Reflectance of interurban-road pavements from radar-based measurements

Fernández, Paz; Peña-García, Antonio; Poyatos-Martínez, David; Escot-Bocanegra, David; Fernández-Oliveras, Alicia

doi:10.1117/12.2020965

Cited by 2 publications

(1 citation statement)

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“…Fernandez et al [31] investigated the reflectance of interurban road pavement by real-time radar measurement. Moretti et al [32] conducted a lighting design and case study of continuously reinforced concrete pavement, plain concrete pavement, and asphalt pavement to determine differences in pavement materials.…”

Section: Introductionmentioning

confidence: 99%

Influence of the Surface Texture Parameters of Asphalt Pavement on Light Reflection Characteristics

Xu,

Qian,

Zhang

et al. 2023

Applied Sciences

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The optical reflection characteristics of asphalt pavement have an important influence on road-lighting design, and the macrotexture and microtexture of asphalt pavement significantly affect its reflection characteristics. To investigate the impact of texture parameters on the retroreflection coefficient of asphalt pavement, the texture indices of rutted plate specimens and field asphalt pavement were obtained by a pavement texture tester, including the macrotexture surface area (S1), microtexture surface area (S2), macrotexture distribution density (D1), microtexture distribution density (D2), root mean square slope (Δq), skewness (Rsk), and steepness (Rku). The corresponding retroreflective coefficient RL was measured by using a retroreflectometer. In the laboratory experiments, rutted specimens of AC-13, SMA-13, and OGFC-13 asphalt mixtures were formed. The changes in texture parameters and the retroreflection coefficient of rutting specimens before and after rolling were studied, and a factor-influence model between macro- and microtexture parameters and RL was established, along with correlation models of the texture index and RL. The results show that after the rutting test, S1, S2, D1, D2, Δq, and Rku decreased, Rsk increased, and RL increased. In the single-factor model, the parameters could be used to characterize RL with high prediction accuracy, whereas for the onsite measurements, the parameters Δq, Rsk, and Rku could well characterize RL. The nonlinear model established, based on the BP neural network algorithm, improved the prediction accuracy. This research provides ideas for optimizing the reflection characteristics of asphalt pavement and a decision-making basis for road-lighting design.

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Section: Introductionmentioning

confidence: 99%

Influence of the Surface Texture Parameters of Asphalt Pavement on Light Reflection Characteristics

Xu,

Qian,

Zhang

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

Influence of the Surface Texture Parameters of Asphalt Pavement on Light Reflection Characteristics

Xu,

Qian,

Zhang

et al. 2023

Preprint

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The optical reflection characteristics of asphalt pavement are an important influencing factor in road lighting design, and the macro and micro textures of asphalt pavement significantly affect its reflection characteristics. To investigate the impact of texture parameters on the retroreflection coefficient of asphalt pavement, this study obtained the macroscopic and microscopic texture properties of rutting board specimens and on-site asphalt pavement using a pavement texture tester. The macro- and microtexture parameters, such as macroscopic texture distribution density (D1), microscopic texture distribution density (D2), profile height root-mean-square (Rq), profile slope root-mean-square (Δq), skewness Rsk and kurtosis Rku, were measured, and the corresponding retroreflection coefficient RL was measured using a retro-reflectometer. In the laboratory ex-periments, rutting specimens of AC-13, SMA-13, and OGFC-13 asphalt mixtures were formed. The changes in texture parameters and retroreflection coefficient of different rutting specimens before and after crushing were studied, and a factor influence model between macro- and microtexture parameters and RL was established. And the correlation models of texture index and RL of asphalt pavement are further established. The results showed that in the single factor model, the param-eters can be used to characterize RL with high prediction accuracy, whereas for the on-site meas-urements, the three parameters of Δq, Rsk, and Rku can characterize the RL well. The nonlinear model established on the basis of the B-P neural network algorithm improves its prediction ac-curacy. This research can provide ideas for optimizing the reflection characteristics of asphalt pavement and further provide a decision-making basis for road lighting design.

show abstract

Reflectance of interurban-road pavements from radar-based measurements

Cited by 2 publications

References 1 publication

Influence of the Surface Texture Parameters of Asphalt Pavement on Light Reflection Characteristics

Influence of the Surface Texture Parameters of Asphalt Pavement on Light Reflection Characteristics

Influence of the Surface Texture Parameters of Asphalt Pavement on Light Reflection Characteristics

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