Emotional Factor Forecasting based on Driver Modelling in Electric Vehicle Fleets

J. Guerrero, M. Romero-Ternero, E. Personal, D. Larios, J. Guerra, C. León

Abstract

Until recently, the automotive industry focus has been safety, comfort, and user experience. Now, the focus is shifting towards human emotion for driver-car interactions, autonomy and sustainability; all of them are increasing concerns in recent scientific literature. On the one hand, the growing role of emotion in automotive driving is empowering human-centred design coupled with affective computing in driving context to improve future automotive design. It is resulting in emotional analysis being present in automotive. This requires real-time data processing that involves energy consumption in the vehicle. On the other hand, electric vehicle fleets and smart grids are technologies that have provided new possibilities to reduce pollution and increase energy efficiency looking for sustainability. This paper proposes the emotional factor forecasting according to data gathered from electric vehicle fleet, based on the application of K-means algorithm. The results shows that is possible to forecast the emotional status that takes negative effect in the driving. Additionally, the Cronbach alpha variation analysis provides an interesting tool to select features from samples.

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Paper Citation


in Harvard Style

Guerrero J., Romero-Ternero M., Personal E., Larios D., Guerra J. and León C. (2020). Emotional Factor Forecasting based on Driver Modelling in Electric Vehicle Fleets.In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-423-7, pages 603-612. DOI: 10.5220/0009561406030612


in Bibtex Style

@conference{iceis20,
author={J. Guerrero and M. Romero-Ternero and E. Personal and D. Larios and J. Guerra and C. León},
title={Emotional Factor Forecasting based on Driver Modelling in Electric Vehicle Fleets},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2020},
pages={603-612},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009561406030612},
isbn={978-989-758-423-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Emotional Factor Forecasting based on Driver Modelling in Electric Vehicle Fleets
SN - 978-989-758-423-7
AU - Guerrero J.
AU - Romero-Ternero M.
AU - Personal E.
AU - Larios D.
AU - Guerra J.
AU - León C.
PY - 2020
SP - 603
EP - 612
DO - 10.5220/0009561406030612