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

Producción científica: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

3 Citas (Scopus)


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.

Idioma originalInglés
Título de la publicación alojadaSystems and Information Sciences - Proceedings of ICCIS 2020
EditoresMiguel Botto-Tobar, Willian Zamora, Johnny Larrea Plúa, José Bazurto Roldan, Alex Santamaría Philco
EditorialSpringer Science and Business Media Deutschland GmbH
Número de páginas10
ISBN (versión impresa)9783030591939
EstadoPublicada - 2021
Evento1st International Conference on Systems and Information Sciences, ICCIS 2020 - Manta, Ecuador
Duración: 27 jul. 202029 jul. 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1273 AISC


Conferencia1st International Conference on Systems and Information Sciences, ICCIS 2020

Nota bibliográfica

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

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


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