Understanding Passersby’s Information Needs in Public Co-presence with Robots

Encounters with robots in shared public spaces are becoming increasingly common, making human-robot coexistence an integral part of everyday life. Achieving this vision will require careful and thoughtful HRI design to ensure harmonious coexistence. Importantly, when people encounter robots in public spaces, they are often not the intended users of these systems but rather passersby who come across them incidentally. Understanding how passersby perceive and attend to robot behavior in such encounters is therefore essential for designing robots that are interpretable, and predictable. To address this, we conducted an eye-tracking field study to explore how passersby allocate their gaze during observation (non-direct) and encounter (direct) interactions, focusing on attention distribution across core robot states (going straight, stopping, and turning). The results show that information processing varied significantly depending on robot state and whether the interaction was an active encounter or passive observation, indicating that pedestrians adapt their attention allocation to both robot behavioral uncertainty and situational demands. The findings suggest that robot information design in public spaces should be proximity-aware and adaptive to the situational context.