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.
|Title of host publication||Systems and Information Sciences - Proceedings of ICCIS 2020|
|Editors||Miguel Botto-Tobar, Willian Zamora, Johnny Larrea Plúa, José Bazurto Roldan, Alex Santamaría Philco|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||10|
|State||Published - 2021|
|Event||1st International Conference on Systems and Information Sciences, ICCIS 2020 - Manta, Ecuador|
Duration: 27 Jul 2020 → 29 Jul 2020
|Name||Advances in Intelligent Systems and Computing|
|Conference||1st International Conference on Systems and Information Sciences, ICCIS 2020|
|Period||27/07/20 → 29/07/20|
Bibliographical notePublisher 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.
- OBD II
- PID’s signals