Human-in-the-Loop: Probabilistic Predictive Modelling, its Role, Attributes, Challenges and Applications
Theoretical Issues in Ergonomics Science
Reliability (Engineering), Risk assessment, Probabilities
Traditional human-factor-oriented approaches are based on experimentations followed by statistical analyses. Our novel probabilistic predictive modelling (PPM) concept is based on physically meaningful and flexible predictive modelling followed by experimentations geared to the appropriate models. The concept enables one to quantify, on the probabilistic basis, the outcome of a particular effort, situation or a mission. This cost-effective and insightful approach is applicable to numerous human-in-the-loop (HITL) situations, when a human acting as a part of the complex man–instrumentation–equipment–vehicle–environment system encounters an uncertain environment or a hazardous off-normal situation, and when there is an incentive to improve his/her role in a particular mission or a situation. The application of the PPM concept could improve dramatically the state-of-the-art in the HITL field in various vehicular technologies and beyond. The examples are taken mostly from the field of avionic safety.
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Unaffiliated researchers can access the work here: http://dx.doi.org/10.1080/1463922X.2014.895879
Suhir, E., (2015). 1.Human-in-the-loop: probabilistic predictive modelling, its role, attributes, challenges and applications. Theoretical Issues in Ergonomics Science. Vol. 16, Iss. 2, 99-123