上路:探索自动驾驶汽车的人机信任

Yosef Razin, K. Feigh
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引用次数: 6

摘要

随着自动驾驶汽车在我们的道路上行驶,我们问的不是它们需要什么才能获得消费者的接受,而是它们可能对其他司机产生什么影响。他们将如何被感知,他们是否会被信任,可能会对交通流量和车辆安全产生重大影响。这项工作首先进行了探索性因素分析,以验证人机交互的信任量表,并展示了先前验证的度量和一般信任理论如何支持更完整的信任模型,该模型在驾驶领域的适用性增强。我们在模拟驾驶过程中,在人机交互的背景下对这个扩展模型进行了实验测试,揭示了如何使用这些维度揭示了人机信任中的重大偏差,当涉及到与自动驾驶车辆共享我们未来的道路时,这些偏差可能会产生特别有害的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hitting the Road: Exploring Human-Robot Trust for Self-Driving Vehicles
With self-driving cars making their way on to our roads, we ask not what it would take for them to gain acceptance among consumers, but what impact they may have on other drivers. How they will be perceived and whether they will be trusted will likely have a major effect on traffic flow and vehicular safety. This work first undertakes an exploratory factor analysis to validate a trust scale for human-robot interaction and shows how previously validated metrics and general trust theory support a more complete model of trust that has increased applicability in the driving domain. We experimentally test this expanded model in the context of human-automation interaction during simulated driving, revealing how using these dimensions uncovers significant biases within human-robot trust that may have particularly deleterious effects when it comes to sharing our future roads with automated vehicles.
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