Studying pedestrians’ crossing behavior when interacting with automated vehicles using virtual reality

Partially and fully automated vehicles (AVs) are being developed and tested in different countries. These vehicles are being designed to reduce and ultimately eliminate the role of human drivers in the future. However, other road users, such as pedestrians and cyclists will still be present and would need to interact with these automated vehicles. Therefore, external communication interfaces could be added to the vehicle to communicate with pedestrians and other non-automated road users. The first aim of this study is to investigate how the physical appearance of the AV and a mounted external human-machine interface (eHMI) affect pedestrians’ crossing intention. The second aim is to assess the perceived realism of Virtual reality based on 360° videos for pedestrian crossing behavior for research purposes. The speed, time gap, and an eHMIs were included in the study as independent factors. Fifty-five individuals participated in our experiment. Their crossing intentions were recorded, as well as their trust in automation and perceived behavioral control. A mixed binomial logistic regression model was applied on the data for analysis. The results show that the presence of a zebra crossing and larger gap size between the pedestrian and the vehicle increase the pedestrian's intention to cross. In contrast to our expectations, participants intended to cross less often when the speed of the vehicle was lower. Despite that the vehicle type affected the perceived risk of the participants, no significant difference was found in crossing intention. Participants who recognized the vehicle as an AV had, overall, lower intentions to cross. A strong positive relationship was found between crossing intentions and perceived behavioral control. A difference in trust was found between participants who recognized the vehicle as automated, but this did not lead to a difference in crossing intentions. We assessed the research methodology using the presence questionnaire, the simulation sickness survey, and by comparing the results with previous literature. The method scored highly on the presence questionnaire and only 2 out of 55 participants stopped prematurely. Thus, the research methodology is useful for crossing behavior experiments.