## 1 Introduction  
According to the data provided by the European Environment Agency (EAA), \"more than 41 million people are reported to be exposed above 55 dB \(\mathrm{L_{den}}\) due to road traffic noise inside urban areas\", and nearly 90 million are estimated in Europe [1]. Road traffic noise is the most diffuse noise source in urban areas, wide spreading in space and time, despite the noise reduction actions implemented by policies and legislations at international and national level. As a consequence, the people's awareness towards the adverse health effects, both direct and indirect, produced by road traffic noise is increasing. The World Health Organization (WHO) has estimated that \"at least one million healthy life years are lost every year from traffic related noise in the western part of Europe\" [2]. There is evidence in the literature that \"sleep disturbance and annoyance, mostly related to road traffic noise, comprise the main burden of environmental noise\" [2]. \(\mathrm{L_{den}}\), introduced by the European Directive 2002/49/EC on the assessment and management of environmental noise [3], is commonly applied by legislation to assess urban sound environments. However, although energetic indicators show good correlations with long term annoyance, their deficiency for evaluating perceptively urban sound environments has been pointed out in several studies [4]. In particular, they fail in evaluating fluctuating sounds, which are very common in urban areas and negatively impact noise annoyance. Road traffic noise is typically characterized by the noise events owing to the single vehicle pass-by, where the temporal structure of sound pressure level (SPL) varies between local one-lane city roads, showing highly intermittent noise, up to wide multi-lane motorways, producing a nearly continuous noise with very limited fluctuations. There is clear evidence in the literature that human hearing is able to adapt to steady noise easier than to SPL fluctuations, as well as to prominent, salient noise events [5; 6]. The higher these fluctuations are, the more annoying a sound is possibly perceived. To quantify these SPL fluctuations and variations, common approaches either apply thresholds to detect events exceeding such thresholds and count the number and the duration of these events, or use SPL statistics, like percentile levels L\({}_{\text{A1}}\), L\({}_{\text{A5}}\), and L\({}_{\text{A10}}\), namely the A-weighted SPL exceeding for 1%, 5%, and 10% of the measurement time, respectively. Recently, a new descriptor has been proposed [7], describing the eventualness (or intermittency) of noise exposure, taking into account both the number and the magnitude of noise events during a certain time period. The metric, named the intermittency ratio (IR), accounts for all sound energy contributions that exceed a given threshold and, by definition, only takes on values between 0% and 100%. It can be derived either directly from acoustic measurements or calculated from traffic and geometric data for any transportation noise source and any time period. However, as pointed out in [7; 8], IR could be a supplementary metric accompanying the continuous equivalent level (L\({}_{\text{Aeq}}\)), which measures the energy content of the noise exposure. The present paper starts from the results obtained in a previous application of IR on the noise data from road traffic, monitored continuously for 24 h in 90 sites in the city of Milan [8; 9]. The database comprised 251 24-h long time series of 1 s A-weighted SPL, monitored at different types of roads, from motorways to local roads with very low traffic flow. The hourly values of L\({}_{\text{Aeqh}}\), each referring to the corresponding day-time L\({}_{\text{Aeqd}}\) (06:00-22:00), and IR were computed and processed by clustering methods to figure out a criterion to classify the urban sites considering road traffic noise features.