Wenyi Li, Yang Hu, Yajing Ji, Muqing Liu, Haiping Shen
{"title":"基于实测的路面亮度系数表预测数据库检索方法","authors":"Wenyi Li, Yang Hu, Yajing Ji, Muqing Liu, Haiping Shen","doi":"10.1080/15502724.2020.1813038","DOIUrl":null,"url":null,"abstract":"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 (Lave, U0, Ul ) 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 (EQ0 = 2.1%, ES1 = 5.0%, Error = 2.3%). Moreover, the proposed method also exhibits an improved luminance response and achieves a 2.1% difference in Lave , a 3% difference in U0 , and a 1.8% difference in Ul . This study proves that the proposed database retrieval method improves the model prediction accuracy.","PeriodicalId":49911,"journal":{"name":"Leukos","volume":"9 1","pages":"21 - 29"},"PeriodicalIF":2.6000,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Database Retrieval Method for the Prediction of Reduced Luminance Coefficient Tables of A Road Surface Based on Measurements in Situ\",\"authors\":\"Wenyi Li, Yang Hu, Yajing Ji, Muqing Liu, Haiping Shen\",\"doi\":\"10.1080/15502724.2020.1813038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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 (Lave, U0, Ul ) 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 (EQ0 = 2.1%, ES1 = 5.0%, Error = 2.3%). Moreover, the proposed method also exhibits an improved luminance response and achieves a 2.1% difference in Lave , a 3% difference in U0 , and a 1.8% difference in Ul . This study proves that the proposed database retrieval method improves the model prediction accuracy.\",\"PeriodicalId\":49911,\"journal\":{\"name\":\"Leukos\",\"volume\":\"9 1\",\"pages\":\"21 - 29\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2020-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Leukos\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/15502724.2020.1813038\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Leukos","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/15502724.2020.1813038","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
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 (Lave, U0, Ul ) 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 (EQ0 = 2.1%, ES1 = 5.0%, Error = 2.3%). Moreover, the proposed method also exhibits an improved luminance response and achieves a 2.1% difference in Lave , a 3% difference in U0 , and a 1.8% difference in Ul . This study proves that the proposed database retrieval method improves the model prediction accuracy.
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