scholarly journals Influence of road traffic noise peaks on reading task performance and disturbance in a laboratory context

Acta Acustica ◽  
2022 ◽  
Vol 6 ◽  
pp. 3
Author(s):  
Catherine Lavandier ◽  
Mehdi Regragui ◽  
Romain Dedieu ◽  
Carine Royer ◽  
Arnaud Can
Keyword(s):  
Road Traffic ◽  
Reading Speed ◽  
Traffic Noise ◽  
Sound Level ◽  
Living Room ◽  
Road Traffic Noise ◽  
Personal Factors ◽  
Reading Task ◽  
Four Levels ◽  
Comprehension Rate

The influence of fluctuating road traffic noise on perceived disturbance during a reading task as well as on performance, inside a living room with closed windows, is presented in this paper. Sixteen 2-min sound sequences were created combining two variables: the number of events (four levels varying from one to four car pass-bys) and the peak emergence above the background noise (four levels with a 5 dB(A) step) keeping limited variations of LAmax, 1s. The noise impact was evaluated through a reading task of texts synchronized with the sound sequences, for participants classified into fast or slow readers, and sensitive or non-sensitive to noise. The comprehension rate of the texts decreases as the background sound level increases. The reading speed decreases during the rising front of a peak, and goes back to its former regular reading speed during the descending front of the peak. This slowdown during the rising front reaches 14% for slow readers. The declared disturbance is higher for slow readers compared to fast readers, and higher for noise sensitive persons compared to non-sensitive persons. The influence of the acoustic indicators on the reading disturbance is very small compared to the influence of personal factors. There is even no influence of the number of events on this disturbance.

scholarly journals The influence of a signal’s time structure on the perceived noise annoyance of road traffic noise

2021 ◽  
Author(s):  
Jan Felcyn
Keyword(s):  
Road Traffic ◽  
Temporal Structure ◽  
Traffic Noise ◽  
Sound Level ◽  
Time Structure ◽  
Common Source ◽  
Road Traffic Noise ◽  
Noise Annoyance ◽  
Modern Cities ◽  
Negative Feelings

Abstract Purpose Road traffic noise is the most common source of noise in modern cities. The noise indicators used to manage noise do not take into account its temporal structure. However, in cities the traffic flow varies during the day, peaking due to congestion and more fluent periods. In this research we sought to analyze how people (giving answers on a numerical ICBEN scale) perceive noise stimuli with the same LAeqT values but different time structures (more/less noise events, different amplitude envelopes). Methods 31 people with normal hearing took part in an experiment conducted in an anechoic chamber. Participants listened to 18 different noise recordings and rated each of them using the numerical ICBEN scale regarding noise annoyance. Results The results showed that only sound level was a statistically significant factor. However, based on people’s remarks about noise, we can also say that the more intermittent the noise is, the more negative feelings it evokes in people. Conclusions Time structure does not have a significant influence on people’s judgments about noise annoyance. However, people tend to have a preference for a steady noise rather than an intermittent one.

Statistical Study of the Instantaneous Values of Traffic Noise Sound Pressure Level

2002 ◽  
Vol 33 (8) ◽  
pp. 16-24
Author(s):  
Jesús Alba Fernández ◽  
Marcelino Ferri García ◽  
Jaime Ramis Soriano ◽  
Juan Antonio Martínez Mora
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Relevant Information ◽  
Sound Level ◽  
Pressure Level ◽  
Road Traffic Noise ◽  
Statistical Parameters ◽  
Sound Event

In environmental acoustics the knowledge of the time dependency of the sound level provides relevant information about a sound event. In this sense, it may be said that conventional sound level metres have frequently implemented programs to calculate the fractiles (percentiles) of the distribution of instantaneous sound levels; and there are several indexes to evaluate the noise pollution, based on different statistical parameters. For further analysis of sound, and to obtain the commented indexes, it is accepted that this distribution is normal or gaussian. The questions we've tried to solve in this work are the following: First of all, whether the time dependent distribution of the variable sound pressure level should be considered as Gaussian in general cases or only in some particular ones. On the other hand, we have studied how the frequency of the sampling affects the resulting distribution of a given a sound event. To these ends, a set of road traffic noise events has been evaluated. Furthermore, even in gaussian distributions of sound pressure levels, the average of the distribution will not be coincident with the equivalent sound pressure level; that is the level of the average quadratic pressure. The difference between this parameter, and its dependence on the standard deviation, is studied.

