Traffic Noise Prediction for Delhi-NCR using Multiple RegressionModelling Approach

Suman Mann; Gyanendra Singh

doi:10.57159/gadl.jcmm.2.6.230104

Authors

Suman Mann Department of Civil Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana, India 131039
Gyanendra Singh Department of Civil Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana, India 131039

DOI:

https://doi.org/10.57159/gadl.jcmm.2.6.230104

Keywords:

Traffic Noise Prediction Model, Noise Pollution, Significant Variables, Multiple Regression Modelling

Abstract

Traffic noise prediction models are crucial for designing highways to implement preventive measures against traffic noise pollution by analyzing future trends. This study aims to identify the traffic, road geometrical, and environmental parameters that escalate traffic noise pollution, enabling rectification of influencing factors and enhancement of strategies to reduce this pollution. A traffic noise prediction model was developed for the highways of Delhi-NCR using the Multiple Regression approach, incorporating various traffic, geometric, and environmental parameters. Statistical analysis was conducted, and the model was formulated based on data collected from 31 sampling stations on two major Delhi highways. Significant variables identified include the number of lanes, average building height, international roughness index, temperature, wind speed, and humidity. The model’s validity is affirmed by a coefficient of determination R2 = 0.75, indicating a good fit.

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