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PRODID:Linklings LLC
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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135145Z
LOCATION:Grand Hall L
DTSTART;TZID=America/Chicago:20251015T141000
DTEND;TZID=America/Chicago:20251015T143000
UID:HFESAM_ASPIRE 2025_sess266_LECT570@linklings.com
SUMMARY:A Multi-Modal Human–AI Collaboration Framework for E-Scooters: Eva
 luating AI Roles in User Preference
DESCRIPTION:Wei-Hsiang Lo (University of Michigan), Yu Wang (TU Wien), Phi
 lipp Wintersberger (IT:U Interdisciplinary Transformation University Austr
 ia), and Gaojian Huang (San Jose State University)\n\nThe rise of e-scoote
 rs raises safety issues, and an AI-driven system might be a potential solu
 tion. Previous frameworks show AI can support humans in three ways: Adviso
 r AI for information, Co-pilot AI for action, and Guardian AI to override 
 control. Understanding the impact of presenting these AI roles with variou
 s modalities (i.e., visual, auditory, tactile) is crucial for their effect
 iveness. However, the effect of presenting AI roles in multiple modalities
  to e-scooter users remains unknown. Therefore, this study assessed user p
 references for human-AI collaboration in e-scooters using a national surve
 y. A total of 473 valid responses (mean age = 46.29) were collected. The r
 esults indicated no differences among AI roles. The auditory modality was 
 preferred over visual and tactile. Within each modality type, road project
 ion was the most favored visual modality, the informative agent was prefer
 red in auditory, and the handlebar was preferred in tactile. Overall, thes
 e findings support the development of future AI-driven micromobility syste
 ms.\n\nTrack: Surface Transportation\n\nSession Chairs: Yiqi Zhang (Pennsy
 lvania State University) and Sakshi  Taori (Virginia Tech Polytechnic Inst
 itute and State University)\n\n
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