The Effect of In-Car Agent Embodiment on Different Types of Information Delivery

要旨

As vehicles become more advanced, in-car agents must manage increasingly complex interactions, heightening the need for effective information delivery. This paper investigates how different embodiments of in-car agents affect the delivery of various information types. We developed the ‘Drop-lit’ prototype to explore three embodiment features: physicality, characterization, and movement. In a user study with 20 participants, we compared three representative agent designs: abstraction, digital character, and mixed-media, across six categories of in-car information. Additionally, a co-design session allowed participants to self-customize and combine embodiment features for six specific driving scenarios. Results indicated that mixed-media agents were most effective for urgent warnings, digital characters for recommendations, and abstracted agents for simple reference information. The study also revealed how embodiment influenced experiential factors such as attention-grabbing, urgency, friendliness, trustworthiness, and playfulness, offering insights for optimizing agent design to enhance user engagement and information delivery in automotive contexts.

著者
Bonhee Ku
KAIST, Daejeon, Korea, Republic of
Chang-Min Kim
KAIST, Daejeon, Korea, Republic of
Hyungjun Cho
KAIST, Daejeon, Korea, Republic of
Jisu Park
KAIST, Daejeon, Korea, Republic of
Tek-Jin Nam
KAIST, Daejeon, Korea, Republic of
DOI

10.1145/3706598.3713255

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713255

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Embodiment and Immersion

Annex Hall F203
7 件の発表
2025-04-29 18:00:00
2025-04-29 19:30:00
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