ABSTRACT

The in-situ measurements for r-tables have attracted special attention owing to their advantages, including increased speed, simplicity of use, and nondestructive road effects. This study presents a database retrieval method proposed for the construction of a full-scale r-table from an r-table database with 25 r coefficients used as input parameters. The proposed method was used in an in-situ, r-table measurement device as a data processing algorithm. To evaluate the accuracy of the proposed method, we performed a) a table-to-table comparison of Q0, S1, and r-tables constructed by different methods and b) comparisons of calculated luminance values (L_ave, U₀, U_l) for a typical road-lighting scenario based on the use of different r-tables. The table-to-table comparison results indicate that following the application of the proposed method, its calculated Q0, S1, and r-table values were very close to their actual values (E_Q0 = 2.1%, E_S1 = 5.0%, Error = 2.3%). Moreover, the proposed method also exhibits an improved luminance response and achieves a 2.1% difference in L_ave, a 3% difference in U₀, and a 1.8% difference in U_l. This study proves that the proposed database retrieval method improves the model prediction accuracy.

摘要

r 表的原位测量由于其优点而引起了特别关注，包括提高速度、使用简单和无损道路效果。本研究提出了一种数据库检索方法，用于从具有 25 个r系数作为输入参数的r表数据库 构建完整的r表。所提出的方法在原位、r表测量设备中用作数据处理算法。为了评估所提出方法的准确性，我们执行了 a)由不同方法构建的Q0、S1和r表的表到表比较和 b) 计算亮度值的比较（大号_AVE，U ₀，U_升），用于基于使用不同的典型道路照明方案- [R -tables。表与表的比较结果表明，应用所提出的方法后，其计算的Q0、S1和r表值非常接近它们的实际值（E _Q0  = 2.1%，E _S1  = 5.0%，Error  = 2.3%）。此外，提出的方法还表现出改进的亮度响应，并实现在一个2.1％的差异大号_AVE，在3％的差异ü ₀，并且在1.8％的差异ù_升. 本研究证明所提出的数据库检索方法提高了模型预测的准确性。