LEAP-HI: Safety and Learning from Errors and Near Misses in the Human-Automation Interaction of Socio-Technical Infrastructure Systems

LEAP-HI：社会技术基础设施系统人机交互中的安全性以及从错误和未遂事件中学习

• 批准号: 2051685
• 负责人: Konstantinos Triantis
• 金额: $ 200万
• 依托单位: Virginia Polytechnic Institute and State University
• 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
• 起止时间: 2021-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2051685&HistoricalAwards=false
• 关键词: LEAP; HI; Safety; Learning; Errors

Modern socio-technical infrastructure systems operate in dynamic environments where there is a high level of interaction between human operators and increasingly autonomous technologies that carry out safety-critical tasks. This Leading Engineering for America's Prosperity, Health, and Infrastructure (LEAP-HI) project will research the balance between safety, workload, and economic considerations in these semi-automated socio-technical infrastructure systems to provide improved design and policy tools to both infrastructure providers and regulators by integrating the disciplines of systems engineering, human factors engineering, decision and organizational theories, and economic production theory. This scientific research contribution supports NSF's mission to promote the progress of science and to advance our national welfare. The expected benefits include improvements in the organization of work, health outcomes associated with the work, and the economic viability of socio-technical infrastructure systems. The project will also support outreach activities to stimulate interest in the socio-technical domain area for students going into STEM-related fields. This project uses a systems-level theoretical approach that provides a computable safe area of operation for modern socio-technical infrastructure systems. It develops a new metric of mental workload that includes distributed situational awareness as determined by multiple physiological measurements and subjective human perceptions. It explores new regions in decision theory by studying how cognitive biases influence trust in automation and decisions to delegate tasks to automated technologies. It also examines the identification and attribution of causes of errors, near misses, and incidents as part of organizational learning in these modern systems. Additionally, the research builds on economic production theory to integrate workload, safety, and economic perspectives in determining an infrastructure’s safety envelope. Finally, the research assesses the dynamic trade-offs among workload, marginal safety, and economics within the safety envelope to improve infrastructure decision-making.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.

现代社会技术基础设施系统在动态环境中运行，在这种环境中，操作员与执行安全关键任务的日益自主的技术之间高度互动。这个领先的美国繁荣、健康和基础设施工程(LEAP-HI)项目将研究这些半自动社会技术基础设施系统中安全、工作负荷和经济考虑之间的平衡，通过整合系统工程、人为因素工程、决策和组织理论以及经济生产理论，为基础设施提供商和监管机构提供改进的设计和政策工具。这一科研贡献支持了美国国家科学基金会促进科学进步和增进国家福利的使命。预期效益包括改善工作安排、与工作相关的健康成果以及社会技术基础设施系统的经济可行性。该项目还将支持外联活动，以激发学生对进入STEM相关领域的学生在社会技术领域的兴趣。该项目采用系统一级的理论方法，为现代社会技术基础设施系统提供了一个可计算的安全作业区域。它开发了一种新的精神工作量度量标准，其中包括由多个生理测量和主观人类感知确定的分布式情景感知。它通过研究认知偏差如何影响对自动化的信任，以及将任务委托给自动化技术的决策，探索了决策理论的新领域。它还检查了在这些现代系统中作为组织学习的一部分的错误、险些和事件的原因的识别和归因。此外，这项研究建立在经济生产理论的基础上，以综合工作量、安全和经济角度来确定基础设施的安全封套。最后，这项研究评估了工作负荷、边际安全和经济之间的动态权衡，以改善基础设施决策。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。