Conflicting Tendencies in Pedestrian Wayfinding Decisions: a Multi-Agent Model Encompassing Proxemics and Imitation

Computer-based simulation of pedestrian dynamics is a consolidated application of agent-based models but it still presents open challenges. The wayfinding of pedestrians is a fundamental aspect to allow the application of such models on complex environments. Several novel approaches have recently been proposed in the literature, yet the lack of empirical knowledge still limits the reliability of the heuristics used in the models. In this paper, a novel model for the simulation of pedestrian wayfinding is discussed and the aim is to provide general mechanisms that can be calibrated for the reproduction of empirical evidences. The model is, in fact, inspired by the behaviors observed in a experiment performed with human volunteers in November 2015, which were put into a trade off scenario, since different paths were available but the shortest one was quickly congested. We observed that several pedestrians choose longer trajectories to preserve high walking speed, and often do so following a first emerging leader. The proposed model encompasses both a proxemic tendency to avoid congestion, as well as an imitation mechanism: these conflicting tendencies can be calibrated according to empirical evidences. A demonstration of the simulated dynamics on a larger scenario will be illustrated in the paper.