The aim of the project is to implement an Intelligent Transport System (ITS), which is innovative compared to existing systems and can optimise traffic while minimising the noise impact on residents. Current systems implement traffic distribution decisions based on traffic conditions, with the aim of avoiding congestion and facilitating traffic flow in urban areas. However, they are currently unable to take into account the acoustic impact on the population, as required by the Environmental Noise Directive (END) 49/2002/EC. The developed system will be able to classify vehicles by means of machine learning systems applied to images, according to the acoustic criteria required by the prediction models of the END, and to process them with a traffic simulation model capable of estimating the flows in the unmonitored sections of the network. The traffic of the whole network will be the input for the noise maps that will provide the exposure levels of citizens according to the END.