Towards augmenting cyber-physical-human collaborative cognition for human-automation interaction in complex manufacturing and operational environments
Towards augmenting cyber-physical-human collaborative cognition for human-automation interaction in complex manufacturing and operational environments
复制标题
DOI：
10.1080/00207543.2020.1722324
复制
发表时间：
2020-03-12
影响因子：
9.2
通讯作者：
Duffy, Vincent
中科院分区：
文献类型：
--
作者：
Jiao, Jianxin (Roger);Zhou, Feng;Duffy, Vincent
增强人-技术协作认知的重要性被认为是在复杂的制造和操作环境中通过人-自动化交互来增强人类认知的基本途径之一。对协作认知的关注需要一种人-自动化相互适应的策略，以增强团队认知和集体智力。本文从分析性和基于模型的决策角度对增强协作认知进行了综述。从认知状态感知与评估、人-自动化交互适应与控制、群决策等方面探讨了建立数学与计算模型的基础与应用问题，旨在促进人类认知增强的基础研究。对网络-物理-人类分析的研究路线图进行了深思熟虑，以揭示为增强情感认知和感知学习、信任动力学建模、人类认知表现预测以及人机交互优化而开发新方法的各种机会。
The importance of augmenting human-technology collaborative cognition has been envisioned as one of the fundamental ways to bolster human cognition through human-automation interaction in complex manufacturing and operational environments. The focus on collaborative cognition entails a human-automation mutual adaption strategy for augmenting team cognition and collective intelligence. This paper provides an overview of augmenting collaborative cognition from an analytic and model-based decision-making perspective. Aiming to advance basic research for understanding human cognition augmentation, the fundamental and applied aspects of creating mathematical and computational models are discussed in regard to cognitive state sensing and assessment, human-automation interaction adaption and control, as well as group decision making in human-automation systems. A research roadmap towards cyber-physical-human analysis is deliberated to reveal a variety of opportunities of developing novel methods for enhancing affective cognition and perception learning, trust dynamics modelling, human cognitive performance prediction, as well as human-automation interaction optimisation.