Traffic Noise Investigation for Regression Analysis Percentile at Different Sound Levels (L10) (L50) (L90)

Traffic noise is a typical area of conflict between individual mobility needs and legitimate societal aspirations for quieter lifestyles. With millions of Indian citizens suffering from unacceptable levels of noise, much of it caused by the transport sector as a whole – there is a clear need for India to take a driving role in promoting targeted legislation for progress. Traffic noise from highways creates problems for surrounding areas, especially when there are high traffic volumes and high speeds. In India, the transportation sector is growing rapidly and number of vehicles on Indian roads is increasing at a very fast rate. This has led to overcrowded roads and pollution. So, a need is being felt to develop a noise prediction model suitable for Indian conditions. The noise measurement descriptors recorded were Leq, L10, L50 and L90. Sound level meter (CESVA SC 310) was used for these measurements. The noise parameters measured were traffic volume for near side, traffic volume for far side, mean speed on near side and mean speed on far side. The Correlation regression analysis applied for traffic noise modeling in the present study. In regression analysis, the values of R2 were above 0.70 for all descriptors and the percentage error varied between ±5%. In the Correlation test, the most impacting factors affecting sound descriptors were found and ranked in order.