Highway traffic noise prediction based on GIS

2014 ◽  
Author(s):  
Jianghua Zhao ◽  
Qiming Qin
Keyword(s):  
Traffic Noise ◽  
Noise Prediction ◽  
Highway Traffic

Highway traffic noise prediction using method fully compliant with ISO 9613: comparison with measurements

2004 ◽  
Vol 65 (9) ◽  
pp. 883-892 ◽  
Author(s):  
Dae Seung Cho ◽  
Jin Hyeong Kim ◽  
Tae Muk Choi ◽  
Byung Hee Kim ◽  
Douglas Manvell
Keyword(s):  
Traffic Noise ◽  
Noise Prediction ◽  
Highway Traffic

Assessment and improvement of a highway traffic noise prediction model with Leq(20s) as the basic vehicular noise

2015 ◽  
Vol 97 ◽  
pp. 78-83 ◽  
Author(s):  
Jianqiang Zhao ◽  
Zhenzhen Ding ◽  
Bo Hu ◽  
Ying Chen ◽  
Wenjuan Yang
Keyword(s):  
Prediction Model ◽  
Traffic Noise ◽  
Noise Prediction ◽  
Highway Traffic

scholarly journals Modelling of Noise Pollution Due to Heterogeneous Highway Traffic in India

2019 ◽  
Vol 20 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Aditya Kamineni ◽  
Sunil Kumar Duda ◽  
Venkaiah Chowdary ◽  
C.S.R.K. Prasad
Keyword(s):  
Traffic Noise ◽  
Noise Pollution ◽  
Heterogeneous Traffic ◽  
Noise Prediction ◽  
Highway Traffic ◽  
Noise Levels ◽  
Speed Variation ◽  
Proposed Model ◽  
Traffic Speed ◽  
The Difference

Abstract Compared to homogeneous traffic flow, traffic speed variation is drastic with the involvement of heterogeneity. With an intent of studying the negative upshot of fluctuating speeds of heterogeneous traffic on the environment, the current paper is the outcome of the research done on various highways located in the states of Andhra Pradesh and Telangana in India, with an objective of developing a comprehensive noise prediction model by taking into account the traffic and roadway factors. Quantified noise levels [Leq (dBA) and L10 (dBA)] revealed that for the traffic speed variation of 10 to 95 kmph, the traffic noise levels were significantly affected by the variations in the proportion of the vehicle. On a specific note, the proposed model can be effectively used for the highway traffic noise prediction especially for the heterogeneous traffic, as the difference between the measured and predicted noise levels are within 1 to 10 dB (A).

Road Traffic Noise Prediction Model

2012 ◽  
Vol 3 (4) ◽  
pp. 110-112
Author(s):  
Rahul Singh ◽  
◽  
Parveen Bawa ◽  
Ranjan Kumar Thakur
Keyword(s):  
Prediction Model ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Prediction

Application of the Boundary Element Method and Modal Analysis to Tire Acoustics Problems

1993 ◽  
Vol 21 (2) ◽  
pp. 66-90 ◽  
Author(s):  
Y. Nakajima ◽  
Y. Inoue ◽  
H. Ogawa
Keyword(s):  
Finite Element ◽  
Boundary Element Method ◽  
Boundary Element ◽  
Acoustic Radiation ◽  
Traffic Noise ◽  
Noise Prediction ◽  
Prediction System ◽  
Tire Noise ◽  
Acoustic Contribution ◽  
Element Method

Abstract Road traffic noise needs to be reduced, because traffic volume is increasing every year. The noise generated from a tire is becoming one of the dominant sources in the total traffic noise because the engine noise is constantly being reduced by the vehicle manufacturers. Although the acoustic intensity measurement technology has been enhanced by the recent developments in digital measurement techniques, repetitive measurements are necessary to find effective ways for noise control. Hence, a simulation method to predict generated noise is required to replace the time-consuming experiments. The boundary element method (BEM) is applied to predict the acoustic radiation caused by the vibration of a tire sidewall and a tire noise prediction system is developed. The BEM requires the geometry and the modal characteristics of a tire which are provided by an experiment or the finite element method (FEM). Since the finite element procedure is applied to the prediction of modal characteristics in a tire noise prediction system, the acoustic pressure can be predicted without any measurements. Furthermore, the acoustic contribution analysis obtained from the post-processing of the predicted results is very helpful to know where and how the design change affects the acoustic radiation. The predictability of this system is verified by measurements and the acoustic contribution analysis is applied to tire noise control.

SPEED DISTRIBUTION INFLUENCE IN ROAD TRAFFIC NOISE PREDICTION

2013 ◽  
Vol 12 (3) ◽  
pp. 493-501 ◽  
Author(s):  
Gerardo Iannone ◽  
Claudio Guarnaccia ◽  
Joseph Quartieri
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Prediction ◽  
Speed Distribution

scholarly journals Application of Machine Learning to Include Honking Effect in Vehicular Traffic Noise Prediction

2021 ◽  
Vol 11 (13) ◽  
pp. 6030
Author(s):  
Daljeet Singh ◽  
Antonella B. Francavilla ◽  
Simona Mancini ◽  
Claudio Guarnaccia
Keyword(s):  
Machine Learning ◽  
Linear Models ◽  
Prediction Models ◽  
Road Traffic ◽  
Traffic Noise ◽  
Machine Learning Techniques ◽  
Coefficient Of Determination ◽  
Road Traffic Noise ◽  
Noise Prediction ◽  
Volume Percentage

A vehicular road traffic noise prediction methodology based on machine learning techniques has been presented. The road traffic parameters that have been considered are traffic volume, percentage of heavy vehicles, honking occurrences and the equivalent continuous sound pressure level. Leq A method to include the honking effect in the traffic noise prediction has been illustrated. The techniques that have been used for the prediction of traffic noise are decision trees, random forests, generalized linear models and artificial neural networks. The results obtained by using these methods have been compared on the basis of mean square error, correlation coefficient, coefficient of determination and accuracy. It has been observed that honking is an important parameter and contributes to the overall traffic noise, especially in congested Indian road traffic conditions. The effects of honking noise on the human health cannot be ignored and it should be included as a parameter in the future traffic noise prediction models.

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