Developing a Data-Driven Social Force Model for Pedestrian Simulation

This case-study-driven presentation explores pedestrian modelling using the Social Force Model, featuring a data-informed approach to optimise simulations through trajectory data and machine learning techniques. It analyses the predictive accuracy of customised models and highlights their application in enhancing urban safety and public space designs. Concluding insights emphasise the integration of data-driven methodologies in urban planning and the strategic prospects for future research.