When reactive agents are not enough: Tactical level decisions in pedestrian simulation

Pedestrian and crowd simulation is generally focused on operational level decisions, providing the choice of exact steps of pedestrians in a representation of the environment, with the aim of replicating observed patterns of space utilization, trajectories and timings. When relatively large environments are considered, though, tactical level decisions become equally important: in general, multiple paths can be followed to reach a target from an entrance or starting point, and path length might not be the only reasonable criterion. This paper presents a hybrid agent architecture for modeling different types of decisions in a pedestrian simulation system, encompassing a floor-field based operational level (based on a “least effort” principle) and an adaptive tactical level component, provided with a graph-like representation of the environment, considering both perceived congestion and characteristics of potential paths in the related decision. The model is experimented and evaluated both qualitatively and quantitatively in benchmark scenarios to show its adequacy and expressiveness.