Evaluating a New Suite of Luminance-Based Design Metrics for Predicting Human Visual Comfort in Offices with Daylight

Abstract

ABSTRACTA new suite of visual comfort metrics is proposed and evaluated for their ability to explain the variability in subjective human responses in a mock private office environment with daylight. Participants (n = 48) rated visual comfort and preference factors, including 1488 discreet appraisals, and these subjective results were correlated against more than 2000 unique luminance-based metrics that were captured using high dynamic range photography techniques. Importantly, luminance-based metrics were more capable than illuminance-based metrics for fitting the range of human subjective responses to data from visual preference questionnaire items. No metrics based upon the entire scene ranked in the top 20 squared correlation coefficients, nor did any based upon illuminance or irradiance data, nor did any of the studied glare indices, luminance ratios, or contrast ratios. The standard deviation of window luminance was the metric that best fit human subjective responses to visual preference on seven of 12 questionnaire items (with r2 = 0.43). Luminance metrics calculated using the horizontal 40° band (a scene-independent mask) and the window area (a scene-dependent mask) represented the majority of the top 20 squared correlation coefficients for almost all subjective visual preference questionnaire items. The strongest multiple regression model was for the semantic differential rating (too dim–too bright) of the window wall (adjR2 = 0.49) and was built upon three variables; standard deviation of window luminance, the 50th percentile luminance value from the lower view window, and mean luminance of the 40° horizontal band.