CRII: HCC: Human-automation Interaction: Assistive and Adaptive Multimodal Interface to Support Older Adults in Complex Automated Systems

CRII：HCC：人机交互：辅助和自适应多模式界面，支持复杂自动化系统中的老年人

• 批准号: 2153504
• 负责人: Gaojian Huang
• 金额: $ 17.48万
• 依托单位: San Jose State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2153504&HistoricalAwards=false
• 关键词: CRII; HCC; Human; automation; Interaction

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Automated systems have been applied in a wide range of environments, such as in transportation, manufacturing, healthcare, or living. One particular demographic expected to benefit from the development of automated systems is adults aged 65 years and older. Older adults have become the fastest-growing age group globally. General age-related declines in cognitive and physical abilities may limit older adults’ ability to perform daily tasks, such as driving. In this case, automated systems (e.g., automated vehicles), may bring particular benefits for older adults to maintain daily task performance and independence. Given that current automated systems are often constrained by design limits and require human interventions, a reliable human-machine interface (HMI) is necessary to assist humans during the manual recovery process. Additionally, individual differences in cognitive and physical capabilities may lead to different task performances. It is necessary to examine how non-chronological age factors, such as cognitive and physical abilities, may impact adults’ performance and wellbeing in complex environments. This project aims to develop methods and tools to support older adults with different abilities in automated systems and to better understand how the aging process affects interaction with an interface. The outcomes of the project will contribute to the knowledge base in aging, automation, and human-machine interactions, as well as provide guidelines and recommendations for the design of next-generation automated systems for a wide range of user groups. By contributing to the scientific basis of human-automation interactions, the project will benefit the society by increasing human safety and wellbeing in automated systems. The PI will also initiate outreach programs in local senior centers, such as workshops and activities to educate the importance of successful aging, i.e., living an active and healthy lifestyle at the later stages of life. This project aims to conduct a series of human-subject experiments using automated driving simulations to investigate three areas. The first area is to explore the effects of multimodal displays, both visual (e.g., augmented reality) and tactile interfaces, on how quickly older adults intervene and takeover from an automated system. Second, the project will investigate the impacts of non-chronological factors on older adults’ task performance in data-rich complex environments. The final area explores whether visual and tactile interfaces, as multimodal displays, can mitigate individual differences in task performance. The project will collect empirical data and develop computational models on human behavior and performance with various capabilities and limitations. These could help researchers working in aging, human factors, and inclusive design and frameworks that address how non-chronological factors affect performance on complex tasks. For addressing individual differences in task performance, the project will investigate the effectiveness of adaptive multimodal displays on older adults’ takeover performance change. The research will also contribute designing models specific to automation takeovers and function/task allocation between machines and humans.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项全部或部分由2021年美国救援计划法案（公法117-2）资助。自动化系统已应用于广泛的环境中，如运输，制造，医疗保健或生活。预计将从自动化系统的发展中受益的一个特定人群是65岁及以上的成年人。老年人已成为全球增长最快的年龄组。与年龄相关的认知和身体能力的普遍下降可能会限制老年人执行日常任务的能力，例如驾驶。在这种情况下，自动化系统（例如，自动驾驶车辆）可能会为老年人带来特别的好处，以维持日常任务的执行和独立性。鉴于当前的自动化系统通常受到设计限制的约束，并且需要人为干预，因此需要可靠的人机界面（HMI）来在手动恢复过程中协助人类。此外，认知和身体能力的个体差异可能导致不同的任务表现。有必要研究非实足年龄因素，如认知和身体能力，如何影响成年人在复杂环境中的表现和健康。该项目旨在开发方法和工具，以支持在自动化系统中具有不同能力的老年人，并更好地了解衰老过程如何影响与界面的交互。该项目的成果将有助于老化，自动化和人机交互方面的知识基础，并为广泛的用户群体设计下一代自动化系统提供指导和建议。通过为人类与自动化交互的科学基础做出贡献，该项目将通过提高自动化系统中人类的安全和福祉来造福社会。PI还将在当地老年中心启动外展计划，如讲习班和活动，以教育成功老龄化的重要性，即，在生命的后期阶段保持积极健康的生活方式。该项目旨在使用自动驾驶模拟进行一系列人体实验，以调查三个领域。第一个领域是探索多模态显示的效果，无论是视觉（例如，增强现实）和触觉界面，关于老年人干预和接管自动化系统的速度。第二，本项目将研究非时序因素对老年人在数据丰富的复杂环境中任务绩效的影响。最后一个领域探讨视觉和触觉界面，作为多模态显示，是否可以减轻任务表现的个体差异。该项目将收集经验数据，并开发具有各种能力和限制的人类行为和表现的计算模型。这些可以帮助研究人员在老龄化，人为因素和包容性设计和框架中工作，以解决非时间因素如何影响复杂任务的表现。为了解决任务绩效的个体差异，该项目将调查适应性多模态显示对老年人接管绩效变化的有效性。该研究还将有助于设计特定于自动化接管和机器与人类之间的功能/任务分配的模型。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估而被认为值得支持。