Predicting User-Preferred Ventilated Seat Intensity in a Dynamic Cooling Environment: A Pilot Study for Adaptive Smart Vehicle Seats

This pilot study investigated user-preferred ventilated seat intensity levels under simulated hot vehicle cabin cooling conditions to support adaptive seat ventilation systems. Thirty-three participants were exposed to a transient cooling environment in which cabin temperature decreased from approximately 38 °C to 25 °C following air-conditioning activation. Participants selected preferred seat ventilation intensity levels (Low, Medium, or High) while demographic and environmental variables were evaluated. Results indicated that cabin temperature was the strongest predictor of ventilation intensity preference, followed by elapsed cooling time and relative humidity. Age demonstrated a statistically significant effect, whereas height, body weight, BMI, and sex were not statistically significant predictors. An exploratory multinomial logistic regression model demonstrated preliminary predictive feasibility with a cross-validated classification accuracy of 73.2%. The findings suggest that occupant-preferred ventilation intensity levels may be estimated using demographic and environmental variables under transient vehicle cooling conditions.