Haptic Shared Control Systems And A Neuroergonomic Approach To Measuring System Trust

随着足够的研发投入，预计到2035年，通过自动化和机器人技术，英国一系列行业将出现显着的经济增长。相关应用领域包括未来联网自动驾驶车辆的设计和安全、远程监控远程操作，以及涉及手术、护理、制造、建筑和维护的人-机器人交互。在英国实现这一雄心壮志的关键是在自动化方面获得足够的用户信任。衡量对自动化的信任度对于确定自动化的接受度和正确使用至关重要。此外，决定信任的行为是基于分析性和情绪性决定的混合。这种复杂性意味着，广泛使用的基于问卷的信任衡量方法是不够的。它们不仅难以测量信任的全部复杂性，而且无法测量信任的变化，因为它们响应于自动化体验而实时发生。测量与自动化交互过程中的神经反应是实时测量信任的潜在客观手段。我们自己发表的研究主张使用功能性近红外光谱(FNIRS)，即大脑中与情绪信任判断相关的区域被识别。拥有一个实时的情感信任标记是很重要的，因为它允许信任的测量不受分析决策过程的影响；分析决策过程涉及一系列认知过程，包括脑力劳动。这项建议的主要目标是确定自动化信任的独特神经测量。在参与者与不同可靠性的自动化队友互动的实验中，我们将通过平行测量和分析神经信任相关性(FNIRS)和精神工作负荷的生理相关性(心率变异性、斜率测量、皮肤电流反应)来应对这一挑战。为了演示自动化信任的独特神经标记物的应用，我们将研究信任如何随着人与自动化之间的沟通方法而变化。按照惯例，人类和自动化之间的责任是作为一个整体从一个人“交换”到另一个人的。例如，自适应巡航控制在现代汽车中的作用方式。司机可以将全部责任转移到汽车上，通常是通过按下按钮启动的。同样，在自动紧急制动中，传输快速而完整，并在检测到即将发生的碰撞时由自动化启动。这些过渡通常被称为“颠簸”，并牵涉到对安全的妥协。另一种很有前途的交流方式是“触觉共享控制”。它通过系统的控制输入(例如方向盘、油门踏板)对自动化行为进行持续的力反馈通信，从而提供更大的透明度。这意味着用户可以更好地“了解情况”，支持“平稳”的权限转移，以响应自动化引发的故障。然而，还没有研究对交易控制和触觉共享控制之间的信任进行比较。因此，目前的建议旨在不仅提供一个应用神经测量的自动化信任的演示，而且还解决了围绕触觉共享控制和信任的基本知识缺乏的问题。为了实现这一雄心勃勃的研究，我们将专注于启动考文垂大学和TU Delft之间的合作学术关系，这两所大学分别是操作员生理监控和触觉共享控制方面的世界专家。我们将共同在一系列实验室和航空模拟实验中建立自动化信任的神经标记，这些实验涉及与自动化队友执行协作任务，这些协作任务将以各种方式与人类参与者进行通信-即交换通信与触觉共享控制通信。

With sufficient R&D investment the UK is forecasted to experience significant economic growth across a range of sectors by 2035 delivered through automation and robotics. Relevant application areas include the design and safety of future connected autonomous vehicles, remotely monitored teleoperations, and human-robot interactions involved in surgery, nursing, manufacturing, construction, and maintenance. Achieving sufficient user trust in automation is pivotal to realising this ambition in the UK. Measuring trust in automation is critical for determining automation acceptance and its correct usage. In addition, the act of deciding to trust is based on a mixture of analytic and emotional decisions. This complexity means that the widely used questionnaire-based methods of measuring trust are insufficient. Not only do they struggle to measure the full complexity of trust, but they cannot measure changes in trust as they occur in real-time in response to automation experience.Measuring neural responses during interaction with automation is a potential objective means to measuring trust in real-time. Our own published research has advocated using functional near infrared spectroscopy (fNIRS) where areas of the brain associated with emotional trust judgements were identified. Having a real-time marker of emotional trust is important as it allows for a measure of trust that is uncoupled from analytical decision processes; processes that are involved in a range of cognitive processes, including mental workload. The primary goal of this proposal is to identify a unique neural measurement of automation trust. We will tackle this challenge through the in parallel measurement and analysis of neural correlates of trust (fNIRS) and physiological correlates of mental workload (heart rate variability, pupillometry, galvanic skin response) during experiments where participants interact with automated teammates of varying reliable.To demonstrate the application of a unique neural marker of automation trust we will examine how trust changes in response to the communication method between humans and automation. Conventionally, responsibility between humans and automation is "traded" from one to another as a lumped whole. For instance, the way adaptive cruise control functions in modern cars. The driver can transfer whole responsibility to the car, typically initiated by a button press. Likewise, transfers are rapid and whole in automatic emergency braking, and initiated by the automation when an imminent collision is sensed. These transitions are often called "bumpy" and are implicated in compromises to safety. A promising alternative communication method is "haptic shared control". It offers greater transparency through the continuous force feedback communication of the automation's behaviour via the system's control input (e.g., steering wheel, accelerator pedal). This means that the user is better kept "in the loop", supporting "smooth" shifts of authority in response to automation-induced faults. However, no studies have been conducted providing a comparison of trust between traded and haptic shared control. Hence, the current proposal aims to provide not an only a demonstration of the application of a neural measure of automation trust, but also addresses the fundamental lack of knowledge surrounding haptic shared control and trust.To realise this ambitious research, we will focus on initiating a collaborative academic relationship between Coventry University and TU Delft, respective world-experts in operator physiological monitoring and haptic shared control. Together we will establish neural markers of automation trust in a series of laboratory and aviation simulation experiments that involve performing collaborative tasks with automated teammates that will communicate with human participants in various ways - i.e. traded communication versus haptic shared control communication.