Author(s): De Coensel Bert, Brown A. L.
Prediction of human response to road traffic noise might be improved by accounting for the occurrence of noise events in addition to using indicators solely based on energy equivalent or percentile measures of noise exposure. Although a wide range of procedures for detecting noise events caused by road traffic have been suggested in literature there is yet no generally accepted algorithm. In this study, we examine the performance of a small selection of noise event detection algorithms, chosen to be representative for a more comprehensive set of algorithms that was compiled on the basis of literature. This selected set of noise event detection algorithms is used to count the number of events occurring within the time history of the road traffic noise level, simulated for a wide range of traffic flow, traffic composition, and propagation distance conditions in unshielded locations in proximity of a roadway. This methodology allows identification of the traffic and distance conditions under which event-based measures provide information about the traffic noise that is uncorrelated with energy-equivalent or percentile measures, and thus may prove useful as supplementary indicators to conventional road traffic noise indicators for use in impact assessment and noise management.
Name: Prof Bert De Coensel