Perceived comfort prediction by occupant package layout and vehicle seat engineering factors

Abstract

Perceived comfort is one of the most important factors in automotive engineering, but it is also a very complex and difficult to define. Consumer survey and expert evaluation is the mostly used to determine the subjective comfort level. As tech-nology advances, engineering becomes increasingly important during the design review phase.The aim of this study is to define a conceptual framework of the consumers’ per-ceived comfort, which is related to various engineering factors, and to develop a ML-model (Machine Learning model).Totally, 23 variables were determined by various objective measured data from vehicle and vehicle seat as independent variables. Each variable was defined through data conversion and calculation after measuring the physical properties and the geometric characteristics of the vehicle seat, and the characteristics of the sitting package. Totally, 11 variables were defined by various subjective evalua-tion data as dependent variables.Sedans and SUVs from various segments were included in the dataset for devel-opment of the machine learning model.Postscript.This paper is a follow-up study for my previous paper which published by AHFE2023, paper no. 326.Developing the machine learning model is almost developed, however, requires little bit more time. The estimated date of the finish is around end of this year. Current model has over 0.8 of r-square values, but we try to various methods to develop the optimal prediction model. In some cases, it is possible to use several different methods to each engineering purpose. The final result will be included in this paper.

Keywords: Vehicle, Vehicle Seats, Vehicle Comfort, Prediction, Comfort Clinic, Objective Measures, Subjective Measures

DOI: 10.54941/ahfe1005250