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

触觉共享控制系统和测量系统信任的神经工学方法

• 批准号: EP/Y00194X/1
• 负责人: James Blundell
• 金额: $ 17.62万
• 依托单位: CRANFIELD UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY00194X%2F1
• 关键词: Haptic; Shared; Control; Systems; Neuroergonomic

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.

凭借足够的研发投资，英国预计到2035年通过自动化和机器人技术实行了一系列领域的经济增长。相关的应用领域包括未来连接的自动驾驶汽车的设计和安全，远程监控的遥控器以及与手术，护理，制造，建造和维护有关的人类机器人相互作用。实现足够的用户自动化信任对于在英国实现这一野心至关重要。衡量自动化的信任对于确定自动化接受及其正确用法至关重要。此外，决定信任的行为基于分析和情感决策的混合。这种复杂性意味着基于广泛的问卷的衡量信任方法不足。他们不仅努力衡量信任的全部复杂性，而且无法衡量信任的变化，因为它们是根据自动化经验实时发生的。与自动化互动期间的神经反应是实时衡量信任的潜在客观手段。我们自己发表的研究提倡使用功能性近红外光谱（FNIRS），其中确定了与情感信任判断相关的大脑区域。拥有情感信任的实时标记很重要，因为它允许与分析决策过程中没有耦合的信任度量；涉及一系列认知过程的过程，包括精神工作量。该建议的主要目标是确定自动化信任的独特神经测量。我们将通过平行测量和分析信任（FNIRS）的神经相关性（FNIRS）和精神工作量的生理相关性来应对这一挑战。自动化。通常，人类与自动化之间的责任是“交易”，因为整个整体都会从一个人到另一个。例如，自适应巡航控制功能在现代汽车中的功能。驾驶员可以将整个责任转移到汽车上，通常由按钮按下。同样，转移在自动紧急制动中是迅速而整体的，并且在感觉到即将发生碰撞时由自动化发起。这些过渡通常被称为“颠簸”，与安全妥协有关。有希望的替代交流方法是“触觉共享控制”。通过系统的控制输入（例如，方向盘，加速器踏板），通过对自动化行为进行连续的力反馈交流提供了更大的透明度。这意味着用户更好地将用户保存在“循环中”，从而支持自动化引起的故障的权威的“平稳”转移。但是，尚未进行研究，可以比较交易和触觉共享控制之间的信任。 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.我们将在一系列实验室和航空模拟实验中共同建立自动化信任的神经标记，涉及与自动化的队友执行协作任务，这些任务将以各种方式与人类参与者进行交流 - 即交易的交流与触觉共享控制沟通。