Gender Profiling of Pedestrian Dyads

In traffic safety community, behavioral differences between genders have been attracting considerable attention in recent decades. Various empirical studies have proven that gender has a significant relation to drivers’, cyclists’ or pedestrians’ decision making, route choice, rule compliance, as well as risk taking/perception. However, most studies examine behavior of individuals, and only very few consider (pedestrian) groups with different gender profiles. Therefore, this study investigates effect of gender composition of pedestrian dyads on the tangible dynamics, which may potentially help in automatically understanding and interpreting higher level behaviors such as decision making. We first propose a set of variables to represent dyads’s physical/dynamical state. Observing empirical distributions, we comment on the effect of gender interplay on locomotion preferences. In order to verify our inferences quantitatively, we propose a gender profile recognition algorithm. Removing one variable at a time, contribution of each variable to recognition is evaluated. Our findings indicate that height related variables have a more strict relation to gender, followed by group velocity and inter-personal distance. Moreover, the “male” effect on dyad motion is found to somehow diminish when the male is paired with a female.