## 5 Results of Analysis
### The Results of VDV Analysis  
The same events analyzed using the RMS method were subjected to VDV analysis. The duration of the events ranged from 11 to 19 s. The results of the VDV analysis along with the collective summary of HPVI indicators calculated in the RMS analysis are presented in Table 4.  
Values that exceed the thresholds defined by the Polish standard [15] for the perception of vibrations by people in buildings (WODL \(>\) 1.0) or correspond to a low probability of complaints from residents during the daytime (VDV \(>\) 0.2) are marked in yellow. For the purpose of comparing the results obtained by the RMS method and the VDV method, the following assumptions were made:  
* A low probability of complaints is compared with exceeding the threshold of vibration perception by people,
* The possible occurrence of complaints is compared with the level of requirements for ensuring necessary vibrational comfort. Based on the VDV method research, fewer events were found in which there was a low probability of resident complaints. These are two events related to subway train passages. Vibrations generated by tram passages are imperceptible. Based on the  
Figure 8: RMS analysis of metro train passage. results of the assessment performed using the VDV method, it can be stated that 18% of events caused by subway train passages result in a low probability of complaints. Based on the measurement results, an attempt was made to analyze the correlation between two methods of determining the impact of vibrations on people in buildings: RMS (in the form of the HPVI index) and VDV. The result of this analysis is shown in Figure 9. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No** & **Type of Vehicle** &
\begin{tabular}{c} **Duration Time** \\ **[s]** \\ \end{tabular} & **VDV [m/s\({}^{1.75}\)]** & **HPVI/f [-/Hz]** \\ \hline
1 & tramway & 19 & 0.050 & 0.48/12.5 \\ \hline
2 & tramway & 11 & 0.049 & 0.49/12.5 \\ \hline
3 & bus & 11 & 0.094 & 1.01/12.5 \\ \hline
4 & tramway & 18 & 0.088 & 0.86/12.5 \\ \hline
5 & heavy truck & 12 & 0.161 & 1.72/12.5 \\ \hline
6 & bus & 12 & 0.065 & 0.75/12.5 \\ \hline
7 & tramway & 12 & 0.050 & 0.52/12.5 \\ \hline
8 & bus & 12 & 0.043 & 0.58/12.5 \\ \hline
9 & tramway & 14 & 0.073 & 0.49/12.5 \\ \hline
10 & tramway & 12 & 0.049 & 0.53/12.5 \\ \hline
11 & tramway & 12 & 0.041 & 0.42/12.5 \\ \hline
12 & tramway & 12 & 0.070 & 0.77/12.5 \\ \hline
13 & metro train & 18 & 0.171 & 0.83/40 \\ \hline
14 & metro train & 18 & 0.142 & 0.70/40 \\ \hline
15 & metro train & 18 & 0.214 & 1.28/40 \\ \hline
16 & metro train & 17 & 0.144 & 0.71/40 \\ \hline
17 & metro train & 16 & 0.119 & 0.57/40 \\ \hline
18 & metro train & 18 & 0.152 & 0.71/40 \\ \hline
19 & metro train & 18 & 0.166 & 0.94/40 \\ \hline
20 & metro train & 18 & 0.162 & 1.03/40 \\ \hline
21 & metro train & 16 & 0.322 & 1.18/40 \\ \hline
22 & metro train & 18 & 0.146 & 0.90/40 \\ \hline
23 & metro train & 18 & 0.198 & 0.82/40 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The VDV values for individual events and the maximum HPVI values in the events. Figure 9: Correlation between HPVI and VDV values in analyzed building. The correlation between HPVI and VDV is equal to 0.67 which suggests a strong correlation between HPVI index and VDV value, but not too strong for exact prediction of one of the factors knowing the other. The regression equation for the relationship between HPVI and VDV is:  
\[\text{HPVI}=2.92\text{-}\text{VDV}+0.44 \tag{5}\]  
This equation indicates that for every unit increase in VDV, HPVI increases by approximately 2.92 units, starting from a base value of 0.44 when VDV is zero. This suggests a strong positive linear relationship between these two variables, confirming the moderate to strong correlation previously discussed. The descriptive statistics for HPVI and VDV across different types of vehicles show differences:  
For HPVI:  
* Metro trains have a mean HPVI of approximately 0.88 with a standard deviation of 0.22, indicating a wider range of HPVI values.