MATEC Web Conf.
Volume 254, 2019XXIII Polish-Slovak Scientific Conference on Machine Modelling and Simulations (MMS 2018)
|Number of page(s)||8|
|Section||Modelling and Simulation, Structural Optimization|
|Published online||15 January 2019|
Variability analysis of urban traffic noise measurands
Kielce University of Technology, Faculty of Mechatronics and Mechanical Engineering, Aleja Tysiąclecia Państwa Polskiego 7, 25314 Kielce Poland
2 Kielce University of Technology, Faculty of Environmental, Geomatic and Energy Engineering, Aleja Tysiąclecia Państwa Polskiego 7, 25314 Kielce Poland
3 University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia
* Corresponding author: firstname.lastname@example.org
The paper presents the analysis results of measurements recorded by road traffic and noise monitoring station. The station is located in a medium size town in Poland (Kielce) situated at the national road to Cracow. The traffic flow was measured over the period between January and December 2013 for twenty four hours a day. Statistical analysis methods were used to determine the variability and uncertainty of the results. The measurements from two vehicular lanes running towards the town and two lanes running towards Cracow were analyzed. The variability of the results was described using parameters such as the coefficient of variation and positional variation. The results of vehicle traffic measurements were used to simulate changes in the noise measurand variation within 1-hour intervals. The Nordic Prediction Method was used for this purpose. It was found that in most cases, the distribution of the tested variable was not normal. Box plots were used to assess whether outliers data occurred in the recorded results. The variability of noise and type A uncertainty was evaluated.
Key words: traffic noise / vehicles flow / predictive models
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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