## 2 Pass-By Noise Annoyance Evaluation Experiment
### Results  
For a statistical analysis of the results, Shapiro-Wilk tests were used to check that the resulting dataset fulfilled the requirements for conducting a repeated measure analysis of variance (ANOVA). The annoyance ratings of the 40 recorded car sounds, which were averaged over all participants' scores, were sorted in ascending order, as shown in Figure 3.  
The results show that the annoyance levels of the vehicle sounds were rated in the range of 15 (slightly annoying) to 93 (extremely annoying). Most of the electric vehicle sounds were rated less annoying than ICE vehicle sounds. These results are in line with the literature data [15; 16; 17; 32; 33]. There are some very annoying electric cars with an AVAS, but at the same time, there are some slightly annoying electric cars with an AVAS. As expected, the AVAS will increase the annoyance of electric car sounds, but the type of AVAS sound plays an important role in the perception. Some AVAS sounds were rated less annoying than other AVAS sounds. Our previous studies showed that it is possible to design minimally annoying AVAS sounds that are detected at a safe distance in traffic [16]. Figure 3: The annoyance ratings of various car pass-by noises. In the ratings, 100 means extremely annoying and 0 means not at all annoying. Abbreviations: EV: electric vehicle without a warning sound, EV AVAS: electric vehicle with a warning sound, ICE G: gasoline internal combustion engine vehicle, ICE D: diesel internal combustion engine vehicle, H: hybrid vehicle. Figure 2: Rating scale used in this study. To understand which parameter can describe the perceived annoyance most appropriately, various analyses were conducted. First, the sound pressure levels of the car sounds were calculated. A regression analysis between the sound pressure levels in dB(A) and the annoyance judgments of the 40 vehicle sounds resulted in a coefficient of determination, which quantifies the strength of a linear relationship and the proportion of explained variance [34], R\({}^{2}\) = 0.34. Figure 4 shows the relationship between the annoyance rating and the average sound pressure level. The correlation between the average sound pressure level and the annoyance ratings is very low. The sounds of both car groups, such as ICE (red dots) and hybrid/electric (green/blue dots), form two different groups, because the annoyance ratings of both groups differ from each other as discussed at Figure 2. The sounds of electric and hybrid electric passenger cars cause in most cases less annoyance than the sounds of ICE cars. Their average sound pressure levels are slightly lower or comparable to those of ICE cars. Figure 4: The relationship between perceived annoyance ratings and sound pressure level in dB(A). Different colors are used in the figure to represent three different passenger car types. Color representation is also used in the Figures 5–8. Red dots correspond to the internal combustion engine cars, green dots represent the hybrid cars, and blue dots represent the electric cars. Figure 5: The relationship between perceived annoyance ratings and the maximum sound pressure level in dB(A). (Red dots: ICE cars, green dots: hybrid cars, and blue dots: electric cars). Previous studies showed that the maximum sound pressure level occurring in the interval of a vehicle pass-by is a better measure than the average sound pressure level [35; 36]. The maximum sound pressure level (Lmax) values of the vehicle sounds and the annoyance ratings are shown in Figure 5. The regression resulted in a coefficient of determination of R\({}^{2}\) = 0.65. This result shows that the maximum sound pressure level is more suitable for describing the perceived annoyance than the average sound pressure level, because the correlation between the annoyance ratings and the average sound pressure level is very low (R\({}^{2}\) = 0.34). Both the average and maximum sound pressure levels, which can be easily measured and determined, describe the perceived annoyance to a limited extent.