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

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.