Ecological data reveal imbalances in human–human collision avoidance due to dyads' social interaction

Humans navigate public spaces safely and smoothly using complex collision avoidance strategies. Traditional models of human–human collision avoidance often draw from physics, relying on repulsive forces, but the effect of social factors on these strategies is not well understood. This study examines frontal encounters between single pedestrians and two-person groups (dyads), investigating the contributions of each party to collision avoidance and the impact of social interaction within the group. Using an ecological dataset of pedestrian trajectories, we measured deviations from a straight path as a proxy for collision avoidance. Our findings reveal a systematic imbalance and significant effects of social interaction on collision avoidance. Single pedestrians tend to prioritise trajectory efficiency in undisturbed situations and are the primary contributors to avoidance during encounters, adjusting their paths according to the dyad's interaction level. For dyads, social interaction correlates with lower efficiency in undisturbed cases and reduced responsiveness during encounters. An analysis of the impact parameter further shows that collision risk influences path deviations: individuals demonstrate larger deviations in response to highly interactive dyads, both in high-risk and less critical encounters. For dyads, the difference in deviation between low and high interaction levels is most pronounced when the single pedestrian is on a near-collision course. These results deepen our understanding of human pedestrian navigation, illustrating dynamical and social implications of group dynamics.