A Microscopic ‘‘Social Norm’ ’ Model to Obtain Realistic Macroscopic Velocity and Density Pedestrian Distributions

Abstract

We propose a way to introduce in microscopic pedestrian models a ‘‘social norm’ ’ in collision avoiding and overtaking, i.e. the tendency, shared by pedestrians belonging to the same culture, to avoid collisions and perform overtaking in a preferred direction. The ‘‘social norm’ ’ is implemented, regardless of the specific collision avoiding model, as a rotation in the perceived velocity vector of the opponent at the moment of computation of the collision avoiding strategy, and justified as an expectation that the opponent will follow the same ‘‘social norm’ ’ (for example a tendency to avoid on the left and overtake on the right, as proposed in this work for Japanese pedestrians). By comparing with real world data, we show that the introduction of this norm allows for a better reproduction of macroscopic pedestrian density and velocity patterns