Bio-inspired intent communication for automated vehicles

Oudshoorn, Max; Winter, Joost de; Bazilinskyy, Pavlo; Dodou, Dimitra

doi:10.1016/j.trf.2021.03.021

Cited by 12 publications

(2 citation statements)

References 47 publications

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“…Our previous research confirms that the effects of eHMIs and vehicle appearances are generalisable and relatively independent of the participant's country of origin (e.g. [61]). In contrast, much of the psychological research is unable to examine international generalisability as the research is conducted with narrowly selected samples, such as university students.…”

Section: Limitationssupporting

confidence: 86%

Blinded windows and empty driver seats: The effects of automated vehicle characteristics on cyclists’ decision‐making

Bazilinskyy

Dodou

Eisma

et al. 2022

IET Intelligent Trans Sys

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Automated vehicles (AVs) may feature blinded (i.e. blacked-out) windows and external human-machine interfaces (eHMIs), and the driver may be inattentive or absent, but how these features affect cyclists is unknown. In a crowdsourcing study, participants viewed images of approaching vehicles from a cyclist's perspective and decided whether to brake. The images depicted different combinations of traditional vehicles versus AVs, eHMI presence, vehicle approach direction, driver visibility/window-blinding, visual complexity of the surroundings, and distance to the cyclist (urgency). The results showed that the eHMI and urgency level had a strong impact on crossing decisions, whereas visual complexity had no significant influence. Blinded windows caused participants to brake for the traditional vehicle. A second crowdsourcing experiment aimed to clarify the findings of Experiment 1 by also requiring participants to detect the vehicle features. It was found that the eHMI 'GO' and blinded windows yielded high detection rates and that driver eye contact caused participants to continue pedalling. To conclude, blinded windows increase the probability that cyclists brake, and driver eye contact stimulates cyclists to continue cycling. Our findings, which were obtained with large international samples, may help elucidate how AVs (in which the driver may not be visible) affect cyclists' behaviour.

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