دورية أكاديمية

A Cyber-Physical-Human System for One-to-Many UAS Operations: Cognitive Load Analysis

التفاصيل البيبلوغرافية
العنوان: A Cyber-Physical-Human System for One-to-Many UAS Operations: Cognitive Load Analysis
المؤلفون: Lars J. Planke, Yixiang Lim, Alessandro Gardi, Roberto Sabatini, Trevor Kistan, Neta Ezer
المصدر: Sensors, Vol 20, Iss 19, p 5467 (2020)
بيانات النشر: MDPI AG, 2020.
سنة النشر: 2020
المجموعة: LCC:Chemical technology
مصطلحات موضوعية: human–machine systems, adaptive systems, one-to-many, unmanned aircraft system, UAS, neuroergonomics, Chemical technology, TP1-1185
الوصف: The continuing development of avionics for Unmanned Aircraft Systems (UASs) is introducing higher levels of intelligence and autonomy both in the flight vehicle and in the ground mission control, allowing new promising operational concepts to emerge. One-to-Many (OTM) UAS operations is one such concept and its implementation will require significant advances in several areas, particularly in the field of Human–Machine Interfaces and Interactions (HMI2). Measuring cognitive load during OTM operations, in particular Mental Workload (MWL), is desirable as it can relieve some of the negative effects of increased automation by providing the ability to dynamically optimize avionics HMI2 to achieve an optimal sharing of tasks between the autonomous flight vehicles and the human operator. The novel Cognitive Human Machine System (CHMS) proposed in this paper is a Cyber-Physical Human (CPH) system that exploits the recent technological developments of affordable physiological sensors. This system focuses on physiological sensing and Artificial Intelligence (AI) techniques that can support a dynamic adaptation of the HMI2 in response to the operators’ cognitive state (including MWL), external/environmental conditions and mission success criteria. However, significant research gaps still exist, one of which relates to a universally valid method for determining MWL that can be applied to UAS operational scenarios. As such, in this paper we present results from a study on measuring MWL on five participants in an OTM UAS wildfire detection scenario, using Electroencephalogram (EEG) and eye tracking measurements. These physiological data are compared with a subjective measure and a task index collected from mission-specific data, which serves as an objective task performance measure. The results show statistically significant differences for all measures including the subjective, performance and physiological measures performed on the various mission phases. Additionally, a good correlation is found between the two physiological measurements and the task index. Fusing the physiological data and correlating with the task index gave the highest correlation coefficient (CC = 0.726 ± 0.14) across all participants. This demonstrates how fusing different physiological measurements can provide a more accurate representation of the operators’ MWL, whilst also allowing for increased integrity and reliability of the system.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1424-8220
Relation: https://www.mdpi.com/1424-8220/20/19/5467; https://doaj.org/toc/1424-8220
DOI: 10.3390/s20195467
URL الوصول: https://doaj.org/article/fe9ec769495e415ea9dd3230af4b5a0a
رقم الأكسشن: edsdoj.fe9ec769495e415ea9dd3230af4b5a0a
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:14248220
DOI:10.3390/s20195467