scholarly journals Reduction in Calculated Uncertainty of a Noise Map by Improving the Traffic Model Data Through Two Phases

2011 ◽  
Vol 97 (5) ◽  
pp. 761-768 ◽  
Author(s):  
M. Ausejo ◽  
M. Recuero ◽  
C. Asensio ◽  
I. Pavón
Keyword(s):  
Input Data ◽  
Road Traffic ◽  
Traffic Noise ◽  
Traffic Model ◽  
Road Traffic Noise ◽  
Noise Emission ◽  
The Road ◽  
Palma De Mallorca ◽  
Two Phases ◽  
Noise Map

The influence of applying European default traffic values to the making of a noise map was evaluated in a typical environment like Palma de Mallorca. To assess these default traffic values, a first model has been created and compared with measured noise levels. Subsequently a second traffic model, improving the input data used for the first one, has been created and validated according to the deviations. Different methodologies were also examined for collecting model input data that would be of higher quality, by analysing the improvement generated in the reduction in the uncertainty of the noise map introduced by the road traffic noise emission.

scholarly journals Rapid Modeling Method for Road Traffic Noise Sources: A case study in Beijing

Noise Mapping ◽  
2015 ◽  
Vol 2 (1) ◽  
Author(s):  
L. Zhu ◽  
X. Li ◽  
C. Jiang ◽  
L. Liu ◽  
R. Wu ◽  
...  
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Modeling Method ◽  
Model Parameters ◽  
Road Traffic Noise ◽  
Emission Model ◽  
Noise Sources ◽  
The Road ◽  
The Mean ◽  
Rapid Modeling

AbstractBased on the local road traffic conditions in Beijing, China, this contribution proposes a rapid modeling method for road traffic noise sources. Since establishing the standardized experiment fields are expensive, real roads are used to determine the road traffic noise emission model in the method. Due to the similarity in the urban structures in China and Japan, this paper uses the ASJ- 2013 model as a template and replaces its model parameters with the ones output by an optimization program which minimizes the sum of absolute errors between the predicted and the measured LAeq. Real road experiments are conducted to verify the effectiveness and feasibility of the modeling method. The mean error of the model deduced by the method and the ASJ-2013 model is respectively 0.4 dB and 2.6 dB, and the mean absolute error of the two models is respectively 1.1 dB and 2.6 dB. The results of the real road experiments show that the road traffic noise sources deduced by the method are more accurate to conduct local noise prediction than those of other models.

Social survey on the road traffic noise effect on the quality of life in Moroccan cities

2008 ◽  
Vol 123 (5) ◽  
pp. 3811-3811
Author(s):  
Weam Kharbaoui ◽  
Mohammed Garoum ◽  
Abdelaziz Bahoussa ◽  
Mohammed Rhachi
Keyword(s):  
Quality Of Life ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Social Survey ◽  
Noise Effect ◽  
The Road ◽  
On The Road

Creation of Theoretical Road Traffic Noise Model with the Help of GIS

2017 ◽  
Author(s):  
Kinga Szopinska
Keyword(s):  
Urban Space ◽  
Road Traffic ◽  
Traffic Noise ◽  
Noise Model ◽  
Road Traffic Noise ◽  
The European Union ◽  
Noise Emission ◽  
Starting Point ◽  
Information Layer ◽  
Gis Data

Road traffic noise, as a form of environmental pollution, is an important element causing discomfort among inhabitants and leading to the emergence of noise nuisance influencing the shaping of urban space. The basic tool in combating noise is a Strategic Noise Map (SNM), which, understood as a system, constitutes an element of a city’s information layer. The system, illustrating the noise situation within a city, is prepared by means of a calculationmeasurement method using specialized computer programs. The assessment of road traffic noise begins by defining the amount of noise emissions coming from acoustically-homogenous sections (emission map), and ends with determining the extent of noise propagation in urban space (immission map). The above process is based on the analysis of actual input data describing, in a detailed manner, the analyzed road infrastructure in terms of the characteristics of the road section, information on the volume and type of traffic, and data on the organization of traffic. Under such extensive analysis of the condition of the environment, it is appropriate to apply GIS data as a methodological basis for creating SNMs. GIS data make it possible to unify the rules for collecting and archiving values characterizing the condition of the environment, as well as parameters influencing the level of noise. The aim of work is create a theoretical road traffic noise model with the help of GIS. The scope of information in attribute tables of acoustically-homogenous road sections comprising a GIS thematic layer was described in detail. The above information are the basis for generating digital road traffic noise emission maps as well as being the starting point for assessing road traffic noise in the area of a city in the form of immission maps. The article additionally analyzes the results of data derived from the first phase of noise mapping in Europe, as well as familiarizing the reader with the procedure of modelling road traffic noise emission in accordance with the CNOSSOS-EU which will become binding as of 31 December 2018 throughout the European Union, and which was introduced by the provisions of the new noise directive – Directive 2015/996 of 19 May 2015.

