Abstract
On the basis of measuring the traffic noise data of Shenyang urban sub road in Shenyang, this paper starts with the speed and traffic flow, analyzes the data by SPSS statistical analysis software, and uses linear fitting, statistical analysis and other methods. The two factors were analyzed, and the conclusions were drawn: First, the traffic noise and speed are approximately linear in a certain speed range, that is to say, the noise value increases with the increase of the speed of the vehicle. Second, the logarithmic positive correlation between traffic flow and traffic noise is that, with the increase of flow rate, the noise value at the initial stage increased significantly. Then when traffic reaches to a certain number, the increasing trend is not very obvious. And the road traffic noise model was established by using Cadna/A software, and the spatial distribution of road traffic noise was analyzed by the software.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Reference
Li F, Li Q, Guan X (2009) The influence of highway traffic noise on the environment and its treatment measures. J Hunan Agric Univ 35(1):44–47
Feng X (2014) Research on the relationship between traffic flow factor and road traffic noise. Master’s thesis, Northeast Forestry University, Harbin
Shi B, Hu X, Qiu R (2016) Influence factors and control strategies of urban traffic noise. J Putian Univ 23(5):105–108
Li L, Yuan X (2012) Discussion on highway traffic noise control measures. Sichuan Environ 31(5):140–142
Hu Y (2008) Study on the relationship between traffic noise and traffic flow state. J Transp Eng Inf 6(1):6–9
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Liu, W., Guan, X., Xing, Y., Wang, J., Cai, W. (2019). Analysis of the Influence of Urban Road Traffic Flow Parameters on the Acoustic Environment. In: Wang, W., Bengler, K., Jiang, X. (eds) Green Intelligent Transportation Systems. GITSS 2017. Lecture Notes in Electrical Engineering, vol 503. Springer, Singapore. https://doi.org/10.1007/978-981-13-0302-9_45
Download citation
DOI: https://doi.org/10.1007/978-981-13-0302-9_45
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0301-2
Online ISBN: 978-981-13-0302-9
eBook Packages: EngineeringEngineering (R0)