A Trust Model for Human-Machine Interaction in Virtual Reality

Human trust in machines is critical for effective human-machine interaction in virtual reality (VR). Prior work defined a three-layered framework of such trust but also indicated two deficiencies. Firstly, there is an absence of a model with metrics spanning all layers to objectively capture fluctuations of the trust (trust dynamics) in real time. Secondly, there is an inadequate consideration of human and machine reliability for the trust. Herein, this study proposed a trust model by defining metrics for all the layers and evaluated this model by considering human and machine reliability. Using objective and subjective data, the evaluation was based on two VR use-cases. The outcomes of the evaluation confirmed the pertinence of the model to capture trust dynamics in the presence of human and machine reliability. The objective data was notably more sensitive to capturing trust dynamics than the subjective counterpart. The model could enable designing trustworthy and adaptive VR.