Exploring the effectiveness of external human-machine interfaces on pedestrians and drivers

Young Woo Kim, Jae Hyun Han, Yong Gu Ji, Seul Chan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Previous literature provided the results that eHMIs can be an effective method in interacting with pedestrians. However, there remains a question whether eHMIs are also effective for other road users or not. Therefore, the present study aimed to explore subjective evaluations on eHMIs with two different perspectives, pedestrians and drivers around AVs. Subjective preferences to different types of eHMIs were investigated through an online survey. Nine types of eHMIs were designed based on the combinations of display location and sign format. The results showed that people have different attitudes towards eHMIs depending on their perspectives. The participants as driver evaluated the bottom condition negatively compared to the pedestrian, and the participants as pedestrians felt that icons are not a good option compared to the drivers. The findings of the present study contribute to design of eHMI considering various road users.

Original languageEnglish
Title of host publicationAdjunct Proceedings - 12th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2020
PublisherAssociation for Computing Machinery, Inc
Pages65-68
Number of pages4
ISBN (Electronic)9781450380669
DOIs
Publication statusPublished - 2020 Sep 21
Event12th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2020 - Washington, Virtual, United States
Duration: 2020 Sep 212020 Sep 22

Publication series

NameAdjunct Proceedings - 12th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2020

Conference

Conference12th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2020
CountryUnited States
CityWashington, Virtual
Period20/9/2120/9/22

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Software
  • Automotive Engineering

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