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

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.

Happiness and high reliability develop affective trust in in-vehicle agents.

The advancement of Conditionally Automated Vehicles (CAVs) requires research into critical factors to achieve an optimal interaction between drivers and vehicles. The present study investigated the impact of driver emotions and in-vehicle agent (IVA) reliability on drivers' perceptions, trust, perceived workload, situation awareness (SA), and driving performance toward a Level 3 automated vehicle system. Two humanoid robots acted as the in-vehicle intelligent agents to guide and communicate with the drivers during the experiment.