Comprehensive approach for the development of traffic noise prediction model for Jaipur city.

The main objective of the present study was to develop an empirical noise prediction model for the evaluation of equivalent noise level (Leq) in terms of equivalent traffic density number under heterogeneous traffic flow conditions. Ten commercial road networks are selected for monitoring and modeling. A new factor, i.e., equivalent number of light vehicles (EqLv) and for heavy vehicles (EqHv), has been used for evaluating the equivalent traffic density for each class of vehicles, and correlation graphs are plotted between equivalent traffic density with respect to EqLv and EqHv and observed equivalent noise level [Leq(o)] for the calculation of equivalent noise levels in terms of light vehicles [Leq(Lv)] and heavy vehicles [Leq(Hv)] for different identified locations as well as for the entire city. Furthermore, regression noise prediction equations have been developed between Leq(o), Leq(Lv), and Leq(Hv). After comparison of the results, it can be depicted that the light motor vehicles are the main source of noise pollution in the city and gives significantly higher correlation coefficient values. This model can be applied for the calculation of road traffic noise under interrupted traffic flow conditions in urban areas of Indian cities.