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. 2022 Feb 25:41:107992.
doi: 10.1016/j.dib.2022.107992. eCollection 2022 Apr.

Smartphone Sensor Dataset for Driver Behavior Analysis

Pawan Wawage  1 , Yogesh Deshpande  1
Affiliations

Smartphone Sensor Dataset for Driver Behavior Analysis

Pawan Wawage et al. Data Brief. .

Abstract

Driving is considered one of the most difficult tasks because the driver is responsible for a variety of other responsibilities in addition to driving. The primary responsibility of a driver should be to properly operate a vehicle while concentrating solely on driving. However, he/she must also complete various secondary jobs at the same time. Modeling realistic driving behavior proved tough for researchers and scientists. With this goal in mind, we constructed a Smartphone sensor dataset of Indian drivers, complete with driving parameters that have a significant impact on driving behavior. As a result, we created a dataset using Smartphone sensors such as the accelerometer and gyroscope. The data is organized into day-by-day folders, each with seven subfolders. We are confident that the suggested dataset will be beneficial in the training, testing, and validation of a machine learning model for driver behavior classification or reorganization.

Keywords: DB classification; Driver behavior analysis; Machine learning; Smartphone sensor dataset.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

    1. J. Ferreira Junior, E. Carvalho, BV. Ferreira, C. de Sou-za, Y. Suhara, A. Pentland, G. Pessin, “Driver Behaviour Profiling: An Investigation with Different Smartphone Sensors and Machine Learning”, PLoS One (2017), doi:10.1371/journal.pone.0174959. - DOI - PMC - PubMed
    1. Lu D.-N., Nguyen D.-N., Nguyen T.-H., Nguyen H.-N. Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones. Article, Sensors. 2018 doi: 10.3390/s18041036. - DOI - PMC - PubMed
    1. Baheti B., Gajre S., Talbar S. Detection of Distracted Driver Using Convolutional Neural Network. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2018 doi: 10.1109/CVPRW.2018.00150. - DOI
    1. K. Zinebi, N. Souissi, K. Tikito, Driver Behaviour Analysis Methods: Applications Oriented Study, Proceedings of the 3rd International Conference on Big Data, Cloud and Applications - BDCA 2018, Morocco.
    1. Wu M., Zhang S., Dong Y. A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors. Article, Sensors. 2016 doi: 10.3390/s16101746. - DOI - PMC - PubMed