2023/08/14 by Korbmacher, Raphael, Nicolas, Alexandre, Tordeux, Antoine +1
#FOS: Physical sciences #Physics and Society (physics.soc-ph)
paper · doi:10.48550/arxiv.2308.07450
We give an overview of time-continuous pedestrian models with a focus on data-driven modelling. Starting from pioneer, reactive force-based models we move forward to modern, active pedestrian models with sophisticated collision-avoidance and anticipation techniques through optimisation problems. The overview focuses on the mathematical aspects of the models and their different components. We include methods used for data-based calibration of model parameters, hybrid approaches incorporating neural networks, and purely data-based models fitted by deep learning. The conclusion outlines some development perspectives that we expect to grow in the coming years.