A STUDY OF HIGHWAY NOISE MODEL

• Main Authors: Shih-chieh Wang, 王世傑
• Other Authors: PEI LIU
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/3xsej5

碩士 === 逢甲大學 === 交通工程與管理所 === 95 === It is very expensive to measure the influence of highway noise. There are a lot of noise prediction models for the purpoase of feasibility study, planning and design, environmental impact assessment. The related software such as CADNA-A, SOUNDPLAN to the highway noise simulation is widely use the highway noise impact assessment and project because of the rapid growth of computer ans its popularization.The right prediction model can help us to increase the accuracy of modeling result and save projecr manhour. The noise of highway vehicles is mainly generated from the engine and from frictional contact between the vehicle and the ground and air. In general, road contact noise exceeds engine noise at speeds higher than 60 km/h. The sound pressure level from traffic can be predicted from the traffic flow rate, the speed of the vehicles, the proportion of heavy vehicles, and the nature if the road surface. The study discuses about the difference of DIN18005、RLS-90 and ASJ MODEL 1998. Within this the vechicle flow noise of the highway network by these prediction models. If the difference of the estimated sound level from that of the measurement is large, the calibration on the prediction models to be use will be grealy reduced. As far as we know, the calibration process is performed by conducting concurrent traffic noise level measurements and vehicle counts, and comparing the measured level with that predicted by the models for the given traffic conditions. This calibration procedure can be used to normalize the models output for varying traffic volumes, speeds, and truck compositions present during the noise measurement samples. The error can be up to 10dB, careful analysis of the results, or comparison with similar situations, is required preparation and calibration of a suitable traffic noise prediction model.