Automated vehicles (AVs) reached technological maturity and will soon arrive on streets as traffic participants.Human traffic participants such as drivers, pedestrians, or cyclists will be increasingly confronted with the presence of AVs within their environment, not necessarily knowing or understanding what to expect and how to interact with them.Although AVs are designed to act safely, effective interaction in mixed traffic scenarios will depend on successful communication, interaction, or even negotiation beyond static rules and regulations.Prosocial behavior, such as yielding one's right of way, will be needed to resolve unclear traffic situations or foster traffic flow.However, what are the characteristics of such prosocial behavior, and how to measure this not only for automated vehicles

Drones are rapidly populating human spaces, yet little is known about how these flying robots are perceived and understood by humans. Recent works suggested that their acceptance is predicated upon their sociability. This paper explores the use of facial expressions to represent emotions on social drones. We leveraged design practices from ground robotics and created a set of rendered robotic faces that convey basic emotions. We evaluated individuals’ response to these emotional facial expressions on drones in two empirical studies (N = 98, N = 98). Our results demonstrate that individuals accurately recognize five drone emotional expressions, as well as make sense of intensities within emotion categories. We describe how participants were emotionally affected by the drone, showed empathy towards it, and created narratives to interpret its emotions. As a consequence, we formulate design recommendations for social drones and discuss methodological insights on the use of static versus dynamic stimuli in affective robotics studies.