An optimization-based overtaking model for unidirectional pedestrian flow

We propose an optimization-based model for simulating the overtaking behaviour in the unidirectional pedestrian flow. A ‘visual area’ is introduced so that agents could receive the information regarding their surroundings and react by choosing one of three options: to move straight on, to dodge to the left, or to dodge to the right. And a side preference of each pedestrian for evading and overtaking is implemented based on traffic ‘social norms’. The model was validated by reproducing the experimentally obtained pedestrian flow patterns. The effects of the initial pedestrian formation on overtaking behaviour and the evacuation time have been analysed in different geometries. The results show that pedestrian flow patterns after overtaking are obviously influenced by both the initial positions and density of the slow pedestrians in the front. Phase changes of pedestrian formation are observed in both experiment and simulations. On the other hand, for sparse pedestrian crowds, the egress time of the fast individuals is mainly impacted by the horizontal distance between the initial positions of the slow pedestrians in the front, especially in the geometry with a bottleneck.