The simulation showed that the Source SPD method caused a significant error of road surface spectral reflectance but could reduce inaccuracy with a correction. In addition, the Source SPD method was not adequate for lighting applications in a scene with multiple light source types [11]. A simulation also conducted by [PERSON] involved four factors, which were the area of measurement (AOM), surrounding luminance effect (SLE), luminance distribution (LD), and eye movement (EMs) of observers to determine adaption luminance for mesopic photometry. From the comparison between the simulation method and two predictors for complex luminance distributions (LD), it pointed out that the adaption luminance could be well predicted with the average luminance of the AOM method except for the condition that has high luminance sources around the AOM [12]. In general, a light source with higher correlated color temperature is provided with a higher S/P-ratio [13]. If a light source has a higher S/P-ratio, visual brightness would be relatively higher in the isotopic conditions, which is likely to enhance night-time visual performance and beneficial to mesopic design [14]. However, if a light source has stronger spectral radiance in about 530 nm, it should be relatively brighter in mesopic vision, but S/P-ratio cannot depict it. [PERSON] discovered a solution for improving the parameters related to the mesopic application, including S/P-ratio and the mesopic luminance of a light source. In their experiment, an optical power ratio algorithm was adopted to select appropriate spectral power distribution (SPD) for their optimal purpose [15]. The CIE proposed Color Rendering Index (CRI) metric compares color differences of eight Munsell color samples illuminated by the light source and a reference illuminant (daylight for CCT \(\geq\) 5000 K; blackbody for CCT \(<\) 5000 K) with the same CCT. Due to the visual judgment affected by high chroma colors and the chroma of the color samples used by the CRI are not high enough, previous studies showed that the CRI score does not have an excellent correlation to the visual preference of saturating LED light sources. To solve this problem, the color quality scale (CQS), which uses high chroma test samples and non-line color difference scaling, was proposed to heighten the correlation. [PERSON] developed a spectral optimization model to acquire the most appropriate SPD for unique mesopic luminous efficacy of white LED consisted of a blue-chip, yellow, and red quantum dots with the ideal color rendering properties. From their discovery, the optimal full width at half maximum (FWHM) of each color was 30 nm, which could achieve the maximum value of mesopic luminous efficiency. The optimized peak wavelength and reasonable colorimetric performances of each color component with CRI \(\geq\) 70 and CQS \(\geq\) 60 as well as CRI \(\geq\) 85 and CQS \(\geq\) 85 for maximizing the mesopic luminous efficiency at CCTs from 2700 K to 45,000 K were here recommended [13]. The CRI refers to the general Color Rendering Index, which is a metric to judge the color performance of a light source. [PERSON] designed desirable trichromatic and tetrachromatic SPDs of white LED light sources that have high luminous efficacy and acceptable color rendering. An optimal spectrum for trichromatic white LED with a combination of wavelengths at 460, 540, and 615 nm provided the best luminous efficacy, 336 lm/W [16]. [PERSON] discussed the visual performance by implementing a dynamic experiment in reaction time with high, middle, and low color temperatures, and the results implied that the reaction time decreased with the raising of background brightness and contrast and the high color temperature LED [17]. [PERSON] modified the parameters \(a\) and \(b\) to avoid no solution or multi-solutions and proposed the Bisection-Newton method for faster convergence in the CIE system of mesopic photometry MES2.