External human-machine interfaces on automated vehicles: Effects on pedestrian crossing decisions

Objective: In this article, we investigated the effects of external human-machine interfaces (eHMIs) on pedestrians’ crossing intentions. Background: Literature suggests that the safety (i.e., not crossing when unsafe) and efficiency (i.e., crossing when safe) of pedestrians’ interactions with automated vehicles could increase if automated vehicles display their intention via an eHMI. Methods: Twenty-eight participants experienced an urban road environment from a pedestrian’s perspective using a head-mounted display. The behavior of approaching vehicles (yielding, nonyielding), vehicle size (small, medium, large), eHMI type (1. baseline without eHMI, 2. front brake lights, 3. Knightrider animation, 4. smiley, 5. text [WALK]), and eHMI timing (early, intermediate, late) were varied. For yielding vehicles, the eHMI changed from a nonyielding to a yielding state, and for nonyielding vehicles, the eHMI remained in its nonyielding state. Participants continuously indicated whether they felt safe to cross using a handheld button, and “feel-safe” percentages were calculated. Results: For yielding vehicles, the feel-safe percentages were higher for the front brake lights, Knightrider, smiley, and text, as compared with baseline. For nonyielding vehicles, the feel-safe percentages were equivalent regardless of the presence or type of eHMI, but larger vehicles yielded lower feel-safe percentages. The Text eHMI appeared to require no learning, contrary to the three other eHMIs. Conclusion: An eHMI increases the efficiency of pedestrian-AV interactions, and a textual display is regarded as the least ambiguous. Application: This research supports the development of automated vehicles that communicate with other road users.