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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135147Z
LOCATION:Grand Hall M/N
DTSTART;TZID=America/Chicago:20251015T135000
DTEND;TZID=America/Chicago:20251015T141000
UID:HFESAM_ASPIRE 2025_sess300_LECT297@linklings.com
SUMMARY:Voice Similarity and Its Impact on Cognitive and Affective Trust i
 n Automated Vehicles
DESCRIPTION:Qiaoning Zhang (Arizona State University) and X. Jessie Yang a
 nd Lionel Robert (University of Michigan)\n\nAs automated vehicles (AVs) b
 ecome more integrated into our daily lives, building user trust is critica
 l to their widespread adoption. This study explores how the voice used by 
 AVs can influence two types of trust: cognitive trust (belief in the AV’s 
 competence and reliability) and affective trust (emotional connection with
  the AV). Drawing from similarity-attraction theory, the research investig
 ates whether users are more likely to trust AVs whose voices match their o
 wn age and gender. In an online study with over 300 U.S. drivers, particip
 ants experienced AV explanations delivered in voices that either aligned w
 ith or differed from their demographic characteristics. Results revealed t
 hat users reported significantly higher trust, both cognitive and affectiv
 e, when the AV voice matched their own. Gender similarity had a strong imp
 act on both types of trust, while age similarity mainly affected affective
  trust. These findings highlight the power of personalized voice design in
  making AVs feel more relatable and trustworthy. This research offers valu
 able insights for designers and developers aiming to improve human-AV inte
 raction through more socially attuned and emotionally resonant communicati
 on strategies.\n\nTrack: User Experience\n\nMini-Conferences: UX Mini-Conf
 erence\n\nSession Chair: Zeinab Kazemi (Clemson University )\n\n
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