Evaluation of Federal Highway Administration’s Traffic Noise Model for Pavements in Qatar

Abstract

Traffic noise is an irritating problem especially for residents near major transportation corridors. It’s in the interest of transportation agencies to check the noise level to develop measures to reduce noise if it exceeds the allowable threshold. This process requires measuring noise level along roadways nearby the residential areas. Alternatively, computer models can be used to study and analyse the noise level which save a lot of resources and enable transportation agencies to take countermeasures when planning new roadways near residential areas. The Federal Highway Traffic Noise Model (TNM) is a computer program that is used to analyse and model traffic noise. The vehicle speed, traffic volume and road geometry are used to predict noise propagation in open far-field environment and determine noise attenuation from noise barriers. In TNMv2.5, pavement and ground type is included but it does not account for noise propagation medium that is random and continuously evolving. In this paper, Federal Highway Administration’s (FHWA) TNMv2.5 was evaluated to determine the accuracy of this model in the State of Qatar. During noise measurement, traffic volume and terrain geometry were used to predict the noise levels by using TNMv2.5. The predicted noise levels were compared with the observed levels for checking the accuracy of this model for predicting the future noise levels of roadways. The predicted noise levels were compared with noise levels measured at 19 locations at nine sites throughout the State of Qatar. For typical pavements in Qatar, the TNMv2.5 is overpredicting approximately 2.3 dB for high traffic, whereas it is underpredicting on an average 1.9 dB for low traffic volume. Although the number of test locations is relatively small, it was still established that the results obtained by FHWA’s TNMv2.5 model were within the reasonable range of the observed noise levels for pavements in the State of Qatar. This demonstrated that the TNMv2.5 model was suitable for predicting noise level for pavements in Qatar.