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CAREER: Enhancing Trust-Driven Human-Autonomy Interaction: Modeling Trust Dynamics and Supporting Trust Calibration

CAREER: Enhancing Trust-Driven Human-Autonomy Interaction: Modeling Trust Dynamics and Supporting Trust Calibration
职业:增强信任驱动的人类自主交互:对信任动态进行建模并支持信任校准
批准号:
2045009
负责人:
Xi Jessie Yang
金额:
$54.98万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-05-01 至 2026-04-30

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中文摘要
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英文摘要
This project aims to tackle a fundamental question at the heart of human-technology partnership: How can designers facilitate the establishment of appropriate trust in technology? Advanced technologies such as autonomous vehicles and collaborative robots are entering every sector of the economy and will fundamentally alter the way people live and work. However, realizing the full economic, safety, and health potential of these technologies is only possible if people establish appropriate trust in them. This project aims to understand and model the formation and evolution of trust, and to develop adaptive autonomy that facilitates the establishment of appropriate trust. The project advances STEM education and workforce development by nurturing the next generation of scientists in human-autonomy interaction, and by developing outreach activities for K-12 students with an emphasis on increasing participation of women and underrepresented minorities, and for working professionals aimed at helping them adapt to the future workplace wherein humans and autonomous agents will increasingly work as a team. The research work has three main thrusts: (1) modeling temporal dynamics of trust formation and evolution; (2) estimating a person's trust in autonomy from behavioral and physiological information; and (3) developing methods that enable the autonomous agent to adapt its behavior and guide a person toward a more desired level of trust required for successful operation. The project will conduct multiple human-in-the-loop studies on a platform with humans interacting with autonomous drones in several situations, including search and rescue where a sequence of tasks and decisions are required. Based on the data, trust dynamics models, trust inference algorithms and adaptive methods will be built, tested and validated.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.
期刊论文(3)
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会议论文
Human operators’ blind compliance, reliance, and dependence behaviors when working with imperfect automation: A meta-analysis
人类操作员在不完美的自动化环境下工作时的盲目服从、依赖和依赖行为:荟萃分析
DOI: 10.1109/ichms56717.2022.9980609
发表时间: 2022
期刊: 2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS
影响因子: --
作者: [Schuler, Patrik T., Yang, X. Jessie]
通讯作者: Yang, X. Jessie
Evaluating Effects of Enhanced Autonomy Transparency on Trust, Dependence, and Human-Autonomy Team Performance over Time
随着时间的推移,评估增强的自主透明度对信任、依赖和人类自主团队绩效的影响
DOI: 10.1080/10447318.2022.2097602
发表时间: 2022
期刊: International Journal of Human–Computer Interaction
影响因子: --
作者: [Luo, Ruikun, Du, Na, Yang, X. Jessie]
通讯作者: Yang, X. Jessie
DOI: 10.1145/3568294.3580164
发表时间: 2023-01
期刊: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
影响因子: --
作者: [Yaohui Guo;Jessie X. Yang;Cong Shi]
通讯作者: Yaohui Guo;Jessie X. Yang;Cong Shi
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