Issue |
MATEC Web Conf.
Volume 203, 2018
International Conference on Civil, Offshore & Environmental Engineering 2018 (ICCOEE 2018)
|
|
---|---|---|
Article Number | 03002 | |
Number of page(s) | 9 | |
Section | Environmental Engineering | |
DOI | https://doi.org/10.1051/matecconf/201820303002 | |
Published online | 17 September 2018 |
An Empirical Model of Road Traffic Noise on Heterogeneous Traffic Situation
1
Senior Lecturer, Department of Environmental Engineering, Universitas Hasanuddin,
Indonesia
2
Associate Professor, Department of Civil Engineering, Universitas Hasanuddin,
Indonesia
* Corresponding author: muraliahustim@yahoo.com
The motorcycle domination on heterogeneous traffic situation in many cities in developing countries including Indonesia leads to the decreasing of environment qualities such noise pollution. Regarding the road traffic noise (RTN) pollution, this paper attempts to develop an empirical model for a RTN prediction model. The model based on a motorcycle unit as reference unit to consider flow rate of the road traffic which dominated by motorcycles. The study collected the RTN data such volume of each vehicle types, i.e., motorcycle; light vehicle; and high vehicle, and the noise level on the forty arterial roads in Makassar, Indonesia. The survey methods based on the traffic count method and the measurement noise level using a video camera and a sound level meter, respectively. We collected data during ten minutes of each one-hour period of each road. The empirical relationship models between the noise level and the traffic volume based on the motorcycle unit were developed using various types of regression models. The results showed that the polynomial model is more significant than the other models. We expected that the model provides a basic RTN prediction model in order to simulate some measures of the traffic management system in reducing the RTN level in Makassar City.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (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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