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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135147Z
LOCATION:Grand Hall G/H
DTSTART;TZID=America/Chicago:20251017T080000
DTEND;TZID=America/Chicago:20251017T082000
UID:HFESAM_ASPIRE 2025_sess314_LECT296@linklings.com
SUMMARY:Understanding User Needs in Automated Vehicle Explanations: A Qual
 itative Approach
DESCRIPTION:Qiaoning Zhang (Arizona State University) and X. Jessie Yang a
 nd Lionel Robert (University of Michigan)\n\nClear explanations about auto
 mated vehicle (AV) decisions are critical for enhancing user understanding
  and reducing uncertainty. However, how users perceive different types of 
 AV explanations and how they would improve them remains underexplored. Thr
 ough qualitative interviews, this study explored user responses to four ty
 pes of AV explanations: no explanation, action explanations ("what"), reas
 oning explanations ("why"), and combined action and reasoning ("what and w
 hy"). Participants highlighted clear differences: the absence of explanati
 ons caused anxiety and confusion, while explanations offering reasons or a
 ctions alone each had strengths and weaknesses. Combined explanations gene
 rally offered the best balance by enhancing predictability and transparenc
 y, though they occasionally risked information overload. Participants also
  suggested practical improvements for AV explanations, emphasizing the inc
 lusion of visual cues, clear descriptions of consequences, and delivery th
 rough natural conversational speech. These insights underscore the importa
 nce of adaptable explanation designs tailored to diverse user preferences 
 and contexts. Overall, this research provides user-driven recommendations 
 for designing effective AV explanations, enhancing transparency and streng
 thening public trust in automated driving technologies.\n\nTrack: User Exp
 erience\n\nSession Chair: April Melody Hui En Tan (Iowa State University)\
 n\n
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