###### Abstract  
The primary objective of the research and analysis reported in this article was to determine an effective method for predicting the luminance coefficient of the mineral mixture for asphalt concrete and stone mastic asphalt. The luminance of the mineral mixture determines the final luminance value of the surface. Predicting the luminance coefficient quickly will significantly improve the mineral-asphalt mix design efficiency in selecting aggregates that meet functional requirements and increase the brightness of the surface. The research process consisted of two stages. The first stage covered modelling the Qd luminance coefficient of aggregate, taking into account its petrographic analysis. The second fundamental stage, based on the research of the first stage, concerned the modelling of the luminance coefficient of the mineral mixture, taking into account the percentage share of a given component, its grain size, and its photometric properties. An effective technique of reinforced trees was used for modelling. As a result of its application, a model match to experimental data was achieved at the level of 87%. It has also been shown that the greatest impact on increasing the luminance coefficient of the mineral mixture was the use of light aggregate (quartzite sandstone or limestone) with a grain size of 2/5 in quantities > 40% or 8/11 in quantities > 60%. Furthermore, the quartzite sandstone aggregates with a grain size of 5/8 had the highest efficiency in lightening the mineral mixture. However, the use of basalt aggregates of the same fraction significantly worsened the photometric properties of the mineral mixture. An important element of the research was also to indicate that the mineralogical composition of the aggregate is crucial for an accurate assessment of its luminance coefficient. luminance; road aggregate; machine learning; petrography; road pavement surface +
Footnote †: journal: Applied Sciences  
0000-0001-9999-4000-0000]M.M. R4. Each of the four classes has a defined light reflection array (r-table) containing a reduced luminance coefficient [4]. Unfortunately, the R classification is based on measurements from the 1960s and 1970s, and it should be taken into account that there have been changes in the technology of making asphalt surfaces (mma) and the requirements for macrotexture, and new types of asphalt aggregates [5] have been introduced. A fundamental fact, increasingly noticeable in scientific publications and industry articles, is that bright surfaces heat up less during periods of intense sunlight and provide a higher contrast of the road profile compared to the roadside. It should not be forgotten that a very important element of road illumination is also the reduction of the amount of energy required to ensure adequate visibility at night. In this aspect, the amount of energy consumed by lighting is about 1.3% used by road lighting in the EU [6]. However, the following question remains: what should be considered when lightening the surface? The reflection of a light beam from the surface of the road is a function of the physical state of the road and its nature, as well as the direction of the light beam and observation conditions [5]. Different surfaces may have different reflection characteristics, even though the light intensity (measured in lux) is the same. Along with the change in reflective properties of road surfaces, the luminance of pavement will also change [7]. Luminance is closely related to the type of aggregate and the state of surface wear. Reflection from the road surface is a function of the physical condition of the road and its character, as well as from the direction of its illumination and observation conditions [5]. Different surfaces can have various reflection characteristics, which depend on the texture of the surface and its age, the materials making up the surface, the binding materials, and the ways of arrangement. The criterion for their acceptance still remains its operational features [8].