Crossing roads in a social context: How behaviors of others shape pedestrian interaction with automated vehicles

Abstract

Automated vehicles (AVs) are going to enter public roads in the near future and will inevitably encounter more than one pedestrian on roads. Very little is known about how multiple pedestrians will interact with AVs and their external human–machine interfaces (eHMIs). This study investigates the social influence of others on the pedestrian decision-making process during their initial encounters with AVs. In a virtual reality experiment, 26 male and 55 female participants in three experimental conditions made crossing decisions – either alone or next to other simulated pedestrians – in front of AVs equipped with abstract eHMIs showing yielding or non-yielding intentions. The results show that the behaviors of others significantly influenced pedestrian crossing decisions. While the appropriate behaviors of others contributed to faster crossing decision-making, misleading behaviors of others led to riskier crossing decisions and greater difficulty in understanding the eHMIs. However, the impacts from others on pedestrian crossing decisions disappeared once participants became more familiar with eHMIs. Qualitative data revealed that participants acquired knowledge about AVs and eHMIs through direct experience, observing others, and drawing from their past experiences. Additionally, there was a tendency among certain pedestrians to overly rely on and misuse eHMIs. To ensure the safe deployment of AVs, it is therefore essential to adequately educating the public about this novel technology and to optimize eHMI designs for effective communication with multiple pedestrians.