scholarly journals The Performance of CRTN Model in a Motorcycle City

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Ni Sheng ◽  
Zherui Xu ◽  
Min Li
Keyword(s):  
Prediction Models ◽  
Road Traffic ◽  
Traffic Noise ◽  
Mean Difference ◽  
Motor Vehicles ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
The World ◽  
Vertical Distributions ◽  
Predicted Values

The Calculation of Road Traffic Noise (CRTN) model is one of the first traffic noise prediction models in the world and has been widely used in many Western countries. However, its performance in a motorcycle city has not been well assessed. This study aims to examine the accuracy of the CRTN model in predicting traffic noise in an Asian city with over half of motor vehicles being motorcycles. The performance of the CRTN model in predicting both roadside and vertical distributions of traffic noise levels is assessed. The results show that the performance of the CRTN model is satisfactory in predicting roadside traffic noise levels, with anR2of 0.832 and a mean difference of +0.52 dB(A) between the measured and predicted values. The performance of the CRTN model is also satisfactory in predicting vertical distribution of traffic noise levels, with anR2of 0.836 and a mean difference of +0.28 dB(A) between the measured and predicted values.

scholarly journals MODELLING URBAN NOISE IN CITYGML ADE: CASE OF THE NETHERLANDS

2017 ◽  
Vol IV-4/W5 ◽  
pp. 73-81 ◽  
Author(s):  
K. Kumar ◽  
H. Ledoux ◽  
T. J. F. Commandeur ◽  
J. E. Stoter
Keyword(s):  
Urban Areas ◽  
Input Data ◽  
Road Traffic ◽  
Traffic Noise ◽  
Environmental Noise ◽  
Motor Vehicles ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
Noise Mapping ◽  
Urban Noise

Road traffic and industrial noise has become a major source of discomfort and annoyance among the residents in urban areas. More than 44 % of the EU population is regularly exposed to road traffic noise levels over 55 dB, which is currently the maximum accepted value prescribed by the Environmental Noise Directive for road traffic noise. With continuously increasing population and number of motor vehicles and industries, it is very unlikely to hope for noise levels to diminish in the near future. Therefore, it is necessary to monitor urban noise, so as to make mitigation plans and to deal with its adverse effects. The 2002/49/EC Environmental Noise Directive aims to determine the exposure of an individual to environmental noise through noise mapping. One of the most important steps in noise mapping is the creation of input data for simulation. At present, it is done semi-automatically (and sometimes even manually) by different companies in different ways and is very time consuming and can lead to errors in the data. In this paper, we present our approach for automatically creating input data for noise simulations. Secondly, we focus on using 3D city models for presenting the results of simulation for the noise arising from road traffic and industrial activities in urban areas. We implemented a few noise modelling standards for industrial and road traffic noise in CityGML by extending the existing Noise ADE with new objects and attributes. This research is a steping stone in the direction of standardising the input and output data for noise studies and for reconstructing the 3D data accordingly.

Road Traffic Noise Levels at Different Types of Residential Areas in Nibong Tebal, Penang

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Herni Halim ◽  
◽  
Nur Fatin Najiyah Hamid ◽  
Mohamad Firdaus Mahamad Yusob ◽  
Nur Atiqah Mohamad Nor ◽  
...  
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Residential Areas ◽  
Noise Levels ◽  
Different Types

scholarly journals Application of Machine Learning to Include Honking Effect in Vehicular Traffic Noise Prediction

2021 ◽  
Vol 11 (13) ◽  
pp. 6030
Author(s):  
Daljeet Singh ◽  
Antonella B. Francavilla ◽  
Simona Mancini ◽  
Claudio Guarnaccia
Keyword(s):  
Machine Learning ◽  
Linear Models ◽  
Prediction Models ◽  
Road Traffic ◽  
Traffic Noise ◽  
Machine Learning Techniques ◽  
Coefficient Of Determination ◽  
Road Traffic Noise ◽  
Noise Prediction ◽  
Volume Percentage

