Collaborative Research: Personalized Systems for Wayfinding for First Responders

协作研究：为急救人员提供寻路的个性化系统

• 批准号: 1761950
• 负责人: Qi Wang
• 金额: $ 19.71万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1761950&HistoricalAwards=false
• 关键词: Collaborative; Research; Personalized; Systems; Wayfinding

First responders face serious risks when responding to emergencies, and disorientation induced by complex building features is a major cause of injuries. In order to successfully navigate complex, dangerous buildings during a crisis, first responders need to build accurate spatial memories of unfamiliar spaces in a timely manner. This requires retention and processing of a large amount of information such as maps and verbal instructions. An apparent gap between the enormous information processing needs during a mission and the limited processing capacity of people creates a potentially fatal situation in emergency wayfinding. This project will contribute to the NSF's Big Idea "Harnessing Data for 21st Century Science and Engineering" by conducting fundamental research in information processing and engineering in the field of disaster management. This project will test the theoretical foundation of personalized wayfinding information systems that can effectively minimize the cognitive load of first responders on the individual level. This scientific research contribution thus supports NSF's mission to promote the progress of science and to advance our national welfare. In this case, the benefits will be insights to improve emergency response wayfinding, which will save lives and potentially reduce economic losses during disasters. This project has three interdependent scientific objectives. First, the research quantifies the structured relationship between spatial information and different forms of cognitive load in wayfinding tasks. Spatial information for wayfinding will be categorized and measured using semantic metrics; then a quantitative model of the relationship between spatial information and cognitive load will be examined. Second, the research explores cognitive resilience that helps identify and prevent an abrupt drop in wayfinding performance. Virtual Reality (VR) based multi-mission experiments are performed to examine the hypothetical nonlinearity of the relationship between cognitive load and wayfinding performance. Third, the research evaluates the effectiveness of personalized wayfinding information system in simulated mission tasks. A holistic VR experiment is performed to compare the new personalized system against the current universal spatial information systems. The outcome of the scientific investigation includes an adaptive wayfinding information system that dynamically tailors the way spatial information is presented based on the real-time cognitive load of individual first responders, measured by a set of neurobiological and physiological metrics. The project will immediately impact first responders primarily firefighters for their missions. A number of collaborative outreach activities are planned between two project sites: Texas A&M University and Northeastern University. These include advancing VR technologies for STEM education, integrating the research outcomes to curriculum development at both institutions, and developing a free online course and open-source project for general public access.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.

急救人员在应对紧急情况时面临着严重的风险，而复杂的建筑特征引起的迷失方向是造成伤害的主要原因。为了在危机期间成功穿越复杂、危险的建筑，急救人员需要及时建立对陌生空间的准确空间记忆。这需要保留和处理大量信息，例如地图和口头指示。任务期间巨大的信息处理需求与人们有限的处理能力之间的明显差距，在紧急寻路中造成了潜在的致命情况。该项目将通过在灾害管理领域的信息处理和工程方面进行基础研究，为 NSF 的“利用数据促进 21 世纪科学与工程”的伟大理念做出贡献。该项目将测试个性化寻路信息系统的理论基础，该系统可以有效地减少个人层面上急救人员的认知负担。因此，这项科学研究贡献支持了 NSF 促进科学进步和增进国家福祉的使命。在这种情况下，好处将是改善紧急响应寻路的洞察力，这将挽救生命并可能减少灾难期间的经济损失。该项目具有三个相互依赖的科学目标。首先，该研究量化了寻路任务中空间信息与不同形式的认知负荷之间的结构化关系。用于寻路的空间信息将使用语义度量进行分类和测量；然后将检查空间信息和认知负荷之间关系的定量模型。其次，该研究探讨了认知弹性，有助于识别和防止寻路性能突然下降。基于虚拟现实 (VR) 的多任务实验旨在检验认知负荷与寻路性能之间关系的假设非线性。第三，研究评估了个性化寻路信息系统在模拟任务任务中的有效性。进行了整体 VR 实验，将新的个性化系统与当前的通用空间信息系统进行比较。科学研究的成果包括一个自适应寻路信息系统，该系统根据个体急救人员的实时认知负荷（通过一组神经生物学和生理指标进行测量）动态调整空间信息的呈现方式。该项目将立即影响执行任务的急救人员（主要是消防员）。 德克萨斯农工大学和东北大学这两个项目地点之间计划开展许多合作外展活动。其中包括推进 STEM 教育的 VR 技术、将研究成果整合到两个机构的课程开发中，以及开发供公众访问的免费在线课程和开源项目。该奖项反映了 NSF 的法定使命，并被认为值得通过以下方式获得支持：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。

项目成果

Personalize Wayfinding Information for Fire Responders based on Virtual Reality Training Data

基于虚拟现实训练数据为消防响应人员提供个性化寻路信息

• DOI: handle/10125/59638
• 发表时间: 2019-01
• 期刊: Proceedings of the ... Annual Hawaii International Conference on System Sciences
• 作者: Du, Jing;Wang, Qi;Lin, Yingzi;Ahn, Changbum
• 通讯作者: Ahn, Changbum

Description–experience gap under imperfect information: Information continuum and aggressive cost estimating in capital projects

描述——不完美信息下的经验差距：资本项目中的信息连续体和积极的成本估算

• DOI: 10.1108/ecam-02-2018-0075
• 发表时间: 2019-04
• 期刊: Construction and Architectural Management
• 作者: Du, Jing;Wang, Qi;Shi, Qian
• 通讯作者: Shi, Qian

A CNN-based personalized system for attention detection in wayfinding tasks

• DOI: 10.1016/j.aei.2020.101180
• 发表时间: 2020-10-01
• 期刊: Adv. Eng. Informatics
• 作者: Yanchao Wang;Yangming Shi;E. Du;Yingzi Lin;Qi Wang
• 通讯作者: Qi Wang