## Materials and Methods
### Analysis  
The influence of the several variables addressed in this study on the participants' crossing decision-making was analyzed in terms of _percentage of crossings_, to infer about the impact of the considered variables (speed pattern and auditory condition) on the effective decision of the participants; _response time_, to evaluate the time that the participants needed to make their decision when they decided to cross; and _time-to-passage (TTP)_, which, although indirectly related to the response time, can ultimately serve as a risk-taking indicator. Here, lower TTPs at the crossing moment were assumed to be indicative of a riskier behavior, as the participant would have less time to cross the road in a real situation.  
The percentage of crossings was calculated, for each participant, considering the number of answers, i.e., the trials for which they have clicked the computer mouse before the vehicle has stopped or passed in front of them, and the total number of trials per condition. For those trials in which the participant did not click, it was assumed that the participants would only cross after the vehicle passed, and no conflict was considered. The response time, which was the time from the start of the stimulus presentation to the moment the participant clicked the mouse, was also registered. The TTP (s), also called time-to-arrival (e.g., [17; 20]), was calculated based on the moment in which the participant clicked the mouse. This variable is generally defined as the time it would take for an object (vehicle) to reach the frontal plane of an observer (participant) [31], given by:  
\[\text{TTP}=\text{D}_{\text{vehicle-conflict point}}\,/\,\text{V}_{\text{vehicle}}, \tag{1}\]  
where \(\text{D}_{\text{vehicle-conflict point}}\) is the distance, in meters, from the center of the vehicle's license plate, assumed as the possible point of impact, and participant's frontal plane at the moment when he or she started to cross, and Vvehicle is the vehicle speed, in meters per second, at the moment the participant started to cross.  
As mentioned in the Introduction, an impact of the noise level on the participants' decision-making was expected. With stimuli with higher noise levels, such as those related to the approach of the gasoline vehicle (see Table 3), the participants would be able to better estimate the vehicle's trajectory and would risk less, which would be translated into higher TTP values and a lower percentage of crossings. A faster decision-making for the gasoline vehicle due to the facilitated trajectory estimation was also expected. In turn and following the same increased saliency of the approaching cues, faster decisions and less risky behavior for electric vehicles when compared with those in which no sound was presented were also expected to be found.  
The influence of the variables such as the auditory condition and the vehicle speed pattern on the percentage of crossings was assessed using a three-way repeated-measures ANOVA and Bonferroni-corrected post-hoc tests. Due to the presence of missing values in the database regarding the trials that participants did not feel safe to cross, Linear Mixed Models were used to assess the influence of the auditory condition and the vehicle speed pattern on response time and on TTP, accounting for repeated measures.