COGNITIVE INFORMATION PROCESSING TECHNOLOGY:

认知信息处理技术：

• 批准号: 7955711
• 负责人: RICHARD A BARKER
• 金额: $ 0.68万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7955711
• 关键词: Air; Aircraft; Architecture; Automation; Beds; Cognition; Cognitive; Complex; Computer Retrieval of Information on Scientific Projects Database; Decision Aid; Effectiveness; Event; Feedback; Funding; Future; Goals; Grant; Individual; Institution; Manuals; Metric; Mission; Modeling; Performance; Phase; Physiological; Research; Research Personnel; Resources; Source; Stress Tests; System; Technology; Testing; United States National Institutes of Health; Workload; cognitive system; combat; computational anatomy; information processing; programs; prototype; quantum; simulation; system architecture

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Cognitive Information Processing Technology: Augmented Cognition on the Future Battlefield The goal of the Augmented Cognition on the Future Battlefield proposal is to enable a quantum leap forward in operator-workstation effectiveness by creating a cognitive closed-feedback loop between the operator and an adaptive workstation. The system architecture being developed will be applicable to any battlefield system. Boeing will use the Unmanned Combat Air Vehicle (UCAV) as a demonstrator test bed for an augmented cognition prototype workstation. The Augmented Cognition UCAV workstation will enable UCAV operators to control more aircraft by augmenting the cognition of individual operators. The proposed augmented cognition architecture will leverage the UCAV workstation and the UCAV Decision Aiding System (UDAS). The UCAV/UDAS architecture consists of 4 main components, the UCAV workstation, the UCAV simulation (both vehicle and scenario simulations), UDAS, and the UDAS cognitive workload assessor. ¿¿The UCAV workstation interface is highly modular, and supports easy and efficient rapid prototyping. It takes input from UDAS and reconfigures the workstation display. The UCAV simulation is a full-featured simulation, capable of inserting many high workload mission events such as pop-up targets, and contingency events. ¿¿ The UDAS cognitive workload assessor currently is under manual control by the operator. The augmented cognition cognitive workload assessor will automate this function. The Augmented Cognition program is now in Phase 3. Phase 1 investigated physiological and performance metrics of cognitive workload and those results were incorporated into later Phases. The principle deliverable for Phase 2 was a demonstration of an adaptive, closed-loop operator-workstation system in which the workstation responds to increasing levels of operator cognitive workload by adaptively increasing the automation level of selected tasks and reconfiguring operator displays, thereby lowering cognitive workload. During Phase 3 the workstation will be stress-tested with increasingly complex and realistic scenarios to push the envelope of the operator-workstation team.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 认知信息处理技术：未来战场的增强认知 未来战场增强认知提案的目标是通过在操作员和自适应工作站之间创建认知闭反馈环，实现操作员工作站效率的巨大飞跃。 正在开发的系统架构将适用于任何战场系统。波音公司将使用无人机（UCAV）作为增强认知原型工作站的演示测试台。增强认知UCAV工作站将使UCAV操作员能够通过增强单个操作员的认知来控制更多的飞机。 拟议的增强认知架构将利用 UCAV 工作站和 UCAV 决策辅助系统（UDAS）。 UCAV/UDAS 架构由 4 个主要组件组成：UCAV 工作站、UCAV 仿真（车辆和场景仿真）、UDAS 和 UDAS 认知工作负载评估器。 UCAV工作站界面高度模块化，支持简单高效的快速原型制作。它从 UDAS 获取输入并重新配置工作站显示。 UCAV模拟是一种全功能模拟，能够插入许多高工作负载任务事件，例如弹出目标和突发事件。 ?? UDAS 认知工作负载评估器目前由操作员手动控制。增强认知认知工作负载评估器将自动执行此功能。 增强认知计划目前处于第三阶段。第一阶段研究了认知工作量的生理和表现指标，这些结果已纳入后续阶段。第二阶段的主要交付成果是演示自适应闭环操作员工作站系统，其中工作站通过自适应地提高所选任务的自动化水平并重新配置操作员显示器来响应操作员认知工作负载水平的增加，从而降低认知工作负载。在第三阶段，工作站将接受越来越复杂和现实的场景的压力测试，以挑战操作员工作站团队的极限。