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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

A Novel Compound Feature based Driver Identification

Author 1: Md. Abbas Ali Khan
Author 2: Mohammad Hanif Ali
Author 3: AKM Fazlul Haque
Author 4: Md. Iktidar Islam
Author 5: Mohammad Monirul Islam

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0131269

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 12, 2022.

  • Abstract and Keywords
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Abstract: In today's world, it is time to identify the driver through technology. At present, it is possible to find out the driving style of the drivers from every car through controller area network (CAN-BUS) sensor data which was not possible through the conventional car. Many researchers did their work and their main purpose was to find out the driver driving style from end-to-end analysis of CAN-BUS sensor data. So, it is potential to identify each driver individually based on the driver's driving style. We propose a novel compound feature-based driver identification to reduce the number of input attributes based on some mathematical operation. Now, the role of machine learning in the field of any type of data analysis is incomparable and significant. The state-of-the-art algorithms have been applied in different fields. Occasionally these are tested in a similar domain. As a result, we have used some prominent algorithms of machine learning, which show different results in the field of aspiration of the model. The other goal of this study is to compare the conspicuous classification algorithms in the index of performance metrics in driver behavior identification. Hence, we compare the performance of SVM, Naïve Bayes, Logistic Regression, k-NN, Random Forest, Decision tree, Gradient boosting.

Keywords: Compound feature; driver behavior identification; engine speed; fuel consumption; vehicle

Md. Abbas Ali Khan, Mohammad Hanif Ali, AKM Fazlul Haque, Md. Iktidar Islam and Mohammad Monirul Islam, “A Novel Compound Feature based Driver Identification” International Journal of Advanced Computer Science and Applications(IJACSA), 13(12), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131269

@article{Khan2022,
title = {A Novel Compound Feature based Driver Identification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131269},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131269},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {12},
author = {Md. Abbas Ali Khan and Mohammad Hanif Ali and AKM Fazlul Haque and Md. Iktidar Islam and Mohammad Monirul Islam}
}


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