This research aimed at modeling interrupted flow traffic noise at a signalized intersection. In this study, a new approach has been used with SPSS and Arc GIS with urban road traffic noise. The measured parameters of noise include noise equivalent level, volume of light vehicles, heavy vehicles and time mean speed. The results showed that the Spearman correlation coefficient between the interface and the level of the noise at morning, evening and total time were 0.241, 0.35 and 0.45. The spearman correlation coefficient between the interface of the buildings and the intersection of all types of vehicles passing through the morning, evening and total time equal to 0.534, 0.328 and 0.409. The results showed that noise level can be predicted through the speed variables of the vehicles, the volume of vehicles passing heavy and the use of land use of buildings. According to the results and the noise maps for the modeling noise of the estimated coefficients from the equation, it can be found that in building highway in urban, closer look on internationally acting Green Building Labels and noise protection is seen as an important part of the social sustainability aspects of a building.

In this study, a new approach has been used with SPSS and MATLAB analysis to study urban road traffic noise distribution mapping, to obtain the representative road traffic noise maps. The observation has been performed at a high traffic highway. The factors influencing noise level (traffic, road width, slope, and residential or administrative–commercial land) use were surveyed and recorded for each point and their local and time dependencies were computed. According to the analysis, the maximum value of goodness of fit index for the traffic and noise level relationship was 0.64, followed by 0.489 for the percentage of residential land use. The result of this study showed that the vehicle speed, width of the road, and the land use can affect different sound levels emitted by moving vehicles on road. The model predicts that by increasing one vehicle per hour, an increase in noise level by 0.002 dB will happen.

To encourage the society to choose the public transportation system, it should comfort and satisfy people. Noise pollution in urban transportation systems is a risk that can endanger passenger health and affect their use of public transportation. Hence, this study investigates the effect of noise pollution on users' satisfaction of Tehran Metro line 7 using a sound level meter to measure noise pollution in four stations, namely Sanat Square, Tarbiat Modarres University, Shahid Navvab Safavi, and Rudaki. The data was analyzed using noise measurement, and noise pollution is compared at four stations with noise contour maps.