A multimodal interpreter with bird's-eye view, map, text, and LLM voice explanations increased self-reported passenger trust in simulated autonomous driving, by about 8% on average and up to 30% in normal conditions.
The role of human-automation consensus in multiple unmanned vehicle scheduling
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"What's Happening"- A Human-centered Multimodal Interpreter Explaining the Actions of Autonomous Vehicles
A multimodal interpreter with bird's-eye view, map, text, and LLM voice explanations increased self-reported passenger trust in simulated autonomous driving, by about 8% on average and up to 30% in normal conditions.