发表机构
Texas Tech University（德克萨斯理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过VR模拟实验，比较事件触发与情境感知两种沟通策略，发现情境感知策略能提高沟通适当性并减少干扰，为主动式车内代理的沟通时机提供了设计依据。
AI 中文摘要
主动式车内代理可以帮助乘客理解自动驾驶车辆（AV）的行为，但传达每一个行驶事件可能会带来不必要的干扰。我们研究了沟通应如何根据事件优先级和乘客活动进行调整。在一项混合方法的受试者内研究中，41名参与者作为乘客乘坐于VR模拟的全自动驾驶车辆中。我们比较了一种事件触发（ET）策略，即在每个事件发生时立即进行沟通，与一种情境感知（CS）策略，该策略选择“立即”、“延迟”或“静默”沟通。CS策略提高了沟通的适当性，并显著减少了感知到的干扰。两种策略下的感知信任没有差异，尽管基线性格信任区分了沟通偏好。研究结果强调了事件后果、乘客活动、持续信息价值和确认需求是选择性车内沟通的关键考虑因素。
英文摘要
Proactive in-cabin agents can help passengers understand automated-vehicle (AV) behavior, but communicating every ride event may introduce unnecessary interruptions. We investigated how communication should adapt to event priority and passenger activity. In a mixed-methods within-subject study, 41 participants rode as passenger in a VR simulated fully-automated vehicle. We compared an event-triggered (ET) policy that communicated immediately at every event with a context-sensitive (CS) policy that selected \textit{Immediate}, \textit{Delayed}, or \textit{Silent} communications. CS increased communication appropriateness and substantially reduced perceived interruption. Perceived trust did not differ between policies, although baselines dispositional trust differentiated communication preferences. Findings highlight event consequence, passenger activity, continuing information value, and confirmation need as key considerations for selective in-cabin communication.
