scholarly journals Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Traffic Noise

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Maghrour Zefreh ◽  
Adam Torok

Road traffic noise is one of the most relevant sources in the environmental noise pollution of the urban areas where dynamics of the traffic flow are much more complicated than uninterrupted traffic flows. It is evident that different traffic conditions would play the role in the urban traffic flow considering the dynamic nature of the traffic flow on one hand and presence of traffic lights, roundabouts, etc. on the other hand. The main aim of the current paper is to investigate the effect of different traffic conditions on urban road traffic noise. To do so, different traffic conditions have been theoretically generated by the Monte Carlo Simulation technique following the distribution of traffic speed in the urban roads. The “ASJ RTN-Model” has been considered as a base road traffic noise prediction model which would deal with different traffic conditions including steady and nonsteady traffic flow that would cover the urban traffic flow conditions properly. Having generated the vehicles speeds in different traffic conditions, the emitted noise (LWA) and subsequently the noise level at receiver (LA) were estimated by “ASJ RTN-Model.” Having estimated LWA and LA for each and every vehicle in each traffic condition and taking the concept of transient noise into account, the single event sound exposure levels (SEL) in different traffic conditions are calculated and compared to each other. The results showed that decelerated traffic flow had the lowest contribution, compared to congestion, accelerated flow, free flow, oversaturated congestion, and undersaturated flow by 16%, 14%, 12%, 12%, and 10%, respectively. Moreover, the distribution of emitted noise and noise level at receiver were compared in different traffic conditions. The results showed that traffic congestion had considerably the maximum peak compared to other traffic conditions which would highlight the importance of the range of generated noise in different traffic conditions.

2020 ◽  
Vol 10 (7) ◽  
pp. 2451 ◽  
Author(s):  
Giovanni Brambilla ◽  
Roberto Benocci ◽  
Chiara Confalonieri ◽  
Hector Eduardo Roman ◽  
Giovanni Zambon

Noise energetic indicators, like Lden, show good correlations with long term annoyance, but should be supplemented by other parameters describing the sound fluctuations, which are very common in urban areas and negatively impact noise annoyance. Thus, in this paper, the hourly values of continuous equivalent level LAeqh and the intermittency ratio (IR) were both considered to describe the urban road traffic noise, monitored in 90 sites in the city of Milan and covering different types of road, from motorways to local roads. The noise data have been processed by clustering methods to detect similarities and to figure out a criterion to classify the urban sites taking into account both equivalent noise levels and road traffic noise events. Two clusters were obtained and, considering the cluster membership of each site, the decimal logarithm of the day-time (06:00–22:00) traffic flow was used to associate each new road with the clusters. In particular, roads with average day-time hourly traffic flow ≥1900 vehicles/hour were associated with the cluster with high traffic flow. The described methodology could be fruitfully applied on road traffic noise data in other cities.


2014 ◽  
Vol 1073-1076 ◽  
pp. 522-525
Author(s):  
Fu Guo Zhao

Considering the Impact of the current urban road traffic noise,I optimize the traffic noise monitoring points on the basis of the actual measurement data. The experimental results prove that less monitoring points may reflect the overall traffic noise level in Binzhou City.


2021 ◽  
Vol 11 (16) ◽  
pp. 7196
Author(s):  
Dámaris A. Jiménez-Uribe ◽  
Darwin Daniels ◽  
Zoë L. Fleming ◽  
Andrés M. Vélez-Pereira

The objective of this study was to determine the influence of vehicular traffic on the environmental noise levels of the Santa Marta City tourist route on the Colombian coast. An analysis of vehicle types and frequencies at various times of the day over nearly a year helped to track the main sources of environmental noise pollution. Five sampling points were selected, which were distributed over 12 km, with three classified as peripheral urban and two as suburban. The average traffic flow was 966 vehicles/h and was mainly composed of automobiles, with higher values in the peripheral urban area. The noise level was 103.3 dBA, with background and peak levels of 87.2 and 107.3 dBA, respectively. The noise level was higher during the day; however, there were no differences between weekdays and weekends. The results from the analysis of variance showed that the number of vehicles and the noise levels varied greatly according to the time of day and sampling point location. The peak and mean noise levels were correlated with the number of automobiles, buses and heavy vehicles. The mean noise levels were similar at all sample points despite the traffic flow varying, and the background noise was only correlated for automobiles (which varied much more than the heavy vehicles between day and night).


