Traffic Noise Prediction Model for Mohammed Al-Qassim Freeway in Baghdad Environment

Abstract

Noise is one of the environmental pollutants that is encountered in daily life. While the rapid increase in the number of vehicles in Iraq, the noise and air pollution rates are increased. In the present study, a freeway traffic noise prediction model for Mohammad AlQassim Freeway in Baghdad city condition is developed using multiple regression analysis techniques. Traffic volume and percent of heavy vehicles along the freeway were measured manually and average sound level (Leq) dBA, was measured using (Victor 824 A Digital Sound Level Meter) instrument. The collected data had been analyzed, the model was developed and considered satisfactory as it gives accepted results, with an R2 value of (0.762). The coefficient of correlation R2 value for observation and estimated noise level by RNM is (0.777).