# Optimized Sensors Network and Dynamical Maps for Monitoring Traffic Noise in a Large Urban Zone
## 2 State of the Art
### The Spatial and Temporal Structure of Road Traffic Noise in Large Urban Zones
#### 2.3.1 Classification of Roads in Large Urban Zones by Their Road Traffic Noise  
It is well known that on a given road stretch traffic noise is strongly dependent on the type of traffic flow along it. The relationship between noise and flow is rather complex, and several models have been employed to understand it. In particular, the dependence of noise on the speed of vehicles is an issue (see, e.g., [19; 20]), and the classification of roads can be more complex than official records based on just standard considerations. Indeed, a careful study shows that, in the case of the official Italian roads classification, a more fundamental approach is required [65; 66; 67]. Based on these studies, and on those mentioned in the introductory discussion of Section 2.3, we develop a spatio-temporal method for road traffic noise based on the fact that vehicular flow forms a rather robust network, in the sense that its structure, and thereby the local road traffic flow, does not change significantly from day to day for working days. This allows us to classify the road stretches according to their mean daily traffic flows, while treating the traffic variations as a kind of perturbation from the mean values. In particular, we consider as noise sources just the road traffic noise in the form of both light and heavy vehicles, discarding all non-traffic-related noises (see the procedure described in Section 3.3.1). In order to build the method, we rely on measurements of both traffic noise and flow within a large urban zone, in our case the city of Milan [68]. The measurement locations, chosen more or less at random, cover the whole city quite uniformly (see Figure 1). Later, we will describe an optimized procedure to find suitable locations for the measurements, but a random choice is a good one to start with. The type of noise monitoring stations used are illustrated in Figure 2.  
The measured signals at 1 s resolution [68] were integrated to obtain the equivalent levels \(L_{\text{eq}}^{(\tau)}(t,s_{i})\), where \(\tau\) is the temporal interval of interest, \(t=n\tau\) (\(n\geq 1\)) is the time within the day at resolution \(\tau\), and \(s_{i}\) (with \(i=1,N_{m}\)) is the \(i\)th measurement site. In our case,  
Figure 1: The nine urban zones in the city of Milan (numbered within circles). The zone of interest in this work that is our pilot zone is the 9 th Zone (Z9). The red and blue full circles indicate the locations of traffic noise measurements performed during two different measurement campaigns [68]. Figure 2: The monitoring stations used during the noise measurement campaigns (red circles). (**A**) Fixed monitoring stations; (**B**,**C**) Semi-permanent monitoring stations; (**D**,**E**) Monitoring stations placed on cart or on mobile laboratory. All monitoring stations must be equipped with at least a class 2 sound level meter, which is able to produce the main noise indexes and the spectral trends in third-octave bands with a temporal resolution of 1 s. The monitoring activity is sized on a minimum measurement time of 24 h, starting at 6:00 a.m. and possibly extended on several days [68]. we have a total of \(N_{m}=93\) measurement sites. Regarding the time intervals, we consider \(\tau=(5,\,15,\,60)\) min for most of our analysis. Since different sites \(s_{i}\) have different traffic noise environments, yielding different absolute \(L_{\text{eq}}^{(\tau)}(t,s_{i})\) values, it is convenient to consider the deviations, \(\delta^{(\tau)}(t,s_{i})\), of the latter with respect to some reference value, \(L_{\text{eq}}^{(\tau_{0})}(t_{\text{ref}},s_{i})\), typical of the site location \(s_{i}\), given by  
\[\delta^{(\tau)}(t,s_{i})=L_{\text{eq}}^{(\tau)}(t,s_{i})-L_{\text{eq}}^{(\tau_ {0})}(t_{\text{ref}},s_{i}). \tag{1}\]  
In this way, we can study traffic noise behavior at different sites by studying the associated deviations along the whole day, which we denote as a normalized noise profile. In our preliminary studies, we take the reference time interval to be \(\tau_{0}=1\,\text{h}\).