Examining situational awareness, trust in automation, and workload in engine resources management: an evaluation of head-worn display technology

Author:

Nizar Adi MasORCID,Miwa Takashi,Uchida Makoto

Abstract

AbstractWork in the engine department is currently demanding more monitoring task. However, the current alarm systems that support operators during troubleshooting are deficient. In many cases, operators reach the engine control room (ECR) only to find a false alarm. This problem is likely to aggravate in the future as operators work in smaller numbers or even alone; therefore, task prioritization should be considered in a given context. Therefore, this study examines the application of head-worn displays in engine resources management to improve situational awareness (SA), trust in automation, and workload. A human-subject experiment was conducted using an engine plant simulator. The participants simultaneously performed maintenance and monitoring tasks in two scenarios: work conditions assisted with and without information on the head-worn display used as a cognition aid. Subjective measurement involved filling in questionnaires after each trial, whereas objective measurement used the simulator-recorded data. The results show that the availability of engine parameters and alarm indicators on a head-worn display is less significant in improving situational awareness. However, it can still help develop trust in automation and lower the workload. In addition, head-worn displays improve participants’ prioritization in a multi-tasking environment. The results indicate that examining these findings in actual work environments can help realize the future application of head-worn displays in ship operations.

Funder

Kobe University

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Safety Research,Transportation,Human Factors and Ergonomics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Smart Guard Towns: Multi-Drone Systems with Deep Learning for Situational Awareness in Urban Management and Security;2023 10th International Conference on ICT for Smart Society (ICISS);2023-09-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3