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: 1761459
• 负责人: Jing Du
• 金额: $ 21.95万
• 依托单位: Texas A&M 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 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1761459&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.

急救员在应对突发事件时面临着严重的风险，而复杂的建筑特征导致的定向障碍是造成人员受伤的主要原因。为了在危机中成功导航复杂、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，如地图和口头指示。执行任务期间巨大的信息处理需求与人员有限的处理能力之间的明显差距在紧急寻路方面造成了潜在的致命情况。该项目将通过在灾害管理领域进行信息处理和工程方面的基础研究，为美国国家科学基金会的“利用数据为21世纪的科学与工程”做出贡献。本项目将测试个性化寻路信息系统的理论基础，该系统可以有效地将急救员在个人层面上的认知负荷降至最低。因此，这项科学研究贡献支持了NSF促进科学进步和增进我们国家福利的使命。在这种情况下，好处将是改进紧急响应路线寻找的洞察力，这将拯救生命，并可能减少灾害期间的经济损失。这个项目有三个相互关联的科学目标。首先，本研究量化了空间信息与寻路任务中不同形式的认知负荷之间的结构关系。用于寻路的空间信息将使用语义度量进行分类和测量；然后将检验空间信息与认知负荷之间的关系的量化模型。其次，这项研究探索了认知韧性，以帮助识别和防止寻路性能的突然下降。通过基于虚拟现实(VR)的多任务实验来检验认知负荷与寻路性能之间关系的假设非线性。第三，对个性化寻路信息系统在模拟任务中的有效性进行了评估。通过一个完整的虚拟现实实验，将新的个性化系统与现有的通用空间信息系统进行了比较。科学调查的结果包括一个自适应的寻路信息系统，该系统根据个体急救员的实时认知负荷，通过一套神经生物学和生理指标来衡量，动态调整空间信息的呈现方式。该项目将立即影响急救人员，主要是执行任务的消防员。计划在德克萨斯农工大学和东北大学这两个项目站点之间开展一系列合作外展活动。其中包括为STEM教育推进虚拟现实技术，将研究成果整合到两所机构的课程开发中，以及开发面向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。

项目成果

Impacts of human communication network topology on group optimism bias in Capital Project Planning: a human-subject experiment

人类通信网络拓扑对基建项目规划中群体乐观偏差的影响：一项以人为对象的实验

• DOI: 10.1080/01446193.2018.1508848
• 发表时间: 2018
• 期刊: Construction Management and Economics
• 影响因子: 3.4
• 作者: Du, Jing;Zhao, Dong;Zhang, Ou
• 通讯作者: Zhang, Ou

Impact assessment of reinforced learning methods on construction workers' fall risk behavior using virtual reality

• DOI: 10.1016/j.autcon.2019.04.015
• 发表时间: 2019-08-01
• 期刊: AUTOMATION IN CONSTRUCTION
• 影响因子: 10.3
• 作者: Shi, Yangming;Du, Jing;Ragan, Eric
• 通讯作者: Ragan, Eric

Simulation of spatial memory for human navigation based on visual attention in floorplan review

平面图审查中基于视觉注意的人类导航空间记忆模拟

• 发表时间: 2019
• 期刊: Winter Simulation Conference
• 作者: Shi, Yangming;Du, Jing
• 通讯作者: Du, Jing

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

• 发表时间: 2019
• 期刊: Proceedings of the 52nd Hawaii International Conference on System Sciences
• 作者: Jing Du, Qi Wang