EAGER: Modeling Intent Communication Pathways for Human-Autonomous System Collaboration

自动化系统在增强安全性方面表现出很大的希望，但是之前在人与自动化交互方面的研究也表明，不适当地添加自动化实际上可能会导致非常不受欢迎的动态交互。此外，在一个更大的系统中自动化一项任务可能会将操作员的工作量从一个物理或认知资源转移到另一个，从而仅仅改变任务，而不是改进它。因此，在设计新技术时，仔细考虑操作员将如何与系统自动化进行交互，特别是与基于随机而不是确定性推理的自主系统进行交互，这一点至关重要。这个早期概念探索性研究资助（EAGER）项目将确定如何设计安全的自主系统，这些系统能够意识到系统内部和周围人类的意图，并与这些人类相互关系。以前的以人为本的设计工作集中在工程系统和人类操作员之间的交互。 该项目增加了设计用于与附近人类通信的界面的考虑，重点是设计考虑外部个人和内部操作员意图的自主系统。该项目的目标如下：（1）对人-系统交互进行全面分析，以确定工程系统与系统内外的个人之间交互的意图表示方法;（2）开发用于计算机解释人类意图的模型，包括系统操作员和外部行为者的意图;以及（3）识别将系统意图传达给操作员和外部参与者的方法。最终的模型将通过使模型适应无人驾驶汽车领域来验证-在这个领域，技术已经超越了对人类如何融入系统的理解。该项目还将使用拾取和放置巴克斯特机器人将建模方法扩展到制造领域。在这两种情况下，研究人员将研究如何对环境元素、机器人的计算系统和人类的独特特征进行建模，以表示需要在系统或系统周围的世界中实例化的意图通信路径。这项工作还将研究包括内源和外源行为者在内的利益攸关方的需求（例如，机器人叉车附近的工厂中的行人和工人）。跨多个领域应用模型将决定两个实体的模型可以通用化的程度。

Autonomous systems show great promise for enhancing safety, however previous research in human-automation interaction has also demonstrated that adding automation improperly may actually result in highly undesirable dynamic interactions. Furthermore, automating a task within a larger system may transfer the operator's workload from one physical or cognitive resource to another, thereby merely changing the task, rather than improving it. Thus it is crucial when designing new technologies to consider carefully how the operator will interact with system automation, particularly with autonomous systems that are based on stochastic, as opposed to deterministic, reasoning. This EArly-concept Grant for Exploratory Research (EAGER) project will determine how to design safe autonomous systems that have awareness of the intent of humans in and around the system, with reciprocal relationships for those same humans. Previous work in human-centered design focused on interactions between an engineered system and a human operator. This project adds consideration of interfaces designed to communicate with nearby humans, with an emphasis on designing autonomous systems that consider the intent of both the external individual and internal operator. This objectives of this project are as follows: (1) perform a comprehensive analysis of human-system interactions to identify methods for representing intent in interactions between an engineered system and individuals within and outside the system; (2) develop models for computer interpretation of human intent, including the intent of the system operator and exogenous actors; and (3) identify methods to communicate system intent to the operator and to exogenous actors. The resulting models will be verified by adapting the model to the driverless car domain -- an area where technology has outpaced understanding of how humans integrate into the system. The project will also extend the modeling approach to the manufacturing domain using a pick-and-place Baxter robot. In both settings, the researchers will study how elements of the environment, the computation systems of the robots, and unique traits of humans can be modeled to represent intent communication pathways that need to be instantiated in the system or in the world around the system. The effort will also study the needs of stakeholders including endogenous and exogenous actors (e.g., pedestrians and workers in a plant near a robotic forklift). Applying the models across multiple domains will determine the extent to which the models of both entities can be generalized.