SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Bazilinskyy P, Dodou D, de Winter JCF. Transp. Res. F Traffic Psychol. Behav. 2019; 67: 175-194.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.trf.2019.10.013

PMID

unavailable

Abstract

The automotive industry has presented a variety of external human-machine interfaces (eHMIs) for automated vehicles (AVs). However, there appears to be no consensus on which types of eHMIs are clear to vulnerable road users. Here, we present the results of two large crowdsourcing surveys on this topic. In the first survey, we asked respondents about the clarity of 28 images, videos, and patent drawings of eHMI concepts presented by the automotive industry.

RESULTS showed that textual eHMIs were generally regarded as the clearest. Among the non-textual eHMIs, a projected zebra crossing was regarded as clear, whereas light-based eHMIs were seen as relatively unclear. A considerable proportion of the respondents mistook non-textual eHMIs for a sensor. In the second survey, we examined the effect of perspective of the textual message (egocentric from the pedestrian's point of view: 'Walk', 'Don't walk' vs. allocentric: 'Will stop', 'Won't stop') and color (green, red, white) on whether respondents felt safe to cross in front of the AV. The results showed that textual eHMIs were more persuasive than color-only eHMIs, which is in line with the results from the first survey. The eHMI that received the highest percentage of 'Yes' responses was the message 'Walk' in green font, which points towards an egocentric perspective taken by the pedestrian. We conclude that textual egocentric eHMIs are regarded as clearest, which poses a dilemma because textual instructions are associated with practical issues of liability, legibility, and technical feasibility.


Language: en

Keywords

Automated vehicles; Crowdsourcing; External Human-Machine Interface (eHMI); Online surveys

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print