Abstract
Research shows that human trust in automation is a key predictor of human reliance on the automation. Several models have been proposed to capture the interplay between trust and reliance and their combined impacts on task performance. Whereas some models assume that trust is affected by automation reliability, others assume that trust is affected by automation speed. In fact, both speed and reliability can be crucial for mission performance, therefore, these models do not represent the interrelationships among automation speed, automation reliability, human decision making, and subsequent effects on mission performance. To address this gap, we propose a system dynamics model which incorporates both the speed and reliability of automation and their combined effects on trust. Our model explicitly represents the speed-accuracy compromise adopted by the subjects to weigh the perceived relative importance of these aspects while evaluating the reliance decision. The model is calibrated and evaluated using data collected from a human experiment in which 33 subjects interacted with an automated aid for swarm supervision in a foraging mission. The simulation results show that the model can closely replicate and predict the experimental data in terms of the reliance rate and the number of targets collected. Model limitations and further efforts for model extension are discussed.