Traffic Noise Investigation and Modelling for Signalized Intersections - Singh, Jaskaran (My University, 2015)
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 present work represents a traffic noise prediction model where the acoustic analysis of vehicular traffic noise considered at a signalized intersection on an urban road in Patiala City (Punjab). The numbers of sets of data were recorded for 1 hour duration at different time and dates in a random manner in order to account for statistical temporal variations in traffic flow 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 regression analysis, Correlation test, t-test and Frequency analysis for 1/1 Octave Band were 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. The t-test expressed no significant difference between the two and ‘t-critical’ value was greater than ‘t-statistical’. In frequency analysis for 1/1 octave band, results indicated that 125, 250, 500 and 1k Hz frequencies were most influenced in sound level spectrum.
M.E. (Production Engineering)
Keywords: Traffic Noise Modelling; Intersection or Traffic Lights; Urban Traffic Noise; Prediction Model