A vehicular road traffic noise prediction methodology based on machine learning techniques has been presented. The road traffic parameters that have been considered are traffic volume, percentage of heavy vehicles, honking occurrences and the equivalent continuous sound pressure level. Leq A method to include the honking effect in the traffic noise prediction has been illustrated. The techniques that have been used for the prediction of traffic noise are decision trees, random forests, generalized linear models and artificial neural networks. The results obtained by using these methods have been compared on the basis of mean square error, correlation coefficient, coefficient of determination and accuracy. It has been observed that honking is an important parameter and contributes to the overall traffic noise, especially in congested Indian road traffic conditions. The effects of honking noise on the human health cannot be ignored and it should be included as a parameter in the future traffic noise prediction models.

scholarly journals Road Noise Levels in Urban Environment Compared to Specification Limits. The Case of the City of Larissa, Greece

2020 ◽  
Author(s):  
Emmanouil A. Papadimitriou ◽  
Grigorios P. Papageorgiou ◽  
Nikolaos Alamanis ◽  
Theodosia-Niki Diakosavva
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
Road Noise ◽  
Greek City ◽  
Limit Values ◽  
High Noise ◽  
Specification Limits ◽  
The City

Greece, as well as other developed countries, is facing the growing problem of road traffic noise. It stands for a severe problem in the urban areas of the country, including the city of Larissa. The root cause is the huge increase in traffic volume and the lack of adequate urban infrastructure planning. Estimation of the level of road traffic noise is usually conducted using acoustic meters. It is widely accepted that most of the cities’ population is exposed to high noise levels due to controversial traffic capacity. Moreover, high noise levels are strongly related to phycological and neurological diseases. Thus, it is of utmost importance, the road noise levels to be lower than dictated by relevant specification limits. To develop better noise-environment policies, relative research should focus on the measurement of in-situ noise levels, so as appropriate for each case corrective measures to be taken. The present paper examines the noise levels of a center road of the 5th Greek city, in terms of population, compared to worldwide adopted noise specification limits. The clear aim stands for finding the percentage of road noise that exceeds commonly accepted threshold values, namely limit values of European Union and World Health Organization. The results of this research strongly indicate that measured noise values override upper limit values in a certain extent.

scholarly journals The Impact of Thin Asphalt Layers as a Road Traffic Noise Intervention in an Urban Environment

2021 ◽  
Vol 13 (22) ◽  
pp. 12561
Author(s):  
Ablenya Grangeiro de Barros ◽  
Jarl K. Kampen ◽  
Cedric Vuye
Keyword(s):  
Noise Exposure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Low Noise ◽  
Urban Environments ◽  
Comfort Level ◽  
Road Traffic Noise ◽  
Acoustic Measurements ◽  
Noise Levels ◽  
The Impact

Low-noise thin asphalt layers (TALs) are a feasible solution to mitigate road traffic noise in urban environments. Nevertheless, the impacts of this type of noise intervention are reported mostly regarding noise levels, while non-acoustic aspects influencing the population perception are still little-known. This study investigates the implementation of TALs in two streets of Antwerp, Belgium. The effectiveness of the intervention was measured via noise modelling and acoustic measurements of road traffic noise. A reduction of 2.8 dB in noise exposure was observed in Lden and Lnight, while SPB measurements showed decreases up to 5.2 dB on the roadside. The subjective impacts of the TALs were evaluated via self-administered surveys and compared to results from control streets. The annoyance indicators were positively impacted by the TALs implementation, resulting in annoyance levels similar or lower than in the control streets. The TALs did not impact the reported physical complaints, sleep quality, and comfort level to perform activities.

Local determinants of road traffic noise levels versus determinants of air pollution levels in a Mediterranean city

2011 ◽  
Vol 111 (1) ◽  
pp. 177-183 ◽  
Author(s):  
Maria Foraster ◽  
Alexandre Deltell ◽  
Xavier Basagaña ◽  
Mercedes Medina-Ramón ◽  
Inmaculada Aguilera ◽  
...  
Keyword(s):  
Air Pollution ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
Pollution Levels ◽  
Mediterranean City
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