A Database Retrieval Method for the Prediction of Reduced Luminance Coefficient Tables of A Road Surface Based on Measurements in Situ

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.

KEYWORDS:

• Road lighting
• road surface
• reduced luminance coefficient
• in-situ measurement
• database retrieval method

Acknowledgments

The authors would like to thank Qun Gu and Xu Zeng from Philips Research for their help on mathematical programming.

Disclosure statement

The authors have no financial interests to declare.

Additional information

Funding

This article is published with the support of the National Key R&D Program of China under Grant 2017YFB0403504.