EAGER: Human-Team-Machine Interaction in Emergency Response

关键基础设施中应急响应的一个关键挑战是了解事件管理团队(IMT)是如何做出决策的，该团队是指导整体响应工作的神经中枢。在如此庞大和动态的团队中，决策的核心是团队认知，在应急响应中，团队认知可以被视为响应者形成“共同操作图景”的能力。这个早期概念探索性研究奖助金项目的目标是考察认知与IMTS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安排在模拟真实世界紧急事件的演习中。这项研究利用了一个这样的设施，即由世界领先的应急响应员培训机构德克萨斯农工机械工程推广服务(TEEX)运营的应急操作培训中心(EOTC)，来研究IMTS，而不需要在实际事件期间收集数据(考虑到真实事件的紧迫性，这既不现实，也不可取)。根据最近的发现，研究人员将根据观察和记录，对团队沟通进行定性分析，并建立代表团队成员之间互动的社交网络，这些社交网络共同形成团队中的认知。研究人员将把团队的工作分解为其组成要素，并检查每个要素如何利用关键技术。由于这项工作涉及以业绩为导向的干预措施，它将导致改进应急人员培训，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。作为应急管理的领导者，EOTC指导员和工作人员与政策制定者保持定期沟通，使他们能够将研究成果转化为可操作的信息，以改进美国国家准备指南、国家事件管理系统(NIMS)以及州和地方的同等标准。本研究旨在表征在紧急响应等高压、时间受限的环境中，人员、团队和技术之间的互动对个人和团队绩效的影响。在这些情况下，IMT支持来自集中式事故指挥所(ICP)的急救人员。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关键问题，因此团队接收、处理和共享信息的能力对于成功的结果至关重要。基于团队认知与个体认知密不可分的观点，本研究将团队作为一个单一的实体，称为“聚合团队人工产物”。与传统的人机交互(HMI)研究不同，本研究考察了两个新的相辅相成的概念：人机交互(HTI)和团队-机器交互(TMI)。HTI专注于个体与聚合团队构件的交互，而TMI将HMI方法应用于团队实体与工具和技术的交互。研究人员将进行一项重点研究，以探索和验证HTI和TMI。在高保真ICP模拟中涉及实际应急人员的演习中，规划小组的工作将被记录和转录。从对成绩单的扎根理论分析开始，研究人员将对HTI和TMI内容进行分类，建立团队沟通网络来设计HTI的度量标准，采用任务分析技术来评估TMI，并将HTI和TMI的度量与个人和团队绩效联系起来。这项工作将对人的因素(HTI和TMI，以补充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(将团队表征为复杂系统)做出基础性贡献。通过为HTI和TMI提供概念验证，这项探索性研究将作为创建应急响应综合预测模型的第一步。

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.