## 2 Materials and Methods
### Collecting and Processing Data  
The video camera recordings were analysed, and the data were entered in the statistical software package IBM SPSS Statistics v. 28. The analysis of the video recording was performed by three members of the team at the same time in order to reduce the possibility of error and to adjust all the data. The following data were extracted from the video material:  
* E-bicycle riding scenario (e-bicycle speed: categorical variable--25 km/h (NT = 375), 30 km/h (NT = 441), and 35 km/h (NT = 412); use of equipment: categorical variable--helmet (NT = 356), reflective vest (NT = 277), helmet and reflective vest (NT = 260), no equipment (NT = 335));* Vehicle categories (categorical variable: passenger cars (NT = 981), light goods vehicles (NT = 58), heavy goods vehicles (NT = 28), buses (NT = 34), motorcycles (NT = 25), SUVs (NT = 60), and taxis (NT = 42));
* Lateral distance of the motor vehicle when overtaking the e-bicycle (continuous variable: units--meter and centimetre). \begin{table}
\begin{tabular}{c c} \hline \hline
**Driver Protective Equipment** & **Description** \\ \hline \multirow{7}{*}{**E-bicycle**} & A KTM electric bicycle named “MACINA Moto 11” was used in the research. The frame of the e-bicycle is grey and made of aluminium; the motor is “Bosch drive unit 36 V-250 W”, the battery is “Powerpack 13.8 Ah—500 Wh”, and the wheel size is “29”. The bicycle has three riding modes: riding without using the electric motor, riding using the electric motor as an assistance to pedalling, and riding using the electric motor. The maximum speed of this e-bicycle is 45 km/h, while its maximum range of 80 km was used in the research. \\ \hline \multirow{2}{*}{**Helmet**} & The helmet used in this research is “Uvex City 9”, black, weighing 440 g, intended for e-bicycle users, made in accordance with the standard “EN 1078/NTA 8776:2016”, with reflective straps and logos. \\ \hline \multirow{7}{*}{**Reflective vest**} & The test bicyclist wore a fluorescent yellow bicycling vest with silver retroreflective material on the shoulders and front and back totalling about 400 cm\({}^{2}\)([PERSON] et al., 2012 [41]). Figure 3 shows an e-bicycle ride with a protective helmet, with a vest, with a helmet and vest, and without equipment (helmet and vest). \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Description of the characteristics of the driver protective equipment. Figure 2: Location of the study area. The normality of the distribution was tested using an inspection of histograms and the Kolmogorov-Smirnov test. Since the data for all the measured variables were normally distributed, parametric methods were used. The analysis of variance (ANOVA), three-way ANOVA, two-way ANOVA, and \(t\)-test were used to assess the significance of differences. The Bonferroni post hoc test was used for additional comparison between groups [47; 48]. The main hypothesis (H\({}_{0}\)) was: There are no significant differences in the lateral distance between the e-bicycle and the overtaking vehicle depending on the equipment use and riding conditions. The alternative hypotheses (Ha) were:  
**Hypothesis 1 (H1). **_There are statistically significant differences in the lateral distance between the e-bicycle and the overtaking vehicle depending on the e-bicycle speed (25 km/h, 30 km/h, 35 km/h)._  
**Hypothesis 2 (H2). **_There are statistically significant differences in the lateral distance between the e-bicycle and the overtaking vehicle depending on the e-bicyclist's use of the protective helmet and reflective west._  
**Hypothesis 3 (H3). **_There are statistically significant differences in the lateral distance between the e-bicycle and the overtaking vehicle depending on the e-bicyclist's use of the protective helmet._  
**Hypothesis 4 (H4). **_There are statistically significant differences in the lateral distance between the e-bicycle and the overtaking vehicle depending on the e-bicyclist's use of the reflective west._  
**Hypothesis 5 (H5).