Trust Dynamics in Human-AV (Automated Vehicle) Interaction
Trust Dynamics in Human-AV (Automated Vehicle) Interaction
复制标题
人机交互中的信任动态
DOI：
10.1145/3334480.3382970
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
X. J. Yang
中科院分区：
文献类型：
--
作者：
Ruikun Luo;Jian Chu;X. J. Yang
尽管自动驾驶有很多好处，例如减少油耗、交通拥堵和碰撞事故，但缺乏信任阻碍了自动驾驶汽车 (AV) 的采用。之前的研究主要基于自动驾驶汽车的整体性能来研究人们对自动驾驶汽车的信任度。本研究的重点是在连续决策环境中人们对自动驾驶汽车的信任随着时间的推移而变化。我们在虚拟 3D 环境中对 16 名参与者进行了人机循环实验，其中参与者扮演乘坐自动驾驶汽车的乘客。我们操纵了两个自变量：随机性水平（高与低）和随机性来源（外部与内部）。因变量包括参与者对自动驾驶汽车的即时信任和实验后信任。我们的结果表明，与外部错误（例如交通堵塞或路障）相比，当随机性是由于内部错误（例如自动驾驶汽车的传感器错误）引起时，参与者对自动驾驶汽车的信任度下降得更明显。此外，由于错误而导致的成本越大，信任度下降就越大。
Despite many benefits of automated driving, such as reducing fuel consumption, traffic congestion and crashes, a lack of trust hinders the adoption of automated vehicles (AVs). Prior research focused on people's trust in AVs based on AVs' overall performance. The present study is focused on people's trust change in AVs over time in a sequential decision making context. We conducted a human-in-the-loop experiment with 16 participants in a virtual 3D environment wherein participants acted as passengers riding an AV. We manipulated two independent variables: level of stochasticity (high vs. low) and source of stochasticity (external vs. internal). Dependent variables included participants' moment-to-moment trust in AVs and post-experiment trust. Our results revealed that when the stochasticity was due to internal errors (e.g. AV's sensor errors) as compared to external errors (e.g. traffic jams or road blocks), participants' trust in AVs decreased more significantly. Also, the larger the cost due to an error, the larger the trust decrement.
影响因子：
7.6
作者：
BARON, J;HERSHEY, JC
通讯作者：
HERSHEY, JC