A Cognitive-Computational Model of Comfort Categorization in Civil Aviation Propeller Aircraft

The present work is dedicated to modeling and analyzing processes of vibro-acoustic comfort perception among passengers in a civil aviation propeller aircraft. The experimental data analyzed in this study were collected as part of the European project IDEA PACI (IDEntification of an Aircraft PAssenger Comfort Index) and encompass both vibro-acoustic and psychometric characteristics. We introduce a computational model of the perceptual processes of passenger comfort for this vehicle class based on an automatic classification system with cognitive plausibility. This system incorporates both prototype theory and exemplar theory of categorization. The study has two primary objectives: first, to develop an artificial classification system with high performance, serving as a valuable support tool for designing more comfortable aircraft; second, to investigate which of the considered cognitive theories most accurately represents the categorization process of human comfort. The experimental results, including other instance-based systems, demonstrate that the computational model used (the Prototype Exemplar Learning - Classifier) effectively predicts human passenger comfort, and the type of representative instances inferred by the system indicates a clear predominance of exemplar theory over prototype theory in modeling the perception of comfort.