10
ISBN (Print)9783030591939
DOIs
StatePublished - 2021
Event1st International Conference on Systems and Information Sciences, ICCIS 2020 - Manta, Ecuador
Duration: 27 Jul 202029 Jul 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1273 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference1st International Conference on Systems and Information Sciences, ICCIS 2020
Country/TerritoryEcuador
CityManta
Period27/07/2029/07/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Braking
  • Clutching
  • Eco-driving
  • K-means
  • OBD II
  • PID’s signals

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