Heterogeneous road traffic noise modeling at mid-block sections of mid-sized city in India

Abstract

This study attempted to develop a computer-based software for monitoring the traffic noise under heterogeneous traffic condition at the morning peak (MP), off peak (OP), and evening peak (EP) periods of mid-block sections of mid-sized city in India. Traffic noise dataset of 776 (LA_eq, 1hr) were collected from 23 locations of Gorakhpur mid-sized city in the state of Uttar Pradesh in India. K-nearest neighbor (K-NN) algorithm was adopted for traffic noise prediction modeling. Moreover, principal component analysis (PCA) technique was used for the dimensionality reduction and to overcome the problem of multi-collinearity. The developed model exhibits R² value of 0.81, 0.78, and 0.77 in the MP, OP, and EP, respectively, for L_eq, and a value of 0.86, 0.80, and 0.84 for L₁₀. The proposed model can predict more than 94% observations within an accuracy of ±3%. Ultimately, a user-friendly noise level calculator named "Traffic Noise Prediction Calculator for Heterogeneous Traffic (TNPC-H)" was developed for the benefit of field engineers and policy planners.

Keywords: Heterogeneous road traffic noise modeling; K-nearest neighbor; Principal component analysis; Traffic Noise Prediction Calculator.