The main objective of this study is to evaluate the noise generated due to tyre-pavement surface interaction for various modes and to develop a noise prediction model for each mode by taking into account various factors affecting the noise generation. Eight asphalt pavement and four cement concrete pavement stretches were selected for measurement of the noise. Tyre-pavement interaction noise was measured using controlled pass-by method by eliminating the noise generated from engine and the vehicle exhaust systems. Noise levels were measured as a function of vehicle type, vehicle speed, loading condition, pavement temperature, direction of wind, and type of pavement. The influence of each of these variables are analyzed and quantified in this paper. The vehicle speed is found to be the most significant variable affecting the noise generated due to tyre-pavement surface interaction followed by other variables. Further, individual noise prediction models are developed for each mode in each survey location and a combined tyre-pavement interaction noise model is developed for each mode for both asphalt and cement concrete pavements.

AbstractThis paper presents a study conducted at major rotaries for quantifying the traffic noise levels by considering the vehicle volume and their respective honking as governing parameters for heterogeneous traffic. Traffic volume and traffic noise data was collected using a digital video camera and a class 1 sound level meter, respectively. The traffic noise data was analysed using noise tools for identifying the noise level variation. The data collected was subjected to statistical analysis for light, medium and heavy vehicles, and their contribution towards noise levels is proven to be effective with the forthright fact that, heavy vehicles and their corresponding honking were majorly affecting the equivalent noise level compared to other vehicular proportion. An equivalent noise level [LAeq (dB)] rise of 2 to 6 dB (A) is solely caused by heavy vehicles, which is an important observation to be considered for traffic noise analysis at the rotaries. Based on the obtained results from one of the rotaries, noise prediction model is developed for estimating the LAeq (dB), which is able to predict the noise levels with good precision when validated with the data collected at second rotary intersection for different vehicle volumes.

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).

No abstract

Vehicle speeds frequently fluctuate due to the prevailing heterogeneous traffic conditions on Indian roads. Accordingly, traffic noise levels are affected by different noise sources that depend on various vehicular and roadway characteristics. In order to simulate the actual vehicle noise generation at the possible speeds on Indian roads, an integrated method has been developed in this study to quantify the engine and tire–road noise levels. The governing parameters considered for the pass-by noise quantification include vehicle speed, type of pavement and gear shift/gear transmission. The measured A-weighted noise levels [LAmax (dB)] revealed that tire–road noise levels increased with the rise in vehicle speeds irrespective of the vehicle type and type of the pavement. Further, the tire–road noise levels quantified through the new methodology closely matched the noise levels measured by the standard coast-by method. The cross-over speeds for engine propulsion noise and tire–road interaction noise occur at much lower speeds on the cement concrete pavements compared to the asphalt pavements. On a decisive note, the perspective of measuring the roadside noise levels coupled with an engine propulsion noise measurement as reported in this study is first of its kind and can be used for noise measurements on critical urban roads by priming with the conventional pass-by methods.