Authors:
J. A. Guerrero
;
M. C. Romero-Ternero
;
E. Personal
;
D. F. Larios
;
J. I. Guerra
and
C. León
Affiliation:
Department of Electronic Technology, Universidad de Sevilla, C/ Virgen de África, Seville, Spain
Keyword(s):
Emotional Computing, Driver Modelling, Electric Vehicle Fleet, Evolutionary Computation, Virtual Power Plant, Smart Grid.
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.
(More)