Automated vehicles do not yet have clearly defined signaling methods towards other road users, which could complement natural communication practices with human drivers, such as eye contact or hand gestures. In order to establish trust, external human–machine interfaces (eHMIs) have been proposed, but so far, these have not been widely evaluated in natural traffic contexts. This paper presents a user study where 30 participants interacted with a functional display-based visual eHMI for an automated shuttle in mixed urban traffic. Two distinct features were investigated: the communication of (1) its awareness of different obstacles on the road ahead and (2) of its intention to start or to brake. The results indicate that the majority of participants in general regarded eHMIs as necessary for automated vehicles. When reflecting their experience with the eHMIs, about half of the participants experienced an increased comprehension and safety. The combined presentation of obstacle awareness and vehicle intentions helped more participants to understand the shuttle’s behavior than the presentation of obstacle awareness only, but fewer participants regarded this combination of awareness and intent to be safe. The strength of the found effects on subjective responses varied with regard to age and gender.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.