A key question for road traffic noise management is whether prediction of human response to noise, including sleep quality, could be improved over the use of conventional energy equivalent, or percentile, measures, by accounting for noise events in road traffic streams. This paper reports initial results from a noise-events investigation into event-based indicators over an exhaustive set of traffic flow, traffic composition, and propagation distance, conditions in unshielded locations in proximity to roadways. We simulate the time-varying noise level histories at various distances from roadways using a dynamic micro-traffic model and a distribution of sound power levels of individual vehicles. We then develop a comprehensive set of noise event indicators, extrapolated from those suggested in the literature, and use them to count noise events in these simulated time histories. We report the noise-event algorithms that produce realistic, and reliable, counts of noise events for one-hour measurement periods, then reduce redundancy in the indicator set by suggesting a small number of representative event indicators. Later work will report the traffic composition and distance conditions under which noise event measures provide information uncorrelated with conventional road traffic noise indicators — and which thus may prove useful as supplementary indicators to energy-equivalent measures for road traffic noise
