EAGER: Human-Team-Machine Interaction in Emergency Response

EAGER：应急响应中的人-团队-机器交互

• 批准号: 1650026
• 负责人: Mark Avnet
• 金额: $ 23.99万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1650026&HistoricalAwards=false
• 关键词: EAGER; Human; Team; Machine; Interaction

A critical challenge to emergency response in critical infrastructures is understanding how decisions are made by the incident management team (IMT), which serves as the nerve center guiding the overall response effort. At the core of decision-making in such large and dynamic teams is team cognition, which in emergency response can be viewed as the responders' ability to form a "common operating picture." The goal of this EArly-concept Grant for Exploratory Research (EAGER) project is to examine the relationship of cognition to individual and team performance in IMTs. While it is difficult to study actual IMTs at work, high-fidelity simulation facilities place responders in exercises that replicate real-world emergency events. This research leverages one such facility, the Emergency Operations Training Center (EOTC) operated by the Texas A&M Engineering Extension Service (TEEX), a world leader in emergency responder training, to study IMTs without the need to collect data during actual incidents (which would be both impractical and undesirable given the urgency of real events). Based on observations and recordings, the researchers will conduct a qualitative analysis of team communication and build social networks representing interactions among team members, which collectively form cognition in the team, according to recent findings. The researchers will break the team's work into its constituent elements and examine how each element makes use of key technologies. Because the work involves performance-oriented interventions, it will lead to improved responder training and thus will contribute to reduced loss of life and property during catastrophic events. The EOTC will be able to use research findings to guide redesign of software and training tools. As leaders in emergency management, EOTC instructors and staff are in regular communication with policymakers, enabling them to translate research outcomes into actionable information to improve the U.S. National Preparedness Guidelines, the National Incident Management System (NIMS), and state and local equivalents.This research seeks to characterize the influence of interactions among humans, teams, and technologies on individual and team performance in high-pressure, time-constrained environments such as emergency response. In these situations, the IMT supports first responders from a centralized incident command post (ICP). The IMT solves complex safety-critical problems under high time pressure and ubiquitous information flow, so the team's ability to receive, process, and share information is essential to successful outcomes. Building on the view that team cognition is inseparable into individual cognition, the research focuses on the team as a singular entity, termed the "aggregate team artifact." Unlike traditional human-machine interaction (HMI) studies, this research examines two new complementary concepts: human-team interaction (HTI) and team-machine interaction (TMI). While HTI focuses on individuals' interactions with the aggregate team artifact, TMI applies HMI methods to the team entity's interactions with tools and technologies. The researchers will conduct a focused study to explore and validate HTI and TMI. During exercises involving actual emergency responders in high-fidelity ICP simulations, the work of the Planning subteam will be recorded and transcribed. Beginning with grounded theory analysis of transcripts, the researchers will categorize HTI and TMI content, build team communication networks to devise metrics of HTI, adapt task analysis techniques to assess TMI, and relate metrics of HTI and TMI to individual and team performance. This work will make fundamental contributions to human factors (HTI and TMI to complement HMI), social and organizational psychology (team cognition in real-world high-pressure settings), and systems engineering (characterization of teams as complex systems). By providing a proof-of-concept for HTI and TMI, this exploratory study will serve as an initial step toward the creation of an integrated predictive model for emergency response.

关键基础架构中应急响应的一个关键挑战是了解事件管理团队（IMT）的决策是如何作为指导整体响应工作的神经中心的。在如此大而充满活力的团队中，决策的核心是团队认知，在紧急响应中，这可以看作是响应者形成“常见的操作图片”的能力。这项对探索性研究（急切）项目的早期概念赠款的目标是研究认知与IMT中个人和团队绩效的关系。虽然很难研究工作中的实际IMT，但高保真模拟设施将响应者置于复制现实世界中紧急事件的练习中。这项研究利用了一个这样的设施，即紧急操作培训中心（EOTC）由得克萨斯州A＆M工程扩展服务（TEEX）（TEEX）（TEEX）是紧急响应者培训的全球领导者，研究IMT，而无需在实际事件中收集数据（鉴于真实事件的迫切性，这既是不切实际的，也是不可能的）。根据最近的发现，根据观察结果和记录，研究人员将对团队沟通的定性分析，并建立代表团队成员互动的社交网络，这些社交网络共同在团队中统一形成了认知。研究人员将将团队的工作分解为其组成部分，并研究每个元素如何利用关键技术。由于该工作涉及以性能为导向的干预措施，因此它将导致响应者的训练得到改善，从而有助于减少灾难性事件期间的生命和财产损失。 EOTC将能够使用研究结果来指导软件和培训工具的重新设计。作为紧急管理领域的领导者，EOTC讲师和员工正在定期与决策者进行沟通，使他们能够将研究结果转化为可行的信息，以改善美国国家准备指南，国家事件管理系统（NIMS）以及等效的国家和地方等效。这项研究旨在表征人类，团队和技术对较高效果的互动的影响，并促进了个人和高级绩效，并促进了高级绩效，并促进了高度绩效。在这些情况下，IMT支持来自集中事件命令帖子（ICP）的第一响应者。 IMT在高时间压力和无处不在的信息流下解决了复杂的安全问题，因此团队接收，处理和共享信息的能力对于成功结果至关重要。基于认为团队认知在个人认知中密不可分的，该研究的重点是团队作为一个单一实体，称为“总团队人工制品”。与传统的人机相互作用（HMI）研究不同，该研究研究了两个新的互补概念：人团队相互作用（HTI）和团队机器相互作用（TMI）。尽管HTI专注于个人与总团队工件的互动，但TMI将HMI方法应用于团队实体与工具和技术的互动。研究人员将进行一项重点研究，以探索和验证HTI和TMI。在涉及实际应急人员ICP模拟中的实际紧急响应者的练习中，将记录和转录计划子程序的工作。从成绩单的基础理论分析开始，研究人员将对HTI和TMI内容进行分类，建立团队通信网络以设计HTI的指标，适应任务分析技术以评估TMI，并将HTI和TMI的指标与个人和团队绩效联系起来。这项工作将对人为因素（HTI和TMI补充HMI），社会和组织心理学（现实世界高压环境中的团队认知）和系统工程（将团队作为复杂系统表征）为人为因素做出基本贡献。通过为HTI和TMI提供概念概念，这项探索性研究将是朝着建立紧急响应的综合预测模型的第一步。