Jewon Yoon, Chulhwan Kim, Wee Sun Lee, Hyejin Kang, J. Lee
{"title":"Parameter analysis and Reliability Evaluation of Road Traffic Noise Prediction Model for Highway Traffic Noise Evaluation","authors":"Jewon Yoon, Chulhwan Kim, Wee Sun Lee, Hyejin Kang, J. Lee","doi":"10.4491/ksee.2022.44.8.267","DOIUrl":null,"url":null,"abstract":"The purpose of this study is to evaluate the reliability of prediction models(KHTN, RLS-90, CRTN, NMPB-08) that are widely used in road traffic noise analysis. For this purpose, the accuracy and difference values of the prediction model were analyzed by comparing the measurement values performed at the total of 21 highway sites, reflecting various conditions such as road structure, road pavement type, and noise barrier installation. In addition, the correlation between commercial programs(SoundPlan, CadnaA) was compared and reviewed for each of the same prediction models. First of all, as a result of analyzing the accuracy of each prediction model, KHTN is rated as 92.8% the most accurate based on ±3 dB error range. And CRTN is rated as 74.0~76.8% the most accurate among prediction models inherent in commercial programs. And, as a result of analyzing the correlation between commercial programs for prediction models, CRTN is 100% highly correlated and NMPB has the lowest correlation by 69.6%.","PeriodicalId":52756,"journal":{"name":"daehanhwangyeonggonghaghoeji","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"daehanhwangyeonggonghaghoeji","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4491/ksee.2022.44.8.267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The purpose of this study is to evaluate the reliability of prediction models(KHTN, RLS-90, CRTN, NMPB-08) that are widely used in road traffic noise analysis. For this purpose, the accuracy and difference values of the prediction model were analyzed by comparing the measurement values performed at the total of 21 highway sites, reflecting various conditions such as road structure, road pavement type, and noise barrier installation. In addition, the correlation between commercial programs(SoundPlan, CadnaA) was compared and reviewed for each of the same prediction models. First of all, as a result of analyzing the accuracy of each prediction model, KHTN is rated as 92.8% the most accurate based on ±3 dB error range. And CRTN is rated as 74.0~76.8% the most accurate among prediction models inherent in commercial programs. And, as a result of analyzing the correlation between commercial programs for prediction models, CRTN is 100% highly correlated and NMPB has the lowest correlation by 69.6%.