Volume 5, 2021
|Number of page(s)||14|
|Published online||14 October 2021|
Technical & Applied Article
A simulation of traffic noise emissions at a roundabout based on a cellular automaton model
School of Automotive and Transportation Engineering, GuangDong Polytechnic Normal University, 510665 Guangzhou, PR China
2 Research Center of Intelligent Transport Systems, School of Intelligent Systems Engineering, Sun Yat-sen University, 510006 Guangzhou, PR China
* Corresponding author: email@example.com
Accepted: 17 September 2021
The calculation and evaluation of traffic noise is an important task in urban road design. Roundabouts are a common form of urban road intersection. The complexity of traffic operations makes the calculation of traffic noise near a roundabout challenging. To explore traffic noise at roundabouts, a cellular automaton traffic flow model for a two-lane roundabout is established. Based on this model, a dynamic simulation method for traffic noise at roundabouts is proposed. The traffic operation and noise emissions at a roundabout are simulated. The vehicle speed distribution and traffic noise distribution at the roundabout are analysed, and the relationship between the traffic volume and sound power level of the cells is discussed. Finally, the proposed method is compared with existing traffic noise models, and the accuracy and efficiency of the proposed method are verified. The results of this paper show that the speed distribution and noise emission distribution at the roundabout are not uniform. When the traffic volume increases to saturation, the noise emission on the ring road will not keep increasing, and the sound power level of the cells on the inner ring is approximately 2 dBA higher than that of the outer ring. The methods and results in this paper may be valuable for road traffic design and noise control.
Key words: Roundabout / Cellular automaton model / Traffic noise / Dynamic simulation
© The Authors, Published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://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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