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http://dx.doi.org/10.12652/Ksce.2018.38.4.0587

Development of Prediction Models for Traffic Noise Considering Traffic Environment and Road Geometry  

Oh, Seok Jin (Chonnam National University)
Park, Je Jin (Korea Expressway Corporation)
Choi, Gun Soo (Chonnam National University)
Ha, Tae Jun (Chonnam National University)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.38, no.4, 2018 , pp. 587-593 More about this Journal
Abstract
The current road traffic noise prediction programs of Korea, which are widely used, are based upon foreign prediction model. Thus, it is necessary to verify foreign prediction models to find out whether they are suitable for the domestic road traffic environment. In addition, an analysis and an in-depth study on the main factors should be conducted in advance as the influence factors on the occurrence of traffic noise vary for each prediction model. Therefore, this study examined the influence factors and the existing prediction models used to forecast road traffic noise. Also, analyzed their relationship with the factors influencing the noise generated by driving vehicles through multiple regression analysis using a prediction model, taking into consideration of the traffic environment and the road geometric structure. In addition, this study will apply experimental values to the existing road traffic noise prediction model (NIER, RLS-90) and the deducted road traffic noise prediction model. As a result, the order of the absolute value sum of the errors are NIER, RLS-90, model value. Through comparison and verification, developed models are to be analyzed for providing basic research results for future study on road traffic noise prediction modeling.
Keywords
Traffic noise; Traffic environment; Road geometry; Multiple regression;
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