This study evaluates the performance and robustness of 22 established and newly proposed glare prediction metrics. Experimental datasets of daylight-dominated workplaces in office-like test rooms were collected from studies by seven research groups in six different locations (Argentina, Denmark, Germany, Israel, Japan and the United States). The variability in experimental setups, locations and research teams allowed reliable evaluation of the performance and robustness of glare metrics for daylight-dominated workplaces. Independent statistical methods were applied to individual datasets and also to one combined dataset to evaluate the performance and robustness of the 22 glare metrics. As performance and robustness are not established in literature, we defined performance as: (1) the ability of the metric value to describe the glare scale (evaluated by Spearman rank correlation), and (2) the ability of the metric to distinguish between disturbing and non-disturbing situations (evaluated by diagnostic receiver operating characteristic curve analysis tests). Furthermore, we defined robustness as the ability of a metric to deliver meaningful results when applied to different datasets and to fail as few as possible statistical tests. Average Spearman rank correlation coefficients in the range of 0.55–0.60 as well as average prediction rates to distinguish between disturbing and non-disturbing glare of 70–75% for several of the metrics indicate their reliability. The results also show that metrics considering the saturation effect as a main input in their equation perform better and are more robust in daylight-dominated workplaces than purely contrast-based metrics or purely empirical metrics. In this study, the daylight glare probability (DGP) delivered the highest performance amongst the tested metrics and was also found to be the most robust. Future research should aim to optimise the terms of glare equations which combine contrast and saturation effects, such as DGP, PGSV or UGRexp, to achieve metrics that also perform reliably in dimmer lighting conditions than the ones explored in this study.
This paper introduces a novel approach for the assessment of daylight performance in buildings, venturing beyond existing methods that evaluate 2-dimensional illumination and comfort within a fixed field-of-view in order to predict human responses to light concerning non-visual health potential, visual interest, and gaze behavior in a visually immersive scene. Using a 3D rendered indoor environment to exemplify this coordinated approach, the authors assess an architectural space across a range of view directions to predict non-visual health potential, perceptual visual interest, and gaze behavior at the eye level of an occupant across an immersive field-of-view. This method allows the authors to explore and demonstrate the impact of space, time, and sky condition on three novel daylight performance models developed to predict the effects of ocular light exposure using a humancentric approach. Results for each model will be presented in parallel and then compared to discuss the need for a multi-criteria assessment of daylight-driven human responses in architecture. A parallel and comparative approach can allow the designer to adapt the architectural space based on the program use and occupants needs.
Discomfort glare is a major challenge for the design of workplaces. The existing metrics for discomfort glare prediction share the limitation that they do not take gaze direction into account. To overcome this limitation, we developed a ‘gaze-driven’ method for discomfort glare assessment. We conducted a series of experiments under simulated office conditions and recorded the participants’ gaze using mobile eye tracking and the luminance distributions using high dynamic range imaging methods. The two methods were then integrated to derive ‘gaze-centred’ luminance measurements in the field of view. The existing ‘fixed-gaze’ and the newly developed ‘gaze-driven’ measurement methods are compared. Our results show that there is a significant difference between the two methods. In this paper, the procedure for integrating the recorded luminance images with the recorded gaze dynamics for obtaining gaze-centred luminance data is described. This gaze-centred luminance data will be compared to the subjective assessment of glare in Part 2 of this study.
For the application of discomfort glare metrics, a categorisation is used, dividing the metric scale into categories of perception. These categories are separated by borderline values, or so-called cut-off values. Recent literature shows that these cut-off values are lower when they are derived from field study data than those derived from laboratory study data. To investigate this further, the data from one field study and two laboratory studies was used to derive and compare cut-off values corresponding to three borderlines. The results show that the field study cut-off values were systematically lower than the laboratory study ones, implying that discomfort glare is reported at lower stimulus magnitudes in the field. Although further research is required on that topic, several hypotheses are discussed in order to explain the gap between cut-off values derived from field data and cut-off values derived from laboratory data. Recommendations for future studies are also provided.
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