Using virtual reality to optimize human factors of informational systems for industrial machinery

利用虚拟现实优化工业机械信息系统的人为因素

• 批准号: RGPIN-2017-06076
• 负责人: Godwin, Alison
• 金额: $ 1.53万
• 依托单位: Laurentian University of Sudbury
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=712036
• 关键词: Using; virtual; reality; optimize; human

Enhancing visibility for the operators of heavy equipment remains a critical goal in several industries. Proximity detection systems that range in complexity from closed-circuit television screens to audio-visual hazard indicators and RFID tagged systems have been used on a variety of heavy equipment. Many light passenger vehicles now come equipped with back-up video monitors to aid the operator during revering procedures. The main goal of these systems is to improve the situational awareness of the operator and improve obstacle detection around the machine for the operator. The mining and construction industries continue to report high levels of fatalities on heavy equipment, and these incidents have frequently been linked to visibility issues. Proximity detection systems have the potential to improve situational awareness for operators of heavy equipment if implemented correctly. To date, heavy industry has not yet adopted a standard for proximity detection systems although several manufacturers are marketing systems with an aim to reduce fatal interactions. The proper human factors design for these systems is critical for improving situational awareness, without adding the additional hazard of distracted driving. There is currently insufficient research to confidently recommend a system tailored to heavy industrial equipment. The proposed project will determine the optimal characteristics of a proximity detection system for industries like mining, which has the difficulty of being a low light and high-glare environment, or the busy, accessible worksites of urban construction. In addition, the informational display competes for the operator's attention, and must be optimally integrated into a tight cabin space using principles of ergonomics. At the culmination of this research program, the work will have identified the components of a proximity detection system that will provide obstacle detection capability in an ergonomic design that does not increase physical or cognitive workload for the operators of heavy equipment.

提高重型设备操作人员的可见度仍然是几个行业的关键目标。从闭路电视屏幕到视听危险指示器和RFID标签系统的复杂程度不等的接近检测系统已用于各种重型设备。现在许多轻型乘用车都配备了备用视频监视器，以帮助操作员在返回过程中。这些系统的主要目标是提高操作员的态势感知能力，并提高操作员对机器周围障碍物的检测能力。采矿和建筑行业继续报告重型设备的高死亡率，这些事件经常与能见度问题有关。如果实施得当，近距离探测系统有可能提高重型设备操作员的态势感知能力。迄今为止，重工业尚未采用接近检测系统的标准，尽管一些制造商正在销售旨在减少致命相互作用的系统。为这些系统设计适当的人为因素对于提高态势感知能力至关重要，同时又不会增加分心驾驶的额外危险。目前还没有足够的研究可以自信地推荐一种适合重工业设备的系统。拟议的项目将确定接近检测系统的最佳特性，适用于采矿等行业，这些行业难以在低光和高眩光环境中工作，或者在繁忙的城市建设工地。此外，信息显示会吸引操作员的注意力，必须根据人体工程学原理将其最佳地集成到狭小的机舱空间中。在该研究项目的最后阶段，该工作将确定接近检测系统的组成部分，该系统将提供符合人体工程学设计的障碍物检测能力，不会增加重型设备操作员的身体或认知工作量。