FW-HTF-P: Understanding and Assessing Technology Innovation to Mitigate Distraction and Improve the Performance of Future Forklift Operators

FW-HTF-P：了解和评估技术创新，以减少分心并提高未来叉车操作员的绩效

• 批准号: 2221942
• 负责人: Suman Niranjan
• 金额: $ 14.99万
• 依托单位: University of North Texas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2221942&HistoricalAwards=false
• 关键词: FW; HTF; Understanding; Assessing; Technology

This Future of Work at the Human Technology Frontier (FW-HTF) Project Development award addresses the use of emerging robotics, artificial intelligence, and wearable sensor technology to benefit workers such as forklift drivers in future warehouses and distribution centers. This award will support gathering of preliminary data and building of an interdisciplinary research team to study how workload and distractions affect worker performance, and in particular how these effects change for older workers. Preliminary studies will determine the appropriate metrics to quantify variables including distraction, comfort, performance, engagement, and levels of technology acceptance. Studies will relate these variables to noninvasive physiological measurements, including eye movement, heart rate, skin resistance, facial expressions, and brain waves. Three workshops will help recruit academic team members and industrial stakeholders. Academic disciplines represented will include experts in logistics, autonomous, soft robotics, computer vision, the science of learning, industrial psychology, data analytics and machine learning, biosensors and neurophysiology, computer network security and privacy, and economics and workforce development. Additional participants will be identified to complement and augment the team’s current industrial collaborators from the Dallas-Fort Worth area material handling industry. The result of this project will be an integrated interdisciplinary team of researchers and stakeholders, a set of well-defined and impactful research questions, and a detailed plan to address those questions. Ultimately the project will benefit the transportation logistics sector and its workers, including operators of vehicles such as forklifts and pallet jacks. More generally, the research project that is articulated under this Project Development award will help create technological interventions to mitigate distraction and improve performance, safety, and quality of life in an aging workforce, across various occupations where small distractions may lead to serious incidents involving physical injury, damage to property, and interruption of operations. Some examples are drone pilots, truck drivers, longshoremen, and ship-to-shore crane operators. This project includes activities to engage and support underrepresented STEM researchers at both graduate and undergraduate levels.This project seeks to validate and advance an explanatory framework of factors correlated to major attention lapses by forklift drivers and other industrial operators (IOs), further characterized by population and gender. The major knowledge gap to be addressed by this project is to identify from among variables such as cognitive load, stress, fatigue, emotional stimuli, and planning, those that correlate most strongly to distraction and dangerous degradation of performance. Pilot data will include physiological and psychological measures. This project will provide deeper understanding of operator perception of, and interaction with, advanced technology in warehouse and distribution center settings to mitigate distraction and improve performance and safety. Specific technology innovations of interest include personalized interaction rules for autonomous mobile robots and the use of predictive algorithms to guide IO behavior. The long-term career sustainability of IO occupations will be related to factors including age, education, socio-economic status, and gender. The results will improve worker performance, comfort, and safety, improve business productivity, and reduce costs due to downtime and injury. Broader impacts of this research will be amplified by the extensive involvement of industry stakeholders.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

人类技术前沿的未来工作(FW-HTF)项目发展奖致力于使用新兴的机器人、人工智能和可穿戴传感器技术，使未来仓库和配送中心的叉车司机等工人受益。该奖项将支持收集初步数据和建立一个跨学科的研究团队，以研究工作量和分心对员工表现的影响，特别是这些影响对老年员工的影响如何变化。初步研究将确定量化变量的适当指标，包括分心、舒适度、性能、参与度和技术接受程度。研究将把这些变量与非侵入性生理测量联系起来，包括眼球运动、心率、皮肤阻力、面部表情和脑波。三个研讨会将帮助招募学术团队成员和行业利益相关者。与会的学术学科将包括物流、自主、软机器人、计算机视觉、学习科学、工业心理学、数据分析和机器学习、生物传感器和神经生理学、计算机网络安全和隐私以及经济学和劳动力发展方面的专家。将确定更多的参与者，以补充和加强团队目前来自达拉斯-沃斯堡地区材料搬运行业的行业合作伙伴。该项目的结果将是一个由研究人员和利益攸关方组成的综合跨学科团队，一系列明确和有影响力的研究问题，以及解决这些问题的详细计划。最终，该项目将使运输物流部门及其工人受益，包括叉车和托盘千斤顶等车辆的运营商。更广泛地说，在本项目发展奖下阐述的研究项目将有助于创建技术干预措施，以减轻劳动力老龄化的分心，并提高绩效、安全和生活质量，涉及各种职业，在这些职业中，微小的分心可能会导致严重的事故，包括人身伤害、财产损失和运营中断。一些例子是无人机飞行员、卡车司机、码头工人和船舶到岸上的起重机操作员。该项目包括吸引和支持研究生和本科生中代表性不足的STEM研究人员的活动。该项目旨在验证和推进与叉车司机和其他工业操作员(IOS)的重大注意力疏忽相关的因素的解释框架，并进一步以人口和性别为特征。这个项目要解决的主要知识差距是从认知负荷、压力、疲劳、情绪刺激和计划等变量中找出与分心和危险的表现降级最相关的变量。试点数据将包括生理和心理指标。该项目将更深入地了解操作员对仓库和配送中心环境中先进技术的认知和互动，以减少分心并提高性能和安全性。令人感兴趣的具体技术创新包括自主移动机器人的个性化交互规则，以及使用预测算法来指导IO行为。IO职业的长期职业可持续性将与年龄、教育、社会经济地位和性别等因素有关。结果将改善员工的工作表现、舒适性和安全性，提高企业生产率，并降低因停机和受伤而产生的成本。这项研究的更广泛的影响将被行业利益相关者的广泛参与放大。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。