The Role of Interaction Patterns with Hybrid Electric Vehicle Eco-Features for Drivers' Eco-Driving Performance


Art der Publikation: Journal Article

Veröffentlicht auf / in: Human Factors

Jahr: 2017

Band / Volume: 59

Seiten: 314-327

Verlag (Publisher): Human Factors and Ergonomics Society


ISSN: 1547-8181


Matthias G. Arend

Thomas Franke


The objective of the present research was to understand drivers' interaction patterns with hybrid electric vehicles' (HEV) eco-features (electric propulsion, regenerative braking, neutral mode) and their relationship to fuel efficiency and driver characteristics (technical system knowledge, eco-driving motivation).Eco-driving (driving behaviors performed to achieve higher fuel efficiency) has the potential to reduce CO2 emissions caused by road vehicles. Eco-driving in HEVs is particularly challenging due to the systems' dynamic energy flows. As a result, drivers are likely to show diverse eco-driving behaviors, depending on factors like knowledge and motivation. The eco-features represent an interface for the control of the systems' energy flows.A sample of 121 HEV drivers who had constantly logged their fuel consumption prior to the study participated in an online questionnaire.Drivers' interaction patterns with the eco-features were related to fuel efficiency. A common factor was identified in an exploratory factor analysis, characterizing the intensity of actively dealing with electric energy, which was also related to fuel efficiency. Driver characteristics were not related to this factor, yet they were significant predictors of fuel efficiency.From the perspective of user-energy interaction, the relationship of the aggregated factor to fuel efficiency emphasizes the central role of drivers' perception of and interaction with energy conversions in determining HEV eco-driving success.To arrive at an in-depth understanding of drivers' eco-driving behaviors that can guide interface design, authors of future research should be concerned with the psychological processes that underlie drivers' interaction patterns with eco-features.


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