Automated vehicles promise to improve urban mobility, but passenger trust remains a challenge. Providing timely, passenger-specific explanations for automated vehicle decisions can bridge this trust gap. To address this, researchers introduced TimelyTale, a dataset designed to capture real-world driving scenarios and passenger explanation needs. It would be nice to see this multimodal dataset approach for in-vehicle explanation generation improving passengers' trust and confidence in automated vehicles.
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