![Figure 3: Distribution of DTs across the target vehicle's approach. (1) Target vehicle emerges behind building, (2) target vehicle starts yielding, (3) target vehicle comes to standstill. Bin width based on Doane's formula [20]. There are no separate figures for AVs and CVs because the distributions were nearly identical.](https://www.researchgate.net/profile/Daniel-Eisele/publication/383959233/figure/fig2/AS:11431281278438966@1726646836928/Distribution-of-DTs-across-the-target-vehicles-approach-1-Target-vehicle-emerges_Q320.jpg)
September 2024
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2 Citations
The proportion of highly automated vehicles in traffic (i.e., the prevalence of AVs) is likely to increase over time. The aim of this study was to investigate whether the prevalence of AVs may influence how pedestrians interact with AVs and with conventional, human-driven vehicles (CVs). A video-based laboratory study was conducted using a two-group mixed design. Participants took the perspective of pedestrians about to cross the road in a situation where AVs (with eHMIs) and CVs were approaching their position. The prevalence of AVs was manipulated between groups (low/high). The participants indicated the moment they decided to cross in front of the vehicles. Our results show that AV prevalence did indeed significantly influence when participants decided to cross. Overall, participants decided to cross earlier in front of the more prevalent vehicle type. Therefore, taking into account the given prevalence of AVs could significantly benefit AVs in predicting pedestrian behavior.