When more is less: Finding the optimal balance of intelligent agents' transparency in level 3 automated vehicles

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Date

2025-01

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Academic Press – Elsevier

Abstract

In automated vehicles, transparency of in-vehicle intelligent agents (IVIAs) is an important contributor to drivers’ perception, situation awareness, and driving performance. Our experiment focused on IVIA's transparency regarding information level and reliability on drivers’ perception and performance in level 3 automated vehicles. A 3 × 2 mixed factorial design was used in this study, with transparency (low, medium, high) as a between-subject variable and reliability (high vs. low) as a within-subjects variable. Forty-eight participants were recruited. Results suggested that transparency influenced drivers’ takeover time, lane keeping, and jerk. The high-reliability agent was associated with a higher perception of system accuracy and response speed and resulted in a longer takeover time than the low-reliability agent. Particularly, participants in medium transparency showed higher cognitive trust, lower workload, and higher situation awareness only when system reliability was high. Our findings can contribute to the advancement of intelligent agent transparency design in automated vehicles.

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Keywords

Intelligent agents, Automated vehicles, Transparency, Explainable AI, System reliability

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