A new procedure for determining the road surface reduced luminance coefficient table by on-site measurements

Strbac-Hadzibegovic, N; Štrbac-Savić, Svetlana; Kostic, M

doi:10.1177/1477153517736804

Cited by 10 publications

(9 citation statements)

References 5 publications

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“…Studies show that the average luminance for dark asphalt can only be 30% of the value obtained for a light one [19]. Measurements could be performed in the field to determine the real reduced luminance coefficient [24][25][26], but this would mean closing the road to the traffic for an unacceptable time. Imaging measurements can also be used in order to calculate the reflectance properties of the asphalt, just as the authors have demonstrated in the paper [27].…”

Section: Case Study Regarding the Influence Of Longitudinal Observer Position In Luminance Measurementsmentioning

confidence: 99%

Average Luminance Calculation in Street Lighting Design, Comparison between BS-EN 13201 and RP-08 Standards

et al. 2021

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This paper presents a study on the influence of the observer’s position in relation to the calculation surface. This is the initial observation of the research, respectively that the two standards consider the position of the observer differently. For these situations, two types of calculations were performed. For the first set of calculations, the software used was DIALux 4.13 as this software can perform calculations in line with the RP-08 standard. The second set of calculations was performed with a script that offers the possibility to change the observer’s position. The conclusion was that EN-13201 has a better approach, but both standards could be improved. The second case study refers to the influence of the longitudinal observer position in an average luminance calculation. If one considers RP-08 as a guideline for performing the calculations, the conclusions are that changing the distance from the observer to the calculation surface has absolutely no effect on the average luminance value. On the other hand, if European standards are used as a guideline, changing the distance (from the standardized 60 m, either closer to the calculation surface or further away) can influence the overall results in average luminance and uniformity. Taking into account the results of these two case studies, the conclusion is that both RP-08 and BS-EN 13201 should be updated so that the observer’s distance in relation to the calculation surface would be a variable dependent on the stopping distance calculated based on the speed limit of the road.

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Section: Case Study Regarding the Influence Of Longitudinal Observer Position In Luminance Measurementsmentioning

confidence: 99%

Average Luminance Calculation in Street Lighting Design, Comparison between BS-EN 13201 and RP-08 Standards

et al. 2021

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“…Following this, a number of methods have emerged for evaluating this parameter. Nevertheless, the evaluation of this criterion is complex and still requires an improvement of measurement methods [3]. CIE introduced the R classification system according to which each type of pavement is classified into one of four classes, from R1 to R4.…”

Section: Introductionmentioning

confidence: 99%

Application of Data Mining Techniques to Predict Luminance of Pavement Aggregate

Mazurek

Bąk-Patyna

2023

Applied Sciences

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The primary purpose of the analysis presented here is to assess the feasibility of effectively predicting the aggregate luminance coefficient. Current road lighting standards and recommendations are based on assessing the level and distribution of luminance on the road surface. The brightness of a road surface depends on the amount of light falling on it, as well as the reflective properties of the road surface, which in turn depend on its physical condition, type and mineralogical composition. The complexity of the factors on which the value of the luminance coefficient depends it makes that data mining techniques the most appropriate tools for evaluation luminance coefficient phenomenon. This article uses five types of techniques: C&RT, boosted trees, random forest, neural network, and support vector machines. After a preliminary analysis, it was determined that the most effective technique was the boosted tree method. The results of the analysis indicated that the actual value of the luminance coefficient has multiple modal values within a single aggregate stockpile, depending on the mineralogical composition and grain size, and cannot be determined by a single central measure. The present model allowed us to determine the value of the luminance coefficient Qd with a mean error of 4.3 mcd-m−2·lx−1. In addition, it was found that the best aggregate for pavement brightening that allows high visibility during the day Qd and at night RL is a limestone aggregate. In the group of those that have the ability to potentially brighten the pavement were quartzite and granite aggregates.

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“…31 While these classification methods and specifications are still in use today, some measurements have indicated that the R and W classes do not represent adequately pavements currently used. 32–35 To analyse the change of current pavement reflection properties and their impacts, some researchers have done meaningful works as follows. The SURFACE project conducted by European researchers provided a pre-normative guideline for road characterization including the aging and wet condition of pavement.…”

Section: Introductionmentioning

confidence: 99%

Exploring the effect of pavement reflection and photometric properties on road lighting performance

Xie

Harvey

et al. 2022

Lighting Research & Technology

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The reflection properties of pavement have an impact on the lit environment and thus upon drivers’ vision and comfort and the energy consumption of the lighting installation. The reflection properties combine diffuse and specular components. The specular reflection component changes with different materials: it also changes when the surface is wet, although this is sometimes ignored in lighting design. This study used simulation (DIALux 4.13) to investigate the effect on lighting parameters (luminance, overall uniformity, longitudinal uniformity and threshold increment (TI)) of changes in pavement reflection properties using different pavement materials and under dry and wet conditions. Furthermore, comparison of lighting parameters was made with different road lighting arrangements. The results show that an increase in the specular reflection component leads to an increase in luminance and a decrease in uniformity. Of the surfaces investigated, the porous pavement had the lower luminance but better uniformity. Arranging the lighting installation based on the extreme wettest condition could make luminance and uniformity rise but with an increase of 2–2.5 kWh/m2 annual energy consumption. When trying to control glare problems during design process, it is suggested that uniformity cannot be neglected except the TI.

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A new procedure for determining the road surface reduced luminance coefficient table by on-site measurements

Cited by 10 publications

References 5 publications

Average Luminance Calculation in Street Lighting Design, Comparison between BS-EN 13201 and RP-08 Standards

Average Luminance Calculation in Street Lighting Design, Comparison between BS-EN 13201 and RP-08 Standards

Application of Data Mining Techniques to Predict Luminance of Pavement Aggregate

Exploring the effect of pavement reflection and photometric properties on road lighting performance

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