Acoustic Prediction Modeling and Sound Mapping of public transport users' exposure at a bus stop.

2021 ◽  
Vol 263 (2) ◽  
pp. 4058-4069
Author(s):  
Dayane Cristina Lima Estercio ◽  
Paulo Fernando Soares
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Sound Level ◽  
Road Traffic Noise ◽  
High Frequencies ◽  
Reference Models ◽  
The Road ◽  
Bus Stop ◽  
Specular Reflections ◽  
The City

The objective of this research is to develop a mathematical model to predict the road traffic noise level at the bus stop, to assess the level of noise that users of these urban facilities are exposed daily. To help assess the exposure and the environmental impact, sound mapping will be performed using the IMMI software. In the model, the calculation of direct paths and specular reflections and diffuse was adopted. The study was applied in three sections in the city of Maringá, Brazil. At each point, the user was simulated standing and sitting. The sound source was positioned on the axis of each strip, every five meters. In total, 5124 readings of source positions were evaluated in 84 measured points. For the validation, the Anderson-Kurze, Kang, Yang and Zhang, Bistafa and Naish model were applied, and then the t-Student test were applied. The results showed a correspondence between the developed model, the data of the measurements and the reference models in the range of 25 Hz to 10000 Hz, there was a greater variance between the models applied in the high frequencies. It is concluded that the model was able to estimate the sound level of the stretches evaluated.

scholarly journals Analysis of Traffic Noise in Two Cross-Sections at the Road Crossing The City

2020 ◽  
Vol 23 (1) ◽  
pp. B13-B21
Author(s):  
Andrzej Bąkowski ◽  
Leszek Radziszewski
Keyword(s):  
Cross Sections ◽  
Acoustic Pressure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Sound Level ◽  
Road Traffic Noise ◽  
The Road ◽  
Recorded Data ◽  
Relative Differences ◽  
The City

The paper presents an analysis of the noise recorded by the two road traffic noise-monitoring stations. The stations were located in Kielce, Poland, at the road No. 74: on the outskirts of the city and near the center. Based on the experimentally recorded data, an equivalent sound level and acoustic pressure were determined for three sub-intervals of the day: nights, days and evenings. The conducted analyses showed that the average annual values (depending only on the time sub-intervals) of the median do not differ significantly between stations. A similar conclusion can be drawn based on simulations of the median and the C90 percentile of the sound pressure . However, the maximum relative differences in the C99 percentile of the acoustic pressure between stations are around 13%. The maximum relative differences in median pressure between stations are around 15% (for the time sub-interval nights).

Application of BP Neural Network in Traffic Noise Prediction

2012 ◽  
Vol 518-523 ◽  
pp. 3838-3842
Author(s):  
Gang Liu ◽  
Li Hua Lin ◽  
Rui Tian
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Measured Data ◽  
Sound Level ◽  
Road Traffic Noise ◽  
Noise Prediction

A model of BP neural network for road traffic noise prediction was established by using some road traffic parameters in this paper. Then use this model to predict equivalent continual sound level of road traffic noise, After an overview about the neural approach, the learning; and production phase results are shown and contrasted with the measured data. They point out how good is the approach proposed to model noise pollution in urban areas.

scholarly journals Modelling of road traffic noise

2018 ◽  
Vol 157 ◽  
pp. 02001
Author(s):  
Andrzej Bąkowski ◽  
Leszek Radziszewski ◽  
Vladimir Dekys
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Sound Level ◽  
Road Traffic Noise ◽  
Urban Mobility ◽  
Level Indicator ◽  
Fundamental Parameters ◽  
The Road ◽  
Effective Implementation ◽  
Traffic Rate

Effective implementation of the EC Communication relating to urban mobility is dependent on adopting relevant indicators that will allow comprehensive assessment of the measures undertaken under the urban mobility plan. One of the fundamental parameters for this assessment is the equivalent sound level indicator, measured over the 24-hour period, used to evaluate the annoyance of the road traffic noise. Not only is its value important but also its variability. This paper reports the results of the analysis of traffic noise along a major road, performed using various descriptors. The data recorded continuously throughout the year by the traffic rate and noise monitoring terminal were used to construct the measurement database. Analysis of the results was performed for the period between March and June in 2011 and 2016. The road was renovated between 2013 and 2015. The noise variability assessment was conducted using classical and positional indicators. Measurement uncertainties were evaluated.

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