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LLM and Natural Language Interaction / In-Vehicle and Autonomous Driving Voice Assistant Contexts

Designers struggle to evaluate driver-friendliness of in-vehicle voice prompts at low cost and high efficiency.

lightbulbPractical problemIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Designers struggle to evaluate driver-friendliness of in-vehicle voice prompts at low cost and high efficiency.

CUI '22A Question of Fidelity: Comparing Different User Testing Methods for Evaluating In-Car Prompts

Similar questions

lightbulbPractical problemIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Fixed-format voice assistants while driving cannot adapt to changes in user cognitive load, reducing safety.

CHI '24AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving Assistance

lightbulbPractical problemIn-Vehicle and Autonomous Driving Voice Assistant Contexts

In-vehicle voice assistant prompt design often ignores trade-offs between safety and user experience during driving.

CUI '23Secure, Comfortable or Functional: Exploring Domain-Sensitive Prompt Design for In-Car Voice Assistants

lightbulbPractical problemIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Drivers may have low trust and acceptance of autonomous driving voice assistants, affecting driving safety.

CUI '22Effects of Wording and Gendered Voices on Acceptability of Voice Assistants in Future Autonomous Vehicles

lightbulbPractical problemIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Proactively operating voice assistants while driving is distracting and affects driving safety.

UbiComp '21Learning When Agents Can Talk to Drivers Using the INAGT Dataset and Multisensor Fusion

Related papers

AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving Assistance

Shaoyue Wen, Songming Ping, Jialin Wang