Jakub Suchojad¹, Samuel S. Sohn¹, Michelle Shlivko¹, Karin Stromswold¹, Jacob Feldman¹; ¹Rutgers University

How do people navigate through crowded, dynamic environments? We investigated social wayfinding (navigation influenced by other people) in virtual reality (VR). Using a VR headset, we placed our participants in a virtual train station and asked them to physically navigate to one of the two exit gates while under time pressure. The station included several obstacles, and a number of virtual humans ("agents"), some static and others walking. The walking agents passed single file in two rows approximately perpendicular to the participant's path, requiring the participants to navigate through gaps between the agents. In a series of experiments, we manipulated the sitting agents' presence, the walking agents' direction, and the time allotted for subjects to reach the gate. Our analyses focused on the balance between global planning, in which the wayfinder plots the entire path from beginning to end, and local planning, in which the wayfinder continually modifies their path in light of newly encountered obstacles. We found evidence for local wayfinding from several sources. First, though most subjects went directly towards the target gate, following a global plan, some subjects switched midway from the foil to target gate, suggesting a more local strategy. Second, even subjects who consistently headed to the target gate decelerated as they approached the room's midpoint, suggesting local path modifications to pass through a "gap" between agents. In Exp. 3, we collected participants’ eye gaze as they traversed the room. Participants fixated almost exclusively on moving agents and other informative elements of the environment (e.g., the sign that identified the target gate or the countdown timer). In sum, participants’ movements and eyegaze provide evidence for both global and local decision-making in a social wayfinding task. Our study demonstrates an interplay of both strategies, with the balance depending on the progression of available information.

Acknowledgements: NRT-FWHTF: Socially Cognizant Robotics for a Technology Enhanced Society (SOCRATES) Grant No. 2021628