scholarly journals Traffic-related Noise at Roadside Schools: Assessment and Prediction in Urban Setting

2021 ◽  
Vol 22 (2) ◽  
pp. 178-189
Author(s):  
Mila Dirgawati ◽  
Gita Nur Apriani ◽  
Astien Arsten Asyari ◽  
R. Triyogo
Keyword(s):  
Noise Level ◽  
Road Traffic ◽  
Traffic Noise ◽  
Urban Setting ◽  
National Standard ◽  
Road Traffic Noise ◽  
Heavy Vehicles ◽  
The Road ◽  
Total Vehicle ◽  
Data Volume

ABSTRAK Kebisingan lalu lintas adalah salah satu ancaman bagi kesehatan masyarakat perkotaan. Paparan bising memberikan efek kesehatan jangka pendek dan panjang, dan efeknya berpotensi lebih buruk pada anak-anak yang belajar di sekolah pinggir jalan. Penelitian ini bertujuan untuk mengkarakterisasi kebisingan lalu lintas jalan di sekolah-sekolah yang terletak di jalan-jalan utama di Bandung, Indonesia serta memberikan rekomendasi mitigasi dan adaptasi untuk pengendalian kebisingan. Kebisingan lalu lintas diperoleh di dua sekolah pinggir jalan terletak di dua jalan utama (Jalan Suci dan Djuanda), beserta data volume dan komposisi lalu lintas, serta kecepatan kendaraan. Pengukuran dilakukan antara jam sekolah selama satu hari yang mewakili lokasi trotoar jalan, depan sekolah, dan halaman sekolah. Parameter tingkat kebisingan yang penting (Leq, L10, L50, L90) diukur, dan dilakukan analisis korelasi antara masing-masing parameter kebisingan. Model CoRTN digunakan untuk memprediksi kebisingan lalu lintas pada jarak tertentu dari jalan raya. Sepeda motor merupakan jenis kendaraan dominan secara berturut 79,1% dan 67,1% dari total volume kendaraan di ruas jalan Suci dan Djuanda. Kendaraan berat menyumbang <1%. Mayoritas kebisingan lalu lintas yang diukur sebagai Leq, L10, L50, L90 melebihi batas maksimum untuk pinggir jalan dan zona sekolah menurut standar internasional dan nasional <55 dBA). Model tersebut berkinerja lebih baik di ruas jalan Djuanda daripada Suci. Jumlah lokasi dan waktu pengukuran yang lebih banyak dapat memberikan penilaian paparan tingkat kebisingan lalu lintas yang lebih baik dengan menggunakan model CoRTN. Hasil penelitian ini diharapkan dapat menjadi masukan kebijakan berbasis pengetahuan bagi pemerintah kota dan lembaga untuk mengurangi dampak bising bagi anak didik. Kata kunci: kebisingan lalu lintas jalan, tingkat kebisingan, Model CoRTN   ABSTRACT Noise from road traffic is one of the most ubiquitous threats to the public health in urban setting. Its exposures have proven short-and long-term health effects. and potentially worse for vulnerable population such as children studying at roadside schools. This study aimed to characterize the road traffic noise at schools located at major roads in Bandung, Indonesia. Traffic noise were obtained at 2 roadside schools located at two major roads (Suci and Djuanda roads), along with data on traffic volume and composition, and vehicles speed. The measurement was conducted between school hours during one day-time only at locations representative of roadside, front of the schools, and schoolyard. Important noise level parameters such as Leq, L10, L50, L90 were recorded, and correlation analysis between each parameter was conducted. The CoRTN model was then applied to predict the traffic noise at particular distances from the road. Motorcycles were the predominant vehicle type on both road segments: 79.1% and 67.1% of the total vehicle volume on Suci on Djuanda segments, respectively.  Conversely, heavy vehicles accounted <1%. The majority of measured traffic noise determined as Leq, L10, L50, L90 exceeded the maximum limit for roadside and school zone set by the international and national standard (>55 dBA). The model performed better in Djuanda road segment than in Suci segment. More measurement locations and time could provide better assessment of exposure to traffic noise levels at roadside schools using the CoRTN model. Keywords: road traffic noise, noise level, CoRTN model

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