Effects of Automation Transparency on Trust: Evaluating HMI in the Context of Fully Autonomous Driving

Explainable AI (XAI)AI-Assisted Decision-Making & AutomationAutonomous Driving Engineers & Test DriversSoftware Engineers & DevelopersUI/UX Designers

Automation transparency offers a promising way for users to calibrate their trust in autonomous vehicles. However, it is still unknown what kind of information should be provided in driving scenarios with different risks and how this affects user trust. Driving scenarios based on different risks and Human-Machine-Interface (HMI) with different transparency based on Situation Awareness–Based Agent Transparency (SAT) model were developed to investigate the impact of risk and transparency on user trust using nine simulated fully autonomous drives within a static driving simulator environment. Results showed that driving scenario with lower-risk and HMI with higher-transparency increased user trust-related beliefs and intention to use. And perceived reliability and trust fully mediated the effects of risk and transparency on intention to use. The findings of this study provide insights on HMI transparency under different driving scenarios that may impact user trust.

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https://hci.top/en/papers/auto_ui/120672/2023

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Paper Snapshot

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Source
AutoUI
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Year
2023
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Authors
4 authors
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Subtopics
Explainable AI (XAI), AI-Assisted Decision-Making & Automation
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Professions
Autonomous Driving Engineers & Test Drivers, Software Engineers & Developers, UI/UX Designers
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Content Status
Abstract only
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