Biased energy efficiency perception based on instantaneous consumption displays – Indication for heuristic energy information processing


Art der Publikation: Journal Article

Veröffentlicht auf / in: Applied Ergonomics

Jahr: In Press

Verlag (Publisher): Elsevier


Vivien Moll

Thomas Franke


Instantaneous consumption displays (ICDs) can be used as central information source to perceive the energy efficiency of manoeuvre-level driving. A key question is whether drivers who use ICDs can accurately derive energy efficiency differences of different driving strategies based on ICDs. There is reason to assume that drivers’ consumption judgements may be biased, similar to driving-related phenomena like the time-saving bias. Therefore, the aim of the present research was to examine drivers’ accuracy in deriving average consumption from dynamic ICD sequences. Participants viewed videos of a schematic ICD in a controlled experiment where the maximum instantaneous consumption systematically varied over time. Participants (N = 55) overestimated the average consumption values. The empirical ranking of the sequences did significantly correlate with the heuristic but not with the correct efficiency ranking. The current study incorporated multilevel modelling due to the nested structure of the data. The estimation difference was greater with higher peak height and shorter peak duration. The effect of peak height on estimation difference weakened with longer peak duration. In sum, the results indicate that ICDs can create biased perceptions of energy efficiency and that drivers seem to use simplifying heuristics. Knowledge and affinity for technology interaction appear to relate to biased estimations, whereas the intensity of prior experience with consumption displays seems irrelevant. Further studies should test other interfaces with debiasing potential such as manoeuvre-based aggregation or fading-trace approaches. Moreover, studies are needed that enable modelling of the effects of more natural temporal- spatial visual attention distribution (e.g. in a driving simulator setting).


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