Transportation Human Factors
Meeting the physical requirements of transportation operators is a prerequisite for optimal job performance. When operator ergonomics are compromised, so is the safety and efficiency of transportation operations. QNA uses a suite of ergonomic tools and analyses to evaluate transportation ergonomics. Our work encompasses the assessment of whole body vibration, 3-D kinematic analysis of an operator in the workspace and anthropometric data collection using non-contact 3-D body scanning.
User-Centered Workspace Design and Evaluation
QNA uses its full arsenal of human factors and ergonomics capabilities to inform the design of workspaces for transportation operators. We employ sophisticated eye tracking equipment to determine optimal layout of information displays; kinematic and anthropometric analysis for the physical layout of the workspace; and advanced cognitive assessments to ensure the design of the workspace does not exceed the information processing limitations of the operator.
Applied Cognitive Science
Transportation operators (motorists, pilots, locomotive engineers) are limited in how much information they can process, particularly under intense workload conditions or when fatigued. QNA is developing an attention trainer using the operator’s own rainwaves (neurofeedback) that will condition them to sustain their attention under varying workload levels. Our work in applied cognitive science also includes the development and evaluation of fatigue models to optimize transportation work schedules. Our capabilities include state-of-the-art physiological and psychological assessments of workload, stress and fatigue.
Organizational Development and Training
QNA has a long history of examining workforce development challenges for the railroad industry. Our work has been seminal in identifying some of the hardest challenges for recruitment and retention including best practices and strategies for overcoming organizational obstacles. QNA has a solid repertoire of developing training programs including those for preparing emergency responders in the event of a train crash. QNA conducted in-depth experiments that identified the most efficient manner to extricate victims from a locomotive cab.