Data-driven physics-based modeling of pedestrian dynamics¶
Python package to create physics-based pedestrian models from pedestrian trajectory measurements. This package is an implementation of the data-driven generalized pedestrian model presented in:
Pouw, C. A. S., van der Vleuten, G., Corbetta, A., & Toschi, F. (2024). Data-driven physics-based modeling of pedestrian dynamics. Phys. Rev. E 110 (6 Dec. 2024), p. 064102. DOI: 10.1103/PhysRevE.110.064102.
Abstract. We introduce a data-driven physics-based generalized Langevin model that allows robust and generic modeling of pedestrian behavior across any environment where extensive pedestrian trajectory data is available. Our model effectively captures the complex interplay between the deterministic movements and stochastic fluctuations associated with walking.
