The current field inspection involves railroaders climbing, measuring, and photographing infrastructure annually to inform repair needs and prioritize decisions regarding safety. Inspectors with extensive experience are most reliable at conducting inspections that yield accurate assessments. Research on expert performance suggests that the development of master-level skills and expertise takes at least a decade of focused practice in realistic work settings. Engineers generally have an aversion to considering human factors when advancing fundamental knowledge related to decision-making frameworks. This multi-disciplinary research project integrates human cognition, professional engineers, railroad inspection crews/teams, and AR to transform the profession of field inspection by transforming the inspector’s current abilities, procedures, and limitations using new human-infrastructure interfaces.
The PIs will utilize augmented reality (AR) as a scaffolding tool and develop a new framework that will promote and accelerate early learner's expertise in decision-making capabilities related to railroad infrastructure inspection. The proposed new framework is transformative for the profession in two ways: 1) it uses a new human-technology paradigm that augments human performance through an interdependent partnership, and 2) it enables human cognition to be accelerated and augmented in real-time.
Based on the needs of the profession of infrastructure inspectors and the need for integrative research, the proposed research will: explore the human cognition of systems and the effect of augmentation on cognition; explore relationships between human cognition of structural properties and learning; quantify those relationships through experiments and simulations; and develop a new AR framework that allows a new and less-experienced infrastructure inspector to conduct better inspections with greater accuracy, less time, and enhanced safety using AR in the field.
This project will enable a new training for inspectors. This new AR framework will transform the training of inspectors, who will not need to wait decades to become experts and conduct accurate assessments of structures. The new interface will enable the use of AR in the field with enhanced safety, enabling inspectors to collect information in the field in less time. A new railroader inspector profession will arise as a result of these new human-technology interfaces.