To Trust or Not to Trust? A Simulation-based Experimental Paradigm

The automated driving system is expected to enhance traffic safety and flow; however, the system will not be as effective if users do not accept it or do not utilize it appropriately. Appropriate acceptance and use of technology depends on attributes such as perceived risk, mental workload, self-confidence, and appropriate level of trust that matches system performance. An inappropriate level of trust in the technology, whether it is over-trust or undertrust, would negatively affect the benefits of that technology. Based on the literature, trust is a dynamic construct that consists of an initial or dispositional trust that is shaped before experiencing the system performance and a history-based trust that constantly changes with user experience of the system. This study first reviews the history of research on humans’ trust in automation and the factors that are correlated with trust. It also provides a brief overview of some previous models of trust in automation. Then, based on the gaps in the literature, a simulator-based experiment is proposed to further study the factors affecting initial or dispositioned trust and history-based trust. The results of this study are expected to help better understand drivers’ trust in automated vehicles and help enhance human-automation interaction models.

自动驾驶系统（automated driving system）有望提升交通安全与通行效率，但倘若用户未能接纳该系统，或是未恰当使用，其效能将大打折扣。技术的合理接纳与使用，取决于感知风险、心理负荷、自信心，以及与系统性能匹配的恰当信任水平等属性。对技术的信任水平失当——无论是过度信任还是信任不足——都会对该技术的应用效益产生负面影响。现有研究表明，信任是一个动态建构体，包含两类成分：一是在接触系统性能之前就已形成的初始信任，即特质信任（dispositional trust）；二是随用户对系统的使用体验持续变化的经验信任（history-based trust）。本研究首先梳理了人类对自动化（automation）信任的相关研究历程，以及与信任相关的各类影响因素，同时简要概述了过往提出的若干自动化信任模型。随后，针对现有研究的空白，本研究提出一项基于模拟器的实验，以进一步探究影响初始信任（或特质信任）与经验信任的各类因素。本研究预期成果将有助于更深入地理解驾驶员对自动驾驶汽车（automated vehicles）的信任机制，并助力优化人机自动化交互（human-automation interaction）模型。