Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method


Autoria(s): Zhang, Chen; He, Jie; Wang, Zhengrong; Yin, Rongrong; King, Mark
Data(s)

01/01/2013

Resumo

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sizedtrucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/65148/

Relação

http://eprints.qut.edu.au/65148/1/Zhang_He_et_al_TRB_13-2016.pdf

Zhang, Chen, He, Jie, Wang, Zhengrong, Yin, Rongrong, & King, Mark (2013) Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method. In Transportation Research Board 92nd Annual Meeting, 13-17 January 2013, Washington, D.C.

Direitos

Copyright 2013 Please consult the authors

Fonte

Centre for Accident Research & Road Safety - Qld (CARRS-Q); Faculty of Health; Institute of Health and Biomedical Innovation; School of Psychology & Counselling

Palavras-Chave #Freeway #Traffic noise #Traffic microsimulation #Noise prediction
Tipo

Conference Paper