Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems.

ABSTRACT: Trust is critical for human-automation collaboration, especially under safety-critical tasks such as driving. Providing explainable information on how the automation system reaches decisions and predictions can improve system transparency, which is believed to further facilitate driver trust and user evaluation of the automated vehicles. However, what the optimal level of transparency is and how the system communicates it to calibrate drivers' trust and improve their driving performance remain uncertain. Such uncertainty becomes even more unpredictable given that the system reliability remains dynamic due to current technological limitations. To address this issue in conditionally automated vehicles, a total of 30 participants were recruited in a driving simulator study and assigned to eit

SUBMITTER: Taylor S 

PROVIDER: S-EPMC10232983 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature