Objective We model the dynamic trust of human subjects in a human-autonomy-teaming screen-based task. Background Trust is an emerging area of study in human-robot collaboration. Many studies have looked at the issue of robot performance as a sole predictor of human trust, but this could underestimate the complexity of the interaction. Method Subjects were paired with autonomous agents to search an on-screen grid to determine the number of outlier objects. In each trial, a different autonomous agent with a preassigned capability used one of three search strategies and then reported the number of outliers it found as a fraction of its capability. Then, the subject reported their total outlier estimate. Human subjects then evaluated statements about the agent's behavior, reliability, and their trust in the agent. Results 80 subjects were recruited. Self-reported trust was modeled using Ordinary Least Squares, but the group that interacted with varying capability agents on a short time order produced a better performing ARIMAX model. Models were cross-validated between groups and found a moderate improvement in the next trial trust prediction. Conclusion A time series modeling approach reveals the effects of temporal ordering of agent performance on estimated trust. Recency bias may affect how subjects weigh the contribution of strategy or capability to trust. Understanding the connections between agent behavior, agent performance, and human trust is crucial to improving human-robot collaborative tasks. Application The modeling approach in this study demonstrates the need to represent autonomous agent characteristics over time to capture changes in human trust.

翻译：目的 本研究对人机协同屏幕任务中人类受试者的动态信任进行建模。背景 信任是人机协作领域的新兴研究方向。诸多研究将机器人性能视为人类信任的唯一预测因子，但这可能低估了交互的复杂性。方法 受试者与自主智能体配对完成屏幕网格搜索任务，以确定异常目标数量。每次试验中，具有预设能力的自主智能体采用三种搜索策略之一，并将其发现异常目标的数量汇报为自身能力的分数。随后，受试者报告其异常目标总数估计值，并评估关于智能体行为、可靠性及自身信任度的陈述。结果 共招募80名受试者。使用普通最小二乘法对自我报告信任度进行建模，但与短时间间隔内交互不同能力智能体的组别相比，采用ARIMAX模型的组别表现更优。通过交叉验证组间模型，发现下一试验信任预测有中等程度改善。结论 时间序列建模方法揭示了智能体性能的时间顺序对信任估计的影响。近因偏差可能影响受试者对策略或能力在信任中贡献权重的评估。理解智能体行为、性能与人类信任之间的关联对改进人机协作任务至关重要。应用 本研究的建模方法表明，需在时间维度上表征自主智能体特征以捕捉人类信任的变化。