Go Ahead, Please!—Evaluation of External Human—Machine Interfaces in a Real-World Crossing Scenario

Alexandra Loew, Julia Graefe, Lukas Heil, Anne Guthardt, Annika Boos, André Dietrich, Klaus Bengler

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In the future, automated vehicles (AVs) without a human driver will potentially have to manage communication with vulnerable road users, such as pedestrians, in everyday traffic interaction situations. The aim of this work is to investigate pedestrian reactions to external communication concepts in a controlled, but real-world crossing scenario. The focus is to investigate which properties of external human–machine interfaces (eHMIs) promote the comprehensibility of vehicle intention (yielding for the pedestrian) and therefore lead to faster and, at the same time, safer crossing decisions of pedestrians. For this purpose, three different eHMI concepts (intention-based light-band, perception-based light-band, and the combination of light-band and signal lamp) were examined and compared to a baseline (no eHMI). In a Wizard-of-Oz experiment, participants (n = 30) encountered a test vehicle equipped with the eHMIs in a real-world crossing scenario. The crossing initiation time in seconds and the participant's intention recognition were measured. Furthermore, the influence of the eHMIs on acceptance and perceived safety was evaluated. It was shown that the presence of the intention-based light-band, and the combination of light-band and signal lamp led to an earlier crossing decision compared to baseline with no eHMI. In summary, the results indicate that the intention-based light-band has a positive effect on the comprehensibility of the vehicle's intention. All concepts were evaluated positively regarding acceptance and perceived safety, and did not differ significantly from each other.

Original languageEnglish
Article number863072
JournalFrontiers in Computer Science
Volume4
DOIs
StatePublished - 14 Jun 2022

Keywords

  • Wizard-of-Oz
  • automated driving
  • external human-machine interfaces
  • human-computer interaction
  • real-world study
  • vulnerable road user

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