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Prediction of Statistical Noise Metrics for Road Traffic

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Objective: To improve current methods of prediction of road traffic noise impact levels. Methods: A method of predicting road traffic noise using A-weighted statistical levels has been developed, primarily focussed on modelling individual source position and noise emission characteristics. The validity of the model has been verified by field studies involving concurrent vehicle flow and noise level surveying. Results: Results using the model have been predicted under a range of traffic flow conditions for observation positions nominally 15 metres from the nearest carriageway. Statistical metrics and equivalent energy levels have been predicted for observation periods of 1 hour duration, with a very satisfactory level of accuracy better than 3dB(A) when compared against measurement observation. Conclusion: The method produces a more informed prediction describing the potential impact on a community from a road project when compared with energy equivalent level predictions alone. Implication: The methodology could be utilised for assessment of any stochastic and/or physically mobile noise generating system, such as a railway, an open-cut mine, construction site, industry or carpark. The method could be enhanced using narrow band prediction.

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Document Type: Research Article

Affiliations: The University of Sydney

Publication date: 30 September 2019

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  • The Noise-Con conference proceedings are sponsored by INCE/USA and the Inter-Noise proceedings by I-INCE. NOVEM (Noise and Vibration Emerging Methods) conference proceedings are included. All NoiseCon Proceedings one year or older are free to download. InterNoise proceedings from outside the USA older than 10 years are free to download. Others are free to INCE/USA members and member societies of I-INCE.

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