# Stabilization Time of Running Equivalent Level \(\mathbf{L_{Aeq}}\) for Urban Road Traffic Noise
## 3 Results and Discussion

Table 2: Percentage of \(ST\) values \(\leq 15\) min for each road type and uncertainty \(\varepsilon\). Figure 4: Median hourly \(ST\) values for the three preset uncertainty \(\varepsilon\) of the \(L_{Avg,lh}\) estimate versus median hourly road traffic flow \(Q_{h}\). The green dashed line corresponds to the measurement time \(t=15\) min, often used in common practice for road traffic noise measurement. The \(ST\) values decrease with road traffic flow increasing and from F road type to A, as well as with increasing of the uncertainty \(\varepsilon\). The horizontal dotted green line corresponds to the time \(t=15\) min, often used in common practice for road traffic noise measurement. It is evident that this duration of the measurement time is acceptable only for road type A and low accuracy of the \(L_{A\alpha,\mathit{1h}}\) estimate (Figure 5a), barely acceptable for road types D and E for road traffic flow \(Q_{\mathit{h}}>700\)-1200 vehicles/h (Figure 5b,c), and never acceptable for road type F (Figure 5d), unfortunately the more diffuse in an urban area. Table 3 reports the values obtained for the constants \(a\) and \(b\) in the regression Equation (5), showing for A and D road types a stronger dependence of stabilization time on the traffic flow. This is essentially due to the more regular traffic dynamics observed for these types of roads. Figure 5: 75 th percentile of \(ST\) values for the three preset uncertainties \(\varepsilon\) of the hourly \(L_{A\alpha,\mathit{1h}}\) estimate, grouped by the four road types ((**a**–**d**)-letters refer to road types A, D, E, F) and hour, versus median hourly road traffic flow \(Q_{\mathit{h}}\). Figure 5 shows the large influence of road traffic flow on the length of stabilization time and, therefore, the knowledge of this data is essential for an estimate of \(ST\) values. Figure 6 shows the median hourly road traffic flow computed for the examined dataset and the four road types. The pattern is rather similar for all roads, with peaks at 8 and 18 h, more pronounced for local roads (F) than for the other types. The flows decrease from 18 to 4 h and increase again afterwards. The flow data in Figure 6 can be input in the regression equations (Equation (5)) to obtain an estimate of the \(ST_{75}\) value for each type of road and uncertainty \(\varepsilon\). For instance, Figure 7 reports the estimated \(ST_{75}\) values for each type of road at each hour for an uncertainty \(\varepsilon=\pm 1.0\) dB(A). The values are rather stable in the daytime from 8 to 18 h; afterwards they increase until 2-4 h in the night, depending on the road type, and decrease again until 8 h. The horizontal green dotted line at \(ST_{75}=15\) min clearly shows that this measurement time is not appropriate for all roads at any hour, with the exception of motorways (type A), excluding the night period 0-4 h. The above pattern is rather similar for the other two accuracy intervals, and Table 4 gives the mean values in the day period 7-19 h of \(ST_{75}\) values estimated by Equation (5) for each road type and uncertainty \(\varepsilon\). It is clear that the measurement time \(t=15\) min is appropriate only for a large uncertainty, \(\varepsilon\geq\pm 1.5\) dB(A), and acceptable for motorways (road type A) for uncertainty \(\varepsilon=\pm 1.0\) dB(A).