2016 ◽  
Vol 22 (1) ◽  
Author(s):  
PETROVICI ALINA ◽  
TOMOZEI CLAUDIA ◽  
NEDEFF FLORIN ◽  
IRIMIA OANA ◽  
PANAINTE-LEHADUS MIRELA

<p>This paper presents a synthesis of current state of the assessment of road traffic noise in urban areas considering economic, social and legal aspects. Therefore, there were described several prediction methods of the urban traffic noise. These methods are useful in calculating the exposure of the population at noise levels which exceed the permissible limits. Mapping is one of the most common methods used for the assessment of noise. Whether it is industrial, airport, rail or road traffic noise, noise mapping provides accurate data needed later in developing action plans against noise. The road traffic noise assessments are performed periodically, and a representative picture of the noise in the analysed areas is obtained. Then, the action plans can be developed in order to reduce road traffic noise, where it is necessary.</p>


Noise Mapping ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 74-83
Author(s):  
Pervez Alam ◽  
Kafeel Ahmad ◽  
S. S. Afsar ◽  
Nasim Akhtar

AbstractNoise pollution has been rising as a critical issue in recent days particularly for the people living in urban areas. This study has been conducted to find out the effects of traffic induced noise on nearby residential building through 3D noise mapping with and without noise Barriers. Monitoring has been carried out at various densely populated preselected locations of Delhi, India. Thereafter, 3D noise mapping has been done using hourly average noise levels for the locations exposed with maximum noise. The developed 3D noise map shows the variation of noise level along X, Y and Z direction for all selected locations before and after installation of noise barriers. Moreover, the result also shows that exact assessment of noise impact is possible through 3D noise mapping, when a multistory building close to the source of noise is taken into consideration. This paper also elaborates the adequate height, distance and NRC value of noise barrier to reduce the effect of road traffic noise on nearby high rise building. Reduction pattern of noise level can easily be visualized and evaluated by using these maps. This type of study could support decision makers during adaptation of suitable remedial measures.


Author(s):  
Vilas K Patil ◽  
P.P. Nagarale

Recently in urban areas, road traffic noise is one of the primary sources of noise pollution. Variation in noise level is impacted by the synthesis of traffic and the percentage of heavy vehicles. Presentation to high noise levels may cause serious impact on the health of an individual or community residing near the roadside. Thus, predicting the vehicular traffic noise level is important. The present study aims at the formulation of regression, an artificial neural network (ANN) and an adaptive neuro-fuzzy interface system (ANFIS) model using the data of observed noise levels, traffic volume, and average speed of vehicles for the prediction of L10 and Leq. Measured noise levels are compared to the noise levels predicted by the experimental model. It is observed that the ANFIS approach is more superior when compared to output given by regression and an ANN model. Also, there exists a positive correlation between measured and predicted noise levels. The proposed ANFIS model can be utilized as a tool for traffic direction and planning of new roads in zones of similar land use pattern.


2016 ◽  
Vol 22 (1) ◽  
pp. 81-89
Author(s):  
ALINA PETROVICI ◽  
CLAUDIA TOMOZEI ◽  
FLORIN NEDEFF ◽  
OANA IRIMIA ◽  
MIRELA PANAINTE-LEHADUS

This paper presents a synthesis of current state of the assessment of road traffic noise in urban areas considering economic, social and legal aspects. Therefore, there were described several prediction methods of the urban traffic noise. These methods are useful in calculating the exposure of the population at noise levels which exceed the permissible limits. Mapping is one of the most common methods used for the assessment of noise. Whether it is industrial, airport, rail or road traffic noise, noise mapping provides accurate data needed later in developing action plans against noise. The road traffic noise assessments are performed periodically, and a representative picture of the noise in the analysed areas is obtained. Then, the action plans can be developed in order to reduce road traffic noise, where it is necessary.


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