A study of the performance of a generalized exceedance algorithm for detecting noise events caused by road traffic

Abstract

A key question for road traffic noise management is whether prediction of human response to road traffic noise could be improved by accounting for noise events instead of, or in addition to, energy equivalent or percentile measures of noise exposure. However, there is a critical prior question: how should noise events in road traffic be measured? Even at moderate traffic flow rates, detecting and counting noise events caused by road traffic is not a trivial exercise, and as yet there is no generally accepted noise event detection algorithm. This paper investigates the performance of a generalized exceedance algorithm for detecting noise events, constructed on the basis of the literature on noise events caused by road traffic. For this purpose, a microscopic traffic simulation model, coupled to an emission model that accounts for distributions of sound power levels of individual vehicles, is used to simulate one-hour time histories of the noise level in the proximity of a roadway, for an exhaustive set of traffic flow/composition and propagation distance conditions in unshielded locations. The validity and reliability of the number of noise events detected by the generalized algorithm in these one-hour time histories is then evaluated for a range of algorithm parameter sets. By discarding parameter sets that do not result in an algorithm that returns valid or reliable counts, and by examining redundancy in the remaining ones, a small number of representative parameter sets is identified, which may prove useful in the construction of event-based indicators supplementary to energy-equivalent measures of road traffic noise.

Methods for Noise Event Detection and Assessment of the Sonic Environment by the Harmonica Index

“…Individual events in the sound pressure level (SPL) time history of the environmental noise are usually identified by an exceedance-based detection algorithm. As detailed in the extensive literature review reported in [15], the onset of a noise event is detected when the instantaneous SPL exceeds a threshold level L β for a duration τ in s, and with an emergence of at least E dB. Noise events are only retained when the time gap (or noise free interval) since the previous detected event is larger than τ g [16].…”

“…Thus far, several methods and algorithms have been proposed to detect sound events in environmental noises. Many of them look at transients in the sound level time history, such as exceedances above fixed or time adaptive thresholds [14][15][16][17]; others focus on modeling the hearing perception process of such events [9]. A review of the wide range of algorithms, protocols, or criteria reported on in the literature for identifying noise events within a time series of A-weighted sound levels, usually from road, rail, or aircraft sources, is given in [15].…”

“…Many of them look at transients in the sound level time history, such as exceedances above fixed or time adaptive thresholds [14][15][16][17]; others focus on modeling the hearing perception process of such events [9]. A review of the wide range of algorithms, protocols, or criteria reported on in the literature for identifying noise events within a time series of A-weighted sound levels, usually from road, rail, or aircraft sources, is given in [15]. In particular, in [16], a small set of parameters were identified, which may prove useful in the construction of event-based indicators supplementary to energy-equivalent measures of road traffic noise.…”

Low-Cost Distributed Acoustic Sensor Network for Real-Time Urban Sound Monitoring

“…Another interesting approach of the monitoring network projects is the hybrid approach of crossing the acoustic information with subjective perception surveys, to consider the typology of the events in relationship with sleep quality [42]. A sound recognition system is applied to provide information about the detected sounds and establish a relationship between the perception surveys and the identified events related to road traffic noise [43]. However, this project is only aimed at the identification of the acoustic events and their perception, it has no impact on any noise maps generation.…”

Review of Wireless Acoustic Sensor Networks for Environmental Noise Monitoring in Smart Cities

“…In the smart sound monitoring project, De Coensel et al conducted a study that crossed acoustic information with subjective perception surveys, in order to consider the typology of the acoustic events occurring in relation to the sleep quality [57]. A sound recognition system is applied to provide information about the detected sounds and establish a relationship between the perception surveys and the identified events 6 Journal of Sensors related to road traffic noise [58]. However, the approach is only focused on the identification of the events of interest, not on the noise map generation process.…”