Title: A NOVEL TECHNIQUE OF ALLOWING FOR THE EFFECTS OF PAVEMENT SURFACE TYPE IN THE PREDICTION OF ROAD TRAFFIC NOISE
Abstract: This paper describes how the prediction of road traffic noise is an essential component of modern road design. It is also an important process in the assessment of the potential noise impacts of both new road proposals and the upgrading of existing roads. Many factors such as traffic conditions, road alignment and receptor locations are involved in traffic noise prediction, and the accuracy of which depends on the accuracy associated with the values of the input parameters that quantify these factors. One critical factor is the pavement type, particularly in the case of high-speed roads and freeways. This paper summarizes an extensive body of recent research under contract to QDMR, which was aimed at improving the way in which the effects of pavement type is incorporated into traffic noise prediction procedures. Initially, a very large data set of measured vehicle passby noise levels was established. These data were then analyzed to produce an array of values of the Statistical Passby Index (SPBI), which is a relatively new index that quantifies the effects of pavement type on traffic noise for varying traffic conditions. From there, the set of SPBI values was analyzed to produce pavement type factors that were subsequently incorporated into traffic noise predictions conducted with the US Traffic Noise Model (TNM) on roads and freeways in Queensland. The accuracy of this modified version of TNM was determined by comparing its predictions with measured data by means of a robust statistically based analysis. It was found that the accuracy of the TNM predictions was not affected by this novel technique of allowing for pavement type in the prediction of road traffic noise.
Publication Year: 2003
Publication Date: 2003-01-01
Language: en
Type: article
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Cited By Count: 1
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