## 4 Evaluating the Indoor Luminous Environment and Visual Comfort Perception
### Current Lighting Design Assessment Strategies
#### 4.2.2 Assessment Methods under Low Building Design LOD  
When building systems and occupant space distribution is unknown or unreliable, detailed analyses are hindered and more robust approaches are generally applied. Some metrics become less effective (e.g., \(E_{h}\) and \(U_{o}\)) as some regions of the potentially occupied space could be dedicated to transitional areas (e.g., corridors) and not as task areas. Among literature, the following were identified to have significant potential to better address visual comfort from an occupant-centred perspective when low LOD models are available:  
* _prict_ function, enabling faster yearly calculations of image-based metrics (e.g., \(DGP\)). * To spatially cover the visual experience and map the daylight glare class in the room on an annual basis, [PERSON] et al. [71] proposed setting lower, intermediate and higher threshold limits of \(E_{v}\) that \(DGP\) would rate glare as imperceptible, perceptible and disturbing. These threshold limits are meant to be specific, as they are extracted after identifying the worst condition in the analysed room. The latter is mainly imposed as an occupant located close to the window and with a line of view perpendicular to the window surface plane (few initial point-in-time and image-based simulations are expected). * To reduce computer simulation time while performing point-in-time and spatial analysis, optimized simulation workflows have been proposed and validated. These optimizations comprise the use of cloud computing services and the integration of graphics processing units (GPUs) [72]. For instance, Ladybug tools [73] has created a new simulation platform service based on cloud computing (i.e., Pollination [74]) able to speed up the simulation process. In particular, when a large number of design options should be tested by running them all in parallel. [PERSON] and [PERSON] [75] have developed a suite of GPU-enabled tools that implement ray-tracing functionality that speed-up both Radiance and DAYSIM process by one order of magnitude. * To avoid extensive computer simulations for monitoring glare and lighting sufficiency, more efficient simulation workflows have been proposed. These have managed to supersede the use of rendered images. For instance, [PERSON] [72] presented a method to fast-compute glare (133,000 times faster) based on the calculation of view factors to a discretized sky dome for estimating direct lighting. Alternatively, cubic illuminance can be computed and re-elaborated [76]. Using \(E_{h}\) and \(E_{v}\) to determine lighting sufficiency and computing \(DGP_{S}\), does not require image-based-point-in-time simulations. A cube-grid-based illuminance simulations with the centre on the hypothetical location of the occupant. It will be directional if ray-tracing engines are used (e.g.,Radiance). It can be run on an annual basis and, from this, by specifying a direction of view, eye illuminance (i.e., \(E_{v}\) or \(E_{p}\)) and work-plane illuminance can be directly computed (\(E_{h}\)). Thus, a room can be spatially populated with cubes for mapping all conditions within a room, and posterior data post-processing by exploring multiple view directions can be carried out. This procedure can be carried out more quickly by using a practical approach presented by [PERSON] [77]. Otherwise, a much simpler procedure was proposed by [PERSON] [78] by employing the mean indirect cubic illuminance (MICI). However, none of the exposed modelling methodologies found were related to the variance of occupants' visual experience, resulting in different comfort perceptions, sensations and ratings. None of them has included the physiological or anatomical variations on subjects that would largely alter the subjects' ratings of a given luminous environment. Moreover, these methodologies become unpractical or infeasible to be surveyed within an existing building.