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A Multi-Modal Human–AI Collaboration Framework for E-Scooters: Evaluating AI Roles in User Preference

  • Wei Hsiang Lo
  • , Yu Wang
  • , Philipp Wintersberger
  • , Gaojian Huang*
  • *Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

E-scooters raise safety concerns, and an AI-driven system might help. Previous research suggests that AI can assist human users in three primary roles: Advisor, Co-pilot, or Guardian. Understanding the impact of presenting these AI roles with various modalities (e.g., visual, auditory, tactile) is crucial for their effectiveness. However, the effect of presenting AI roles in multiple modalities to e-scooter users remains unknown. Accordingly, this study examined user preferences for human-AI collaboration in e-scooters using a national survey. A total of 473 valid responses (mean age = 46.29) were collected. The results indicated no significant differences among AI roles. The auditory modality was preferred over both the visual and tactile modalities. Within each modality type, road projection was the most favored visual modality, an informative agent was preferred in the auditory modality, and the handlebar was preferred in the tactile modality. Overall, these findings support the development of future AI-driven micromobility systems.
Original languageEnglish
Pages (from-to)849-852
Number of pages4
JournalProceedings of the Human Factors and Ergonomics Society
Volume69
Issue number1
DOIs
Publication statusPublished - Sept 2025
Event69th Human Factors and Ergonomics Society Annual Meeting, HFES 2025 - Chicago, United States
Duration: 13 Oct 202517 Oct 2025

Keywords

  • e-scooter safety
  • human–AI collaboration
  • micromobility
  • multimodal human–machine interface
  • online